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Structural Characterization of the Flavonoid Enzyme Complex
Christopher David Dana
Dissertation submitted to the faculty of the
Virginia Polytechnic Institute and State University
in partial fulfillment of the requirements for the degree of
Doctor of Philosophy
in
Biology
B.S.J. Winkel, Chair
D.R. Bevan
J.M. McDowell
J.C. Sible
R.A. Walker
July 8, 2004
Blacksburg, VA
Keywords: Flavonoids, Arabidopsis, chalcone synthase, chalcone isomerase
Copyright 2004, Christopher Dana
Structural Characterization of the Flavonoid Enzyme Complex
Christopher David Dana
Abstract
Flavonoid biosynthesis is an important secondary metabolic pathway in higher
plants with a range of vital functions in plants and animals. This pathway has been
developed as a model system for the study of multi-enzyme complexes. The goal of the
work presented here was to structurally characterize a series of loss-of-function chalcone
synthase (CHS) alleles and to define the molecular basis of the interaction between CHS
and the second enzyme of flavonoid biosynthesis, chalcone isomerase (CHI).
CHS proteins encoded by five previously characterized alleles were characterized
by homology modeling in an effort to explain the alterations in function, stability, and
dimerization exhibited by these variants. Four of the encoded proteins have a single
amino acid substitution and the fifth is a truncated protein resulting from a frameshift.
Models for each of these proteins were generated in silico and analyzed after molecular
dynamics simulations. This analysis suggested reasons for changes in catalytic ability
and stability for three of the five CHS variants.
To characterize the molecular basis of the CHS-CHI interaction, a model was
developed using X-ray crystallography, small-angle neutron scattering (SANS), in silico
docking, molecular dynamics simulations, and yeast 2-hybrid analyses. These enzymes
appear to be interacting in a manner that could facilitate the flow of intermediates from
one active site to another. These experiments also identified a series of amino acids that
appear to be involved in the interaction, which are currently undergoing alteration and
iii
analysis using a yeast 2-hybrid assay to verify the authenticity of the model. The data
presented herein could be used in future engineering experiments to alter pathway flux to
control the levels or types of flavonoid endproducts, resulting in more nutritious plants or
flowers with novel pigments.
These experiments advance the study of the structure of multi-enzyme complexes,
an area that currently contains little information. As well, this is the first known use of
SANS for the investigation of the architecture of metabolons. The techniques described
herein could easily be applied to other systems in an effort to better understand the
organization of multi-enzyme complexes and the implications of these assemblies on
metabolic regulation.
iv
Dedication
This work is dedicated to my family, especially my parents and brother, David,
Donna, and William Dana, who have been my biggest cheerleaders throughout this
endeavor. They have always urged me to pursue my dreams, and without them and the
rest of my family, I surely would not be who or where I am today.
v
Acknowledgements
There are, indeed, many people to thank for their help and support during my time
at Virginia Tech. First and foremost, I would like to thank my advisor, Dr. Brenda
Winkel, for allowing me to add my two cents to this amazing story. She patiently
listened to my sometimes hair-brained schemes on how to approach an experiment, and
offered invaluable support and guidance when something didn’t go quite as expected. I
also would like to express my gratitude to Dr. David Bevan, Dr. John McDowell, Dr. Jill
Sible, and Dr. Rich Walker for serving on my advisory committee and offering nothing
but support throughout my time here. Finally, I would like to thank all of the laboratories
in both Derring Hall and Fralin Biotechnology Center that have provided advice,
assistance, and facilities over the years.
This work could have not been done without the support of my collaborators. Dr.
David Bevan and Jory Zmuda provided invaluable assistance and advice on the molecular
dynamics simulations. Dr. Joe Noel, Dr. Joe Jez, Dr. Steph Richards, Mike Austin, and
Marianne Bowman at the Salk Institute introduced me to protein crystallography. Dr.
Susan Krueger at the NIST center for neutron research, introduced me to small angle
neutron scattering, and with her unwavering help and support, this project has come to
fruition.
I would also like to thank the members of the Winkel lab, both past and present
for their support and general joviality, which kept the environment of the lab good. I
thank Dr. David Saslowsky for guiding me along and putting up with my incessant
questions when I first got here. Many thanks go to Dr. Mike Santos, who handled my
teasing quite well, and was a wonderful mentor for the molecular biology lab. My
vi
gratitude also goes to Daniel “The Notorious HPLC” Owens for the many conversations
about science, life, and music over the years, for they have brightened my day on more
than one occasion. I would also like to thank Dr. Anne Walton, Dr. Ujwala Warek,
Melissa Ramirez, Ana Frazzon, and Michelle Barthet for their help and advice over the
years. In the cast of Winkel lab members, the group of undergrads cannot be overlooked.
Over the years, there have been many wonderful undergrads that have come through the
lab. My thanks go out to all of them and everything they contributed to the project and to
me, but most especially, Ashley Duda, Sandra Jabre, Anna Leung, Eric McFadden, Anna
Watson, Lori Hill, and Liz Tucker.
I have been extremely fortunate to have been surrounded by an amazing group of
people in my time here. First and foremost, I would like to thank James Glazebrook,
director of the New River Valley Symphony at Virginia Tech for allowing me the honor
of playing with his orchestra during my time here, it provided many hours of enjoyment,
learning, and stress relief. I would also like to thank Dr. Robert Goebel at James
Madison University for many hours of laughter from the puns, the reading suggestions
and helping me to look at things beyond science. Special thanks go to Becky Abler, Tom
Bunt, Mike Crandall, and Laura Moffett for their amazing friendship and support, which
has meant more to the completion of this dissertation than any of you will know. Many
thanks also go out to Tracey and Douglas Slotta for all of the support and kindness they
have shown me over the years. Friends in “The Other Group” have provided hours of
laughter and fun, without which I would have gone mad. For those friends who weren’t
mentioned here, your support and friendship has not gone unnoticed and has been a
source of strength for me.
vii
Table of Contents
Chapter 1: Literature Review……………………………………………………………...1
Introduction………………………………………………………………………..2
Metabolons………………………………………………………………………...3
Static vs. Dynamic Metabolons…………………………………………………...4
Metabolic Complexes and Whole Cell Visualization……………………………..4
Phenylpropanoid and Flavonoid Biosynthesis…………………………………….5
Regulation of Flavonoid Biosynthesis…………………………………………….8
Evidence for a Flavonoid Metabolon………………………………………...........9
Arabidopsis Flavonoid Biosynthesis as a Model System for Studying Metabolic
Pathways…………………………………………………………………………11
Structural Biology of Flavonoid Metabolism………………………………........12
Chalcone Synthase………………………………………………….........13
Chalcone Isomerase…………………………..……………………….....14
Methods to Determine Interactions Between Proteins…………………………..16
Small-Angle Neutron Scattering………………………………………....16
Surface Plasmon Resonance……………………………...……………...17
Project Goals/Rational……………………………………………...……………20
References Cited……………………………………………………...……….....22
viii
Chapter 2: Interpretation of Functional Effects of Mutations in Arabidopsis Chalcone
Synthase Based on Molecular Modeling………………………………………….……..44
Abstract……………………………………………………………………….…45
Introduction……………………………………………………………………...46
Methods ………………………………………………………………………....48
Results…………………………………………………………………………...50
tt4(85)…………………………………………………………………….51
tt4(UV113)……………………………………………………………….53
tt4(38G1R)……………………………………………………………….54
tt4(UV01)………………………………………………………………...55
tt4(UV25)………………………………………………………………...56
Discussion………………………………………………………………………..57
Acknowledgements…………………………………………………………........59
References Cited…………………………………………………………………60
Chapter 3: Structural Characterization of the Chalcone Synthase-Chalcone Isomerase
Interaction………………………………………………………………………………..75
Abstract………………………………………………………………………….76
Introduction…………..………………………………………………………….77
Materials and Methods…………………………………………………………..80
Site Directed Mutagenesis of pET32a(+)………………………………..80
Creation of Expression Constructs…………………………………........81
Expression and Purification of pCD1-CHS and CHI………………........82
ix
Determination of the CHS Crystal Structure…………………………….84
Multiple Sequence Alignment of CHS Proteins…………………............85
Site-Directed Mutagenesis……………………………………………….85
Yeast 2-Hybrid Analysis…………………………………………………86
Small-Angle Neutron Scattering…………………………………............87
In Silico Docking………………………………………………………...88
Molecular Dynamics Simulations……………………………………….88
Multiple Sequence Alignment of CHS and CHI………………………...89
Results…………………………………………………………………………...91
CHS Structure……………………………………………………………91
Experimental Evidence for a Role of Specific Residues in CHS in
Assembly of the Flavonoid Enzyme Complex ………………………….91
Small-Angle Neutron Scattering…………………………………............93
In Silico Docking and Molecular Dynamics Analysis of the CHS-CHI
Complex…………………………………………………………………94
Conservation of Residues Involved in the CHS-CHI Interaction……….96
Discussion……………………………………………………………………….97
Acknowledgements…..…………………………………………………...........100
References Cited…………………………………………………………..........101
Chapter 4: Conclusions…………………………………………………………………129
Appendix A: Homology Modeling of Flavonoid Enzymes……………………………135
x
Appendix B: SPR Analysis of Flavonoid Enzymes……………………………………139
xi
List of Tables and Figures
Chapter 1
Figure 1.1: Schematic of the flavonoid pathway in Arabidopsis
thaliana………………………………………………………………….36
Figure 1.2: Reaction catalyzed by CHS..………………………………..37
Figure 1.3: Structure of Medicago sativa CHS2..……………………….38
Figure 1.4: Close up of CHS2 active site………………………………..39
Figure 1.5: The reaction catalyzed by CHI…………….………………..40
Figure 1.6: The structure of CHI from Medicago sativa………………...41
Figure 1.7: Schematic representation of SANS………………………….42
Figure 1.8: Schematic representation of the principle of SPR…………...43
Chapter 2
Table 2.1: Biochemical and genetic characteristics of Arabidopsis CHS
alleles……………………………………………………………………63
Table 2.2: Dimensions of the CHS proteins.……………………………64
Table 2.3: Phi-psi torsion angles within the CHS active site……………65
Table 2.4: Distances between CoA binding residues.…………………...66
Figure 2.1: RMSD of the backbone atoms for wild-type CHS…………67
Figure 2.2: Multiple sequence alignment of selected regions of a
representative group of plant type III polyketide synthases……………..69
Figure 2.3: Structure of the Arabidopsis wild-type CHS enzyme….……71
xii
Figure 2.4: Models of the Arabidopsis wild-type and TT4 CHS
enzymes…………………………………………………………………..73
Chapter 3
Table 3.1: Crystallographic data…………………….………………….110
Table 3.2: Primers used for PCR and site-directed mutagenesis for yeast 2-
hybrid constructions………………………………………………….....111
Table 3.3: Yeast 2-hybrid analysis of amino acid substitutions…….….112
Table 3.4: Neutron Scattering Parameters for CHS and CHI in
solution………………………………………………………………….113
Table 3.5: RMSD and distance measurements of secondary structure and
residues proposed to be involved in the CHS-CHI interaction..………..114
Figure 3.1: Schematic of the flavonoid pathway in Arabidopsis
thaliana…………………………………………………………………115
Figure 3.2: CHS crystal structure………………………………………116
Figure 3.3: Residues on CHS tested for effects on interactions with other
flavonoid enzymes by yeast 2-hybrid…………………………………..117
Figure 3.4: Normalized SANS data…….………………………………118
Figure 3.5: Data fit of the docked CHS-CHI complex…………………120
Figure 3.6: Proposed structure of the CHS-CHI enzyme complex……..121
Figure 3.7: Movements of CHI beta sheets…….………………………122
Figure 3.8: Residues proposed to participate in the CHS-CHI
interaction………………………………………………………………123
xiii
Figure 3.9: Close up of the interaction interface between CHS and
CHI……………………………………………………………………...124
Figure 3.10: Multiple sequence alignments of Arabidopsis CHS and CHI
protein sequences……………………………………………………….125
Appendix A
Figure A.1: Homology models of Arabidopsis Flavonoid Enzymes…...137
Appendix B
Figure B.1: Representative SPR output………………………………...141
Curriculum vitae………………………………………………………………………..143
xiv
List of Abbreviations
ANR – anthocyanidin reductase
ANS – anthocyanidin synthase
BD – binding domain
C4H – cinnamate 4-hydroxylase
CHI – chalcone isomerase
CHS – chalcone synthase
DFR – dihydroflavonol 4-reductase
DTT - dithiothreitol
ER – endoplasmic reticulum
F3H – flavanone 3-hydroxylase
F3’H – flavonoid 3’-hydroxylase
FLS – flavonol synthase
HIV – human immunodeficiency virus
I(0) – forward scattering intensity
IGF – insulin growth factor
OAS-TL – O-acetylserine (thiol) lyase
PAL – phenylalanine ammonia lyase
PKS – polyketide synthase
PS – pyrone synthase
Rg – radius of gyration
rER – rough endoplasmic reticulum
xv
RMSD – root mean square deviation
SANS – small-angle neutron scattering
SAT – serine acetyltransferase
SPR – surface plasmon resonance
STS – stilbene synthase
TA – transactiviation domain
TCA – tricarboxylic acid
tt – transparent testa
TRX – thioredoxin
Chapter 1
Literature Review
2
Introduction
A driving question in the study of biochemistry is how metabolic pathways are organized
within the cell. Evidence for organized metabolism dates back to the 1950s when David Green
first isolated the enzymes of the tricarboxylic acid (TCA) cycle as a complex (Green, 1958).
Subsequent ultracentrifugation experiments with Neurospora (Zalokar, 1960) and Euglena
(Kempner and Miller, 1968) indicated that the aqueous cytoplasm contains little or no free
floating proteins or enzymes and that the interior of the cell is highly organized. These seminal
experiments revolutionized the concept of cellular organization and laid the groundwork for
future experiments aimed at defining metabolic organization within the cell. The advent of
interactome analyses (Ito et al., 2001; Li et al., 2004; Sanchez et al., 1999) provided new insights
into the extent to which cellular proteins are able to interact. As more examples of multienzyme
complexes, or metabolons, were identified, the notion that cellular metabolism is arranged as a
highly organized network of metabolic complexes gained widespread acceptance.
In our laboratory, we are investigating multi-enzyme complex formation in flavonoid
biosynthesis. Flavonoids are secondary metabolites that are important both for the plant and for
organisms that use plants for nutrition. Helen Stafford first suggested that flavonoid metabolism
is organized as one or more enzyme complexes (Stafford, 1974a; Stafford, 1974b), and later
experiments provided evidence for this (for example, Burbulis and Winkel-Shirley, 1999; Fritsch
and Grisebach, 1975; Hrazdina and Jensen, 1992). One of our goals is to determine the
molecular basis of the interaction between the first two enzymes in this pathway, chalcone
synthase (CHS) and chalcone isomerase (CHI), in the hope that this information will lead to a
better understanding of the architecture of enzyme complexes in this and other systems.
3
Metabolons
An enzyme complex is a group of two or more enzymes that interact to catalyze related
metabolic reactions, allowing for higher catalytic efficiency than if the enzymes were not
associated. Metabolic pathways can obtain such an efficiency by controlling the flux of substrate
and product thru channels between proteins (Ovádi and Srere, 2000). Metabolic channeling also
protects intermediates that are unstable or rare and maintains concentration gradients within the
complex (Mathews, 1993). The mechanics behind metabolic channeling include the covalent
binding of intermediates to the active site, a physical barrier acting as a tunnel, direct site-to-site
transfer, transfer in an unstirred layer, and electrostatic channels (reviewed in Ovádi and Srere,
2000).
The TCA cycle represents one of the best-characterized multienzyme complexes. Since
David Green isolated the TCA cycle complex, the functional and structural properties of the
TCA cycle complex have been well characterized in the laboratory of the late Paul Srere
(Robinson et al., 1987; Srere, 1985; Srere, 1987; Sumegi et al., 1993; Vélot et al., 1997; Vélot
and Srere, 2000). Srere’s work eventually led to the first three dimensional model of the citrate
synthase-malate dehydrogenase enzyme complex though in silico docking of the crystal
structures (Ovádi and Srere, 2000). There are now many more examples of this level of
organization, and it has been suggested that all metabolic pathways organize in this way
(Beeckmans et al., 1994; Beeckmans et al., 1989; Gontero et al., 1988; Robinson et al., 1987).
4
Static vs. Dynamic Metabolons
Enzyme complexes have been classified as being either static or dynamic (Welch, 1977).
Generally, static complexes are very stable over time and the interactions between the enzymes
are so strong that upon purification, the enzymes remain associated because little energy is
needed to maintain the integrity of the complex (Ovádi and Srere, 2000). In contrast, a dynamic
enzyme complex is held together by relatively weak forces and is dependent upon constant
energy dissipation (Welch, 1977) and is composed of multiple branch points where many
enzymes could compete for one substrate (Ovádi and Srere, 2000). It is generally thought that
static enzyme systems possess no branches, whereas dynamic enzyme systems may contain
many branches (Ovádi and Srere, 2000). Examples of static enzyme complexes are the α-keto
acid dehydrogenase complex, the proteasome, and proteins involved in DNA, RNA, and protein
syntesis (reviewed in Ovádi and Srere, 2000; Winkel, 2004). Two examples of dynamic enzyme
systems are the TCA cycle complex (Robinson et al., 1987) and enzymes involved in carbamoyl
phosphate metabolism (Massant and Glansdorff, 2004).
Metabolic Complexes and Whole Cell Visualization
There is a plethora of in vitro and in vivo evidence for protein-protein interactions and
macromolecular crowding within the cell. It has only recently been possible to visualize this
directly; however, there have been few examples of whole cell visualization showing enzyme
complexes and, ultimately, macromolecular crowding. An initial representation of
5
macromolecular crowding came from David Goodsell’s drawings of E.coli ribosomes, DNA, and
RNA to shape and scale and illustrated that the interior of the cell is crowded (Goodsell, 1991).
Electron tomography, an established technique, has recently gained new popularity for
visualization of macromolecular organization within cells. By using this technique, Hoppe et al.
(1974) were able to describe a complex of enzymes involved in fatty acid biosynthesis. As
computational power increased, electron tomography could be used to visualize organelles and
later whole cells. Marsh, et. al (2001) recently used this technology to show that the
environment around the Golgi apparatus in pancreatic ß cells is extremely congested. Elegant
work performed in Wolfgang Baumeister’s lab using electron tomographic imaging of whole
Dictyostelium cells showed that the cell is crowded with actin networks, membranes, and
macromolecular assemblies (Medalia et al., 2002).
Phenylpropanoid and Flavonoid Biosynthesis
The phenylpropanoid pathway converts phenylalanine into a variety of secondary
metabolites including lignins, sinapate esters, and stilbenes (Figure 1.1) that have a multitude of
in planta functions, such as reproduction, defense against fungal infections, and signaling in
pathogenesis and symbiosis (reviewed in Winkel-Shirley, 2001). Phenylpropanoid biosynthesis
also feeds into the flavonoid pathway, which converts coumaroyl-CoA and malonyl-CoA into
flavonoids, isoflavonoids, flavonol glycosides, anthocyanidins, and condensed tannins (Figure
1.1). In plants, these compounds have been postulated to function in reproduction, defense
against the biotic and abiotic environment, and signaling in pathogenesis and symbiosis. These
metabolites, along with sinapate esters derived from sinapic acid (Landry et al., 1995; Li et al.,
6
1993), protect the plant by absorbing light in the damaging UV-B spectrum (between 280 and
320 nm), acting as natural sunscreens for the plant. Flavonoids have been shown to accumulate
at the epidermal layer of leaf tissue, pollen where UV-B exposure is the highest as well as in the
epidermis of fruit (Chapple et al., 1992; Day, 1993; Jordan et al., 1998; Landry et al., 1995;
Solovchenko and Schmitz-Eiberger, 2003; Strack et al., 1985).
Other in planta activities for flavonoids include defense against pathogen attack,
signaling molecules, and regulators of auxin transport. Defense-related compounds, called
phytoalexins, are produced when the plant comes under attack from pathogenic fungi or bacteria
and, in the case of bacteria, are potent anti-microbial agents (Liu and Dixon, 2001). Certain
flavonoids such as naringenin, quercetin, kaempferol, and rutin, are constitutively produced and
thought to have some anti-microbial properties (Paiva, 2000). However, when a plant comes
under attack from fungal pathogens, some species produce glyceollin and medicarpin (both
isoflavonoid pterocarbons, and are also potent anti-microbial agents) in the foliage surrounding
the infection site (Paiva, 2000). In legumes, a specific class of flavonoids, the isoflavonoids, act
as signaling compounds that initiate the symbiosis of the nitrogen-fixing rhizobia (Hirsch et al.,
2001). Flavonoids have also been implicated in the regulation of auxin transport (Winkel-
Shirley, 2002). Recent studies showed that in Arabidopsis plants that are unable to produce
naringenin, auxin distribution resembles that of a plant overproducing auxin (Brown et al., 2001;
Buer and Muday, 2004; Murphy et al., 2000). Normal auxin distribution is restored upon the
application of exogenous naringenin.
Flavonoids are also responsible for pigmentation in flower, fruit, and vegetative tissue
(especially blue, red, and purple coloration), functioning as attractants for pollinators and seed
dispersers. These pigments have been the phenotype observed in some important scientific
7
breakthroughs such as Mendel’s elucidiation of genetics through the study of phenotypes in pea
(Pisum sativa), one being flower coloration. Altering the pigmentation of flowers is of intense
interest to the horticultural industry (Forkmann and Martens, 2001). The first example of
metabolic engineering of flower pigmentation came involved introduction of the maize gene
encoding dihydroflavonol 4-reductase (DFR) into Petunia, yielding flowers with a novel orange
color (Meyer et al., 1987). Recently, the color of Phalenopsis flowers were altered by a transient
transfection method using a putative flavonoid-3’,5’-hydroxylase from the same organism (Su
and Hsu, 2003).
Flavonoids exhibit a host of nutritional and medicinal properties including anti-oxidant
activities, which are useful in reducing the risk of cardiovascular disease and some cancers
(Dixon and Steele, 1999). Other beneficial properties of flavonoids include prevention of
bacterial infections, enzyme inhibition, and free radical scavenging (reviewed in Havsteen,
2002). Daidzin, an isoflavonoid, is a potent anti-diphsotropic agent that has been used as a
Chinese herbal remedy for alcohol dependence for over a millennium (Keung, 2003). In Asian
societies, the low incidence of cardiovascular disease and cancer has been, in part, linked to the
isoflavones produced in soybean, which is regularly consumed (Sarkar and Li, 2003). Dark
chocolate, interestingly, has the highest concentration of anti-oxidant flavonoids among
commonly-consumed foods (Lotito and Fraga, 2000; Serafini et al., 2003).
Creating plants with elevated levels of antioxidant flavonoids is a focus of recent
metabolic engineering projects. Work done at Unilever Research in the United Kingdom and
Plant Research International in the Netherlands demonstrated that expression of petunia CHI in
tomato plants induces a 78-fold increase of fruit peel flavonols without any change in visible
phenotype (Muir et al., 2001). Interestingly, when the fruit was processed, a majority of the
8
flavonols were retained. Yu et al. (2003) were able to increase the levels of isoflavones in
soybean seed by suppressing flavanone 3-hydroxylase (F3H), the entry point to flavonol,
condensed tannin, and anthocyanin biosynthesis, and activating expression of two transcription
factors required for isoflavonoid biosynthesis. These metabolic engineering efforts could create
edible plants that supplement diets with anti-oxidants to help protect against cancer and other
diseases.
Regulation of Flavonoid Biosynthesis
Flavonoid biosynthesis is tightly controlled by a number of internal and external factors.
It can be modulated by development, exposure to UV-B radiation, high intensity and blue light,
and both low and high temperatures (reviewed in Winkel-Shirley, 2002). The molecular basis of
this regulation has been intensely studied in parsley, petunia, snapdragon, maize, and
Arabidopsis and numerous transcriptional regulators have been identified and characterized (
reviewed in Marles et al., 2003; Sainz et al., 1997; Weisshaar and Jenkins, 1998).
In maize, two sets of transcription factors, the R family of regulatory proteins and the C1
myb-domain-containing transcription factors, appear to control the transcription of the entire
flavonoid pathway (Taylor and Briggs, 1990). However, other plants that contain homologues of
the maize transcription factors do not exhibit the same breadth of control over the pathway. For
example, an1, 2, 4, and 11 from petunia and delila from snapdragon all appear to be
homologues of the R family of genes in maize, but control the transcription of a more defined
subset of genes (Martin and Gerats, 1993; Spelt et al., 2000).
9
Much is also known about the regulation of flavonoid biosynthesis in Arabidopsis. Some
of the transcription factors that control flavonoid biosynthesis in Arabidopsis have been
identified by characterization of the transparent testa (tt) mutants. For example, TTG1, TTG2,
TT2, TT8, and TT16 encode transcription factors that control DFR and anthocyanidin reductase
(ANR) expression in the seed coat, and have been proposed to cooperate in controlling the
accumulation of proanthocyanidins in developing seed coats (Johnson et al., 2002; Nesi et al.,
2000; Nesi et al., 2002; Nesi et al., 2001; Walker et al., 1999). However, there are transcription
factors that are ubiquitous in their ability to regulate the expression of genes. ICX1 is such an
example which has been implicated in the negative regulation of both light and non- light
responses (Wade et al., 2003).
Evidence for a Flavonoid Metabolon
Helen Stafford’s original hypothesis that phenylpropanoid metabolism is organized as
one or more enzyme complexes (Stafford, 1974a; Stafford, 1974b) has been supported by
experiments performed in many laboratories, including our own (reviewed in Winkel, 2004;
Winkel-Shirley, 1999). Through microsomal fractionation experiments, Czichi and Kindl (1977)
demonstrated a close association of the first two enzymes of general phenypropanoid metabolism
[phenylalanine ammonia lyase (PAL) and cinnamate 4-hydroxylase (C4H)] with the endoplasmic
reticulum. Later evidence for channeling between these enzymes was obtained in experiments
where 3H-L-phenylalanine was fed to tobacco cell cultures. Little 3H-trans-cinnamic acid (the
product of PAL) was identified in the cells, suggesting that this product was rapidly channeled
10
through the general phenylpropanoid pathway (Rasmussen and Dixon, 1999). Evidence for a
multi-enzyme complex and channeling has also been obtained for the first two enzymes of
isoflavonoid biosynthesis through in planta localization and feeding experiments (Liu and
Dixon, 2001).
The first experimental evidence for protein-protein interactions within the flavonoid
pathway came in cell fractionation experiments that demonstrated that the enzymes are located
on microsomal or endoplasmic reticulum (ER) membranes (Fritsch and Grisebach, 1975).
Sucrose density gradients of Hippeastrum petals demonstrated activity of PAL, C4H, CHS, and
UDP-glucose flavonoid glucosyltransferase in fractions corresponding to ER (Wagner and
Hrazdina, 1984). Fractionation experiments in buckwheat showed that CHS activity
corresponded with the rough ER (rER) and C4H, a P450 hydroxylase and purported membrane
anchor for the pathway (Hrazdina and Wagner, 1985). Through immunolocalization, Hrazdina’s
laboratory was able to show that CHS associated with the cytoplasmic face of the rER (Wagner
and Hrazdina, 1984). Building on these results, affinity chromatography, co-
immunoprecipitation, and yeast two-hybrid experiments provided the first direct evidence for
interactions within flavonoid metabolism (Burbulis and Winkel-Shirley, 1999). Further evidence
was obtained from immunolocalization assays in fixed cells (Saslowsky and Winkel-Shirley,
2001). These assays showed that CHS and CHI co- localize and were consistent with a
previously-proposed role for flavonoid 3’-hydroxylase (F3’H) as a membrane anchor for the
complex (Saslowsky and Winkel-Shirley, 2001; Stafford, 1990). It has also been demonstrated
that by expressing a phage-derived antibody to CHI in transgenic plants, the activity of CHI is
altered, as is the overall flavonoid composition of the plant (Santos et al., 2004). This antibody
could prevent CHI from assembling with other flavonoid enzymes. These recent findings have
11
changed the overall concept of the flavonoid metabolon from one of a linear arrangement of
enzymes (Hrazdina, 1992; Stafford, 1974a; Stafford, 1974b) to a multi-enzyme complex with
contacts between multiple proteins (Burbulis and Winkel-Shirley, 1999). The next challenge is
to determine the molecular basis of these interactions. A greater understanding of how enzyme
complexes form and how this assembly is regulated may facilitate the engineering of plants with
enhanced agronomic, nutritional or medicinal characteristics.
Arabidopsis Flavonoid Biosynthesis as a Model System for Studying Metabolic Pathways
Arabidopsis has been developed as a model system for the study of plant genetics,
biochemistry and molecular biology because of its ease of growth, short generation time, utility
as a genetic system, and the availability of an efficient and simple transformation system (Page
and Grossniklaus, 2002). In our laboratory, Arabidopsis is being used to provide a better insight
into the flavonoid biosynthetic machinery and enzyme complexes as a whole. The Arabidopsis
flavonoid biosynthetic pathway is very well characterized and mutations in flavonoid genes can
be easily identified based on the seed coat color (Shirley et al., 1995). The use of the tt mutants
has provided important new knowledge on the function of flavonoids for the plant. For example,
the tt4(2YY6) mutant (which carries a null allele for CHS) was used to show that, unlike the
situation in maize and petunia, flavonoids do not play a role in male fertility in Arabidopsis
(Burbulis et al., 1996b). Another interesting result is the determination that sinapate esters and
flavonoids play a critical function as sunscreens (Landry et al., 1995; Li et al., 1993). These
mutants have also played an important part in characterizing the organization of the pathway as a
12
multi-enzyme complex (Burbulis et al., 1996a; Burbulis and Winkel-Shirley, 1999; Saslowsky
and Winkel-Shirley, 2001).
Genes encoding eight flavonoid enzymes have been isolated in Arabidopsis. These
enzymes are CHS, CHI, F3H, flavonol synthase (FLS1-6), F3’H, DFR, ANS (also known as
leucoanthocyanidin dioxygenase (LDOX)), and ANR (also known as BANYULS (BAN))
(Burbulis et al., 1996a; Pelletier et al., 1999; Pelletier et al., 1997; Pelletier and Shirley, 1996;
Saslowsky and Winkel-Shirley, 2001; Shirley and Goodman, 1993; Xie de et al., 2004). All of
these enzymes are encoded by single copy genes with the exception of FLS, which is present in
six copies, at most three of which are thought to be catalytically active (Owens, Walton, and
Winkel, unpublished data). Five of these enzymes, CHS, CHI, F3H, FLS, ANS, and ANR, have
been overexpressed in E. coli and used to raise polyclonal antibodies (Cain et al., 1997; Pelletier
et al., 1997; Xie de et al., 2004).
Structural Biology of Flavonoid Metabolism
Understanding the structure and function of a protein on an atomic level can lead to a
better understanding the catalytic properties of a protein. Structures have been solved for three
flavonoid enzymes over the past several years, CHS2 and CHI from Medicago sativa, and ANS
from Arabidopsis (Ferrer et al., 1999; Jez et al., 2000b; Turnbull et al., 2001; Wilmouth et al.,
2002). As detailed below, the structures of these enzymes have allowed researchers to better
understand how these enzymes function catalytically and also investigate ways to alter their
substrate specificity and understand their evolution.
13
Chalcone Synthase: CHS catalyzes the first committed reaction in flavonoid biosynthesis in
which one molecule of 4-coumaroyl-CoA and 3 molecules of malonyl-CoA are used to create
naringenin chalcone, the starter molecule for the ensuing steps in flavonoid metabolism (Figure
1.2). CHS is a member of the plant type III polyketide synthase family, which encompasses all
CHS enzymes as well as a variety of ‘CHS-like’ enzymes that catalyze similar polyketide
reactions in plants (Austin and Noel, 2003). The structure (Figure 1.3) and the reaction
mechanism of CHS2 from Medicago sativa was solved in the laboratory of Joe Noel at the Salk
Institute (Ferrer et al., 1999; Jez et al., 2000a; Jez et al., 2001; Jez et al., 2000d; Jez and Noel,
2000). The CHS structure is made up of an aßaßa core motif that is conserved among all type
III polyketide synthases as well as enzymes containing a thiolase fold, such as ketoacyl thiolase
(Austin and Noel, 2003). CHS bears a striking resemblance, both in sequence and structure, to
thiolase enzymes such as ketoacyl synthases and thiolases, which provides evidence for the
hypothesis that CHS evolved from an enzyme of fatty acid biosynthesis as first suggested by
Verwoert, et al. (1992).
Catalytically-active CHS is a bi- lobed homodimer containing two distinct active sites.
The CHS homodimer is held together by identical six-residue loops in each opposing monomer
that contribute a methionine to the wall of the active site of the neighboring subunit. The CHS
active site cavity is buried within the structure of the
protein and is accessible only through a 16 ? long channel. However, the CHS crystal structure
has shown that this channel is actually too small for the product to leave CHS, suggesting that it
is a dynamic structure that can change dimensions to accommodate the entry or exit of different
substrates and products (Ferrer et al., 1999).
14
The CHS reaction starts by the loading of coumaroyl-CoA onto the active site cysteine
(Fig. 4), which is conserved among all thiolase-fold enzymes (Austin and Noel, 2003). This
allows the CoA moiety to be released through a decarboxylation reaction. Malonyl-CoA is then
freed of its CoA moiety by a second decarboxylation reaction and attached to the coumarate
bound in the active site. Two more malonyl-CoA units are added until a linear tetraketide chain
is created, which is circularized to form the chalcone product through an aromatase- like
mechanism that is not yet completely understood. The overall reaction is carried out by a
‘catalytic triad’ of conserved residues that play critical roles in the decarboxylation and
condensation reactions required for catalysis (Austin and Noel, 2003). The first of these
residues, the active site cysteine, was initially identified
by site directed mutagenesis studies performed in Gerhard Schröder’s group (Lanz et al., 1991).
This cysteine is conserved across all thiolase-fold enzymes and situated in a loop between two
buried amphipathic a-helices within the central core of the enzyme (Austin and Noel, 2003).
Chalcone Isomerase: CHI catalyzes the second step in flavonoid biosynthesis, closing the
center ring (Figure 1.5) and creating the basic flavonoid backbone. The CHI reaction can occur
spontaneously, however there is a 107 increase in reaction rate when the reaction is performed by
CHI (Bednar and Hadcock, 1988). There is also some evidence that CHI is post-translationally
modified, possibly through a thiol linkage, which could anchor CHI to the ER or aid in the
association of CHI with other enzymes in the complex (Burbulis and Winkel-Shirley, 1999).
The structure (Figure 1.6) and catalytic mechanism of CHI from Medicago sativa were
also solved in Joe Noel’s laboratory (Jez et al., 2000c; Jez et al., 2002). The structure resembles
an upside down flower bouquet with an open ß sandwich fold (Jez et al., 2000c). The overall
15
CHI fold is maintained in this enzyme across higher plant species. The fold is also predicted to
be present in some bacterial (gamma proteobacteria) and fungal proteins (Gensheimer and
Mushegian, 2004), dispelling the initial notion that this fold is unique to CHI. The functions of
these ‘CHI- like’ proteins are unknown, however.
The cyclization reaction catalyzed by CHI is facilitated by an initial binding of the
tetrahydroxychalcone through a hydrogen bond between the hydroxyl group at the 7 position of
the substrate to the hydroxyl on threonine 190, which has also been suggested to function in
determining substrate preference (Jez et al., 2002). A further hydrogen bonding network is
required in order to catalyze the reaction. One water molecule, in particular, is hydrogen bonded
to tyrosine 106, which is thought to activate the water molecule and is hydrogen bonded to the
substrate. Upon activation, the water molecule attacks the carbon-carbon double bond, thus
reducing it and allowing for the formation of a bond to close the center ring on the substrate (Jez
et al., 2002). CHI appears to have evolved to be stereospecific in the reaction it catalyzes.
Medicago CHI prefers the S-isomer of tetrahydroxychalcone over the R- isomer by an apparent
100,000:1 ratio (Bednar and Hadcock, 1988). In order for CHI to efficiently catalyze the
conversion of the R- isomer of tetrahydroxychalcone, there would have to be significant changes
in the active site structure in order to accommodate the additional stereochemistry (Jez et al.,
2000c). This stereospecificity raises the questions, does CHS always produce the S- isomer and,
if not, is there a use for the R- isomer in plant secondary metabolism? Unfortunately, the answers
are not yet known.
16
Methods to Determine Interactions Between Proteins
When investigating interactions between proteins, it is helpful to have multiple
techniques available. Many of the original studies that demonstrated protein-protein interactions
relied on techniques such as precipitation of protein aggregates, chromatography, and
ultracentrifugation (Ovádi and Srere, 2000). More recent techniques such as fluorescence
resonance energy transfer (Day et al., 2001), affinity gel electrophoresis (Beeckmans et al.,
1989), and yeast two-hybrid analysis (Ito et al., 2001) allow for the identification of two or more
interacting proteins. Techniques such as surface plasmon resonance refractometry (Rich and
Myszka, 2000), analytical ultracentrifugation (Lebowitz et al., 2002), and isothermal titration
calorimetry (Weber and Salemme, 2003) are capable of giving more detailed information such as
kinetic binding constants, reaction kinetics, and the thermodynamics of interactions. However,
these techniques cannot approach the atomic level of resolution that is needed for determining
the structure of a complex. The best ways to gain an appreciation of the structure of an enzyme-
complex on an atomic level are through co-crystallography of the proteins, small angle neutron
scattering (SANS) (Koch et al., 2003), and in silico protein-protein docking algorithms (Halperin
et al., 2002). For the purpose of this introduction, two of the above techniques, SANS and
surface plasmon resonance refractometry, will be discussed.
Small-Angle Neutron Scattering: SANS is a technique that uses neutrons to probe three-
dimensional structure of biological macromolecules in a non-destructive manner. Whereas X-
ray diffraction is typically used to study atomic- level structures (under 10 Å), SANS is generally
used to investigate larger structures (10 to 1000 Å) (Koch et al., 2003). Briefly, a sample is
17
exposed to a monochromatic, cold neutron beam generated by either a nuclear reactor or a
spallation source (details are shown in Fig. 7). The neutrons are scattered upon contact with the
sample due to interactions with the individual atoms. Neutron scattering intensities are recorded
by a two-dimensional detector, which can be moved in the both the y- and z- axis with respect to
the sample. Typically, neutrons are scattered through small angles (less than 1 degree) when
compared to traditional diffraction angles (more than 10 degrees). The scattering pattern is then
analyzed computationally to determine the overall size and shape of the molecules in solution.
The data obtained from these measurements do not provide a high resolution structure
like traditional crystallography, but rather a low resolution solution structure into which high
resolution crystal structures can be fit in order to develop models of macromolecular assemblies.
SANS can also be used to determine regions of proteins that are highly mobile in crystal
structures. SANS has been used in a number of biological applications, contributing to
determination of the structure of the 30S ribosomal subunit (Capel et al., 1987), elucidating
better ways to crystallize a protein by determining the amount of protein that is aggregated
(Velev et al., 1998), and characterizing the structure of the GroEL/ES chaperonin complex
(Krueger et al., 2003). Beyond biological applications, SANS has been used in the study of
polymers, complex fluids, materials science and condensed matter (Koch et al., 2003).
Surface Plasmon Resonance: Another powerful technique that can be used to determine
molecular interactions between proteins is SPR refractometry (or spectroscopy). This approach
uses monochromatic light to detect interactions between different molecules via a change in
refractive index that occurs during complex formation or dissociation (Rich and Myszka, 2000).
Briefly, protein is first immobilized onto a gold-coated glass slide that has been coupled with oil
18
to a sapphire crystal through which monochromatic light is passed (Fig. 8). The slide (or chip)
has a defined surface chemistry through a thiol linkage onto the gold. Two of the more common
surface chemistries currently being used are carboxy-methyl dextran self assembling monolayers
and metal affinity chemistries (Rich and Myszka, 2000). The former involves covalently linking
the protein (typically, any surface amine groups are utilized) to the surface chemistry whereas
the latter generally involves non-covalent coupling via a hexa-histadine tag. Once protein is
bound onto the slide, unbound protein is washed off, and solution containing a second protein is
passed over the slide. Interaction between the two is detected by a change in refractive angle
which is detected by a photo diode array and reported on the monitor.
SPR can be used not only to detect protein interactions, but also to measure kinetics,
affinity constants, the thermodynamics of an interaction, and, in some cases, to determine the
stoichiometry and mechanism of interaction (Morton and Myszka, 1998; Myszka et al., 1998).
Recent advances have also coupled SPR with mass spectrometry to identify interacting proteins
as well as determining interaction domains (Nedelkov and Nelson, 2003a). Various software
packages exist to aid in analyzing the results of SPR experiments, such as CLAMP99 (Myszka
and Morton, 1998), which allows for the determination of association and dissociation values for
an interaction.
One of many examples of current research using SPR is with the human
immunodeficiency virus (HIV). Areas of the HIV life cycle that have been intensely studied
with SPR are binding, mapping of epitopes for antibody development, and effects of inhibitory
drugs on viral machinery. This work has given a unique insight into how HIV functions
(reviewed in Rich and Myszka, 2003). These studies focused on antibody-antigen interactions
19
with the hopes of finding a magic bullet that will affect the ability of HIV to infect and replicate
in the human host.
An example of biosynthetic enzymes being studied by SPR is the cysteine synthase
complex. Previous evidence from yeast two-hybrid analysis indicated that serine
acetyltransferase (SAT) and O-acetylserine (thiol) lyase (OAS-TL) interact to form a complex
that is involved in cysteine biosynthesis (Bogdanova and Hell, 1997). These initial studies also
defined some of the interaction domains between SAT and OAS-TL by means of truncation
series. SPR was subsequently used to determine the binding kinetics of these two enzymes when
they are activated in the presence of sulfur (Berkowitz et al., 2002).
A recent innovation has been the addition of mass spectroscopy at the conclusion of the
SPR assay (Nedelkov and Nelson, 2001). The technique of SPR is carried out in the same
manner as in conventional applications, except that the immobilized protein has to be covalently
attached to the slide to inhibit leaching. Once the SPR experiment is complete, interacting
proteins are eluted, leaving the initial protein bound to the slide, and these proteins are subjected
to matrix-assisted laser desorption- ionization time-of-flight (MALDI-TOF) MS (Nedelkov and
Nelson, 2003b). This technique allows for the effective identification of previously-unknown
interacting proteins. An example of the application of SPR-MS is the identification of the
protein complex makeup of insulin- like growth factors (IGF-1 and -2) from human plasma
(Nedelkov et al., 2003). In separate experiments, antibodies against IGF-1 or -2 were used to
immobilize IGF-1 and -2 along with any other proteins interacting with them from human
plasma, which were later identified by MS. It was determined that both growth factors are
present in human plasma, suggesting that IGF-1, -2 and a previously unknown truncated form of
IGF-2 make up a protein complex in vivo (Nedelkov et al., 2003).
20
Project Goals/Rationale
There has been a variety of experimental evidence for interactions between enzymes
involved in flavonoid metabolism, both in vitro and in vivo. These data provide a broad
understanding of interactions within the metabolon, but no details regarding the molecular basis
of these interactions. It would seem that the next logical step would be to investigate this
problem on an atomic scale, i.e., determining how the enzymes physically interact with each
other and identifying the specific residues and atoms involved. Data from such experiments
would provide more information, not only on the organization of the flavonoid metabolon, but
also for metabolic organization in general. These insights could be used to create stronger (or
weaker) interactions to modulate pathway flux and engineer plants with higher levels of
flavonoids important for flower pigments, (e.g., create a blue rose), or as antioxidants.
This project was divided into two major objectives. First, the structural implications of
amino acid substitutions were investigated by molecular dynamics simulations. The second part
of this project studied the functional and structural components of flavonoid biosynthesis,
specifically the interactions between CHS, CHI, and F3H. X-ray crystallography and molecular
modeling were utilized to determine or deduce the structure of proteins involved in flavonoid
biosynthesis. Amino acid substitutions were introduced on the surface of CHS to test for effects
on the interaction of CHS with CHI in a yeast two-hybrid assay. SANS, which had not
previously been used for the study of metabolic complexes, was used to generate a structural
model of the interacting proteins. Next, computational docking studies were performed to
develop a model that fit the SANS data. The results from this project provide new insights into
21
the self assembly of enzymes involved in flavonoid biosynthesis, with implications for the
organization of enzyme complexes in general.
22
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36
COSCoA
OHOH
COOH
NH2
Fatty Acid Metabolism
phenylalanine 4-coumaroyl-CoA
General Phenylpropanoid Pathway
3
Malonyl Co-A
+
CHS
OH
O
OHOH
OH
tetrahydroxychalcone
OH
O
OOH
OH
naringenin
CHI
OH
O
OOH
OH
OH
F3’H
F3H F3H OH
O
OOH
OH
OH
OH
O
OOH
OH
OH
OH
eriodictyol
DFR
F3’H
OH
OH
OOH
OH
OH
OH
OH
O+OH
OH
OH
OH
ANS
Anthocyanins
3GT, 5GT
ANR (BAN)
Condensed Tannins (proanthocyanidins)
OH
OOH
OH
OH
OH
LAR
OH
OOH
OH
OH
R
O
FLS
FLS
Flavonol glycosides
dihydrokaempferol dihydroquercetin
leucopelargonidin
leucocyanidin
cyanidin
Figure 1.1: Schematic of the flavonoid pathway in Arabidopsis thaliana . The pathway creates a diverse set of compounds used in UV protection, signaling, defense, and pigmentation. CHS represents that first committed step in the pathway, where 4-coumaroyl-CoA (from phenylpropanoid biosynthesis) and 3 units of malonyl-CoA (from fatty acid metabolism) are used as substrates. Structures in the figure represent the three enzymes in the pathway that crystal structures have been solved for, CHS (pdb id:1BI5) and CHI (pdb id:1EYQ) (both from Medicago sativa), and anthocyanidin synthase (ANS) (pdb id:1GP6) (from Arabidopsis thaliana). Structures in orange are homology models of dihydroflavonol 4-reductase (DFR), flavanone 3-hydroxylase (F3H), flavonoid 3’ hydroxylase (F3’H), and flavonol synthase (FLS). Other enzyme names are abbreviated as follows: anthocyanidin reductase (ANR), cinnamate 4-hydroxylase (C4H), p-coumarate:CoA ligase (4CL), leucoanthocyanidin reductase (LAR), phenylalanine ammonia-lyase (PAL). Arrows labeled in grey indicate branches of the pathway not present in Arabidopsis.
HOOC
COSCoA
Isoflavonoids
CHS/CHR
PAL C4H 4CL
3GT, RT
37
Figure 1.2. Reaction catalyzed by CHS. CHS utilizes 4-coumaroyl-CoA and 3 units of malonyl-CoA in a Claisen condensation reaction to create tetrahydroxychalcone. The atoms on tetrahydroxychalcone which are labeled in black come from 4-coumaroyl-CoA and the atoms in red come from malonyl-CoA.
38
Figure 1.3. Structure of Medicago sativa CHS2 (Ferrer et al., 1999). The CHS protein is composed of two identical monomers (illustrated in purple and yellow). The red atoms indicate the methionine that is utilized as part of the active site wall by the partner monomer. The arrow indicates the substrate/product channel leading to the buried active site. The structure was generated using SwissPDB Viewer (Guex and Peitsch, 1997) and rendered using POV-Ray 3.1 (www.povray.org).
39
H303
C164
N336
F215
F265
Figure 1.4. Close up of CHS2 active site (Ferrer et al., 1999). F215 and F265 are the ‘gatekeeper’ residues that are proposed to control the entry of substrate. H303 and N336 are involved with the binding of substrate and removal of the CoA moieties while C164 holds the substrate during the reaction.
40
Figure 1.5. The reaction catalyzed by CHI. The C ring of tetrahydroxychalcone is closed in a cyclization reaction to create (2S)-naringenin, which serves as the basic backbone for the downstream flavonoid metabolic reactions.
41
Figure 1.6. The structure of CHI from Medicago sativa crystallized with its product (Jez et al., 2000c). The structure maintains an overall open ß-sandwich fold. The arrow indicates the location of the product, (2S)-Naringenin.
(2S)-Naringenin
42
Neutron Source (Reactor/ Spallation) with LH2 moderator
Velocity Selector
Lens/focusing system
sample
detector
beamstop
Figure 1.7. Schematic representation of SANS. Cold neutrons are emitted from the neutron reactor or spallation source and are then selected for the appropriate wavelength by the velocity selector. A series of lenses then focus the monochromatic neutron beam before passage through the sample. Upon hitting the sample, scattered neutrons are recorded by the 2-D detector and turned into electrical impulses, which are then transmitted to a data collection computer. Non-scattered neutrons are blocked by a beamstop made of neutron-dense material. (adapted from Koch et al., 2003).
43
?
Polarized Light Diode Array Detector
Coupling Prism
Solution of Protein
Flow Cell
Glass (0.2 mm) Ti (1.5 nm) Au (38 nm) m SAM (~ 3 nm)
Figure 1.8: Schematic representation of the principle of SPR. Polarized light at 760 nm is directed through the sapphire prism onto a glass slide with evaporated Ti and Au and a surface chemistry has been coupled. The change in observed resonance angle (?) is recorded by a photodetector when protein binds to the surface chemistry (adapted from Lahiri et al., 1999).
44
Chapter 2
Interpretation of functional effects of mutations in Arabidopsis chalcone synthase based on
molecular modeling
Christopher D. Dana1, David R. Bevan2 and Brenda S.J. Winkel1
1Department of Biology and Fralin Biotechnology Center and 2Department of Biochemistry,
Virginia Tech
Manuscript to be submitted to Journal of Molecular Modeling
Key Words: molecular dynamics, allelic series, chalcone synthase (CHS), transparent testa (tt)
45
Abstract
Chalcone synthase (CHS) catalyzes the first committed step in flavonoid biosynthesis, a
major pathway of plant secondary metabolism. An allelic series for the Arabidopsis CHS locus,
tt4, was previously characterized at the gene, protein, and end product levels (Saslowsky et al.,
2000). The substitutions identified in each of these alleles were used to generate models for five
of the tt4 proteins based on the Arabidopsis CHS crystal structure (Chapter 3) in order to
determine how mutations may affect protein structure and function. tt4(85) contains a
substitution that apparently disrupts catalytic activity due a change in the CoA binding face
geometry. The tt4(UV113) allele disrupts enzymatic activity while maintaining a stable protein,
which could be caused by a stiffening of the loop containing the critical active site residue, C169.
In contrast, the tt4(38G1R) mutation results in a truncated protein that is both catalytically
inactive, does not dimerize, and accumulates at reduced levels, presumably due to the loss of
three beta sheets. However, no structural basis could be discerned for the temperature-dependent
loss-of-function of the enzymes encoded by tt4(UV01) and tt4(UV25).
46
Introduction
The type III polyketide synthases (PKSs) comprise a structurally-related class of enzymes
that are key to the production of an array of biologically-active natural products in plants and
some bacteria (Austin and Noel, 2003; Moore et al., 2002). These enzymes, also known as
homodimeric iterative PKSs, include the extensively-studied chalcone synthase (CHS), an
enzyme that is ubiquitous among plants and that catalyzes the first committed step in the
synthesis of flavonoids. In the CHS reaction, one molecule of p-coumaroyl CoA and three
molecules of malonyl CoA are used to generate a tetraketide that is then cyclized into 4,2’,4’,6’-
tetrahydroxychalcone. This molecule serves as a backbone for the production of a wide array of
flavonoid compounds that function in such diverse roles as flower pigmentation, UV protection,
signaling, male fertility, and defense against microbial pathogens (Winkel-Shirley, 2001).
Alfalfa CHS was the first type III PKS, and the first flavonoid enzyme, for which a
crystal structure was solved (Ferrer et al., 1999). Together with the subsequent determination of
structures for mutagenized forms of this enzyme and for 2-pyrone synthase (PS) from daisy (Jez
et al., 2002; Jez et al., 2000b), significant insights have been gained into the molecular basis of
the reaction series catalyzed by the type III PKSs. For example, it was known that, although
each of the two active sites in CHS and the closely related enzyme, stilbene synthase (STS),
function independently, dimerization is required for activity (Tropf et al., 1995). It is now clear
that this is because a methionine in each monomer helps shape the active site cavity of the
adjoining monomer. In addition, it has been shown that each active site is buried within the
enzyme and that substrates enter via a long (16 Å in alfalfa CHS) CoA binding tunnel [Ferrer,
1999 #79]. The three key catalytic residues are located within an initiation/elongation cavity,
one lobe of which forms a coumaroyl binding pocket, while the other accommodates and
47
determines the length of the growing polyketide chain. Although CHS and PS use different
substrates, produce different products, and exhibit 74% amino acid sequence identity, the overall
architecture of the two enzymes is nearly identical. Remarkably, it has been possible to engineer
CHS for PS activity by altering just three residues that affect the overall dimensions of the
initiation/elongation cavity (Jez et al., 2002).
Several recent studies have utilized molecular dynamics simulations in efforts to
elucidate the functional properties of a protein containing amino acid substitutions. For example,
Ceruso et al. (2004) were able to suggest a nucleotide exchange mechanism in the Ga subunit of
transducin by modeling a series of substitutions in residues that had been previously
characterized biochemically. Another study, on the molecular switch present in the
glucocorticoid receptor, used molecular dynamics simulations to show that distinct substitutions
that result in a gain-of- function are caused by two different structural mechanisms (Stockner et
al., 2003).
We previously characterized an allelic series of mutations for Arabidopsis CHS, which is
defined by the TT4 locus (Saslowsky et al., 2000). The seven tt4 alleles included in this analysis
were found to have diverse effects on the accumulation of CHS mRNA, the dimerization and
stability of the enzyme, and the accumulation of flavonoid end products. Two of the alleles also
exhibited temperature sensitivity. A homology model was initially generated for the wild-type
Arabidopsis enzyme based on the Medicago CHS2 crystal structure, and the locations of the five
tt4 mutations resulting in single amino acid changes or a small deletion were mapped on this
model (Ferrer et al., 1999). This preliminary analysis suggested that several of the mutations
could have significant effects on the structure of the CHS enzyme. To further explore this
possibility, individual homology models have been generated for these five altered proteins
48
based on the recently-solved crystal structure for Arabidopsis CHS (Chapter 3). These models
provide insights into the phenotypic and biochemical consequences that arise from either point
substitutions or truncation in the enzyme in three of these alleles.
Methods
A multiple sequence alignment of 15 representative members of the plant type III PKS
superfamily was generated using Clustal W (Thompson et al., 1994) using the Megalign program
in DNAStar (Madison, WI). Included in this analysis were CHS from Arabidopsis (accession
number P13114), alfalfa (P30074), maize (SYZMCC), parsley (S42523), raspberry
(AAK15174), snapdragon (P06515), and tea (P48387); acridone synthase 2 from rue (Q9FSC0);
bibenzyl synthase from orchid (S71619); coumaroyl triacetic acid synthase from hydrangea
(BAA32733); dihydropinosylvin-forming stilbene synthase from pine (Q02323); PS from daisy
(P48391); trihydroxystilbene synthase sequences from grape (P51070) and peanut (S00334); and
valerophenone synthase (O80400) from hops.
Homology models were generated for five of the Arabidopsis tt4 alleles [tt4(85),
tt4(UV113), tt4(38G1R), tt4(UV01), and tt4(UV25)] based on the crystal structure for
Arabidopsis CHS (Chapter 3). The deduced sequences of the mutant proteins (Saslowsky et al.,
2000; Shirley et al., 1995) were first aligned independently with alfalfa CHS2 using Biology
Workbench (http://workbench.sdsc.edu). Five models were produced for each allele using
Modeller6 of Sali and Blundell (1993) and an average model was generated for each protein by
coordinate averaging. The averaged structures were minimized using the Sander module of
Amber7 for 200 steps using steepest descent (Pearlman et al., 1995). Models were then solvated
with water, and sodium ions were added to give the system a net charge of zero. Minimization
49
of the solvent and counterions was performed for 200 steps as described above, followed by a
minimization of the entire system. Molecular dynamics was then performed using the Sander
module of Amber7 for a total of 500 ps with a time step of 2.0 fs and a structure collected at
every 1 ps. All simulations were performed using 4-8 processors on Virginia Tech’s Laboratory
for Advanced Scientific Computing and Applications Linux cluster. The dynamics simulation
was divided into the following components: the first 80 ps was a heating phase to raise the
system temperature from 0 K to either 285 K, 293 K, or 300 K, the next 120 ps was a constant
volume equilibration phase, and the final 300 ps was a constant pressure phase. Final models
were generated by coordinate averaging of the last 100 ps of the dynamics simulation. The
solvent and sodium ions were manually stripped from the average structures and the systems
were minimized again as described above. Assessments of the models were performed using
Procheck on the Whatif server (http://swift.embl-heidelberg.de/servers/). Root mean squared
deviation (RMSD) calculations for the last 100 ps of the dynamics simulations were performed
using the Carnal module of Amber7 (a representative RMSD graph is shown in Figure 2.1).
Distances between alpha carbons, phi-psi torsion angles for residues, and hydrogen bond
networks were determined using the Carnal module of Amber7 using the last 100 ps of the
dynamics simulations. To determine the structural differences between the TT4 proteins and the
wild-type structure, the structures were individually aligned by the least squares fit function
within Swiss-Pdb Viewer, version 3.7 (Guex and Peitsch, 1997) and RMSD was calculated using
the same program. All images of protein structures were generated using Swiss-Pdb Viewer
(Guex and Peitsch, 1997) and rendered using POV-Ray version 3.1a (www.povray.org).
50
Results
Seven alleles of the Arabidopsis CHS gene, induced by either EMS or gamma radiation,
were previously characterized at the gene, protein, and end product levels (Table 2.1) (Burbulis
et al., 1996; Saslowsky et al., 2000; Shirley et al., 1995). One of these alleles [tt4(UV118a)]
contains a complex rearrangement, while the other six contain point mutations that either disrupt
splicing to generate a severely- truncated coding region [tt4(2YY6)], introduce a stop codon to
truncate the coding region by 15 codons [tt4(38G1R)], or alter a single amino acid in the gene
product [tt4(85), tt4(UV01), tt4(UV25), and tt4(UV113)]. Most of the mutations completely
abolish the accumulation of flavonoids in affected plants, although one appears to be leaky and
two others display a temperature-sensitive phenotype (unpublished observations and Saslowsky
et al., 2000) (Table 2.1).
To further investigate the effects of small changes in CHS protein sequence on the
properties of the enzyme, the proteins containing single amino acid changes or the C-terminal
truncation were first examined in the context of current information on structure-function
relationships in CHS. A multiple sequence alignment generated using 14 representative
members of the plant type III PKS superfamily, including Arabidopsis CHS, illustrates that each
of the tt4 mutations affect residues that are very highly, if not absolutely, conserved in these
enzymes (Figure 2.2) and that most are also located in highly-conserved stretches of sequence.
Although all five mutations significantly affect flavonoid accumulation, none affect residues
with known functional importance. Mapping of the affected residues on a homology model of
the Arabidopsis wild-type enzyme previously showed that many are located in or near important
functional domains, including the dimerization interface and the catalytic center, suggesting that
51
these mutations may have other, indirect effects on various aspects of enzyme function
(Saslowsky et al., 2000) (Figure 2.3). To examine the structural effects of these mutations in
further detail, the crystal structure for the wild-type Arabidopsis enzyme (Chapter 3) was first
subjected to energy minimizations in the presence of solvent and counterions, followed by
molecular dynamics simulations, as described in the Methods. Models were then developed and
similarly refined for the products of the five mutant alleles, tt4(85), tt4(UV01), tt4(UV25),
tt4(UV113), and tt4(38G1R). The effects of the altered residues and the C-terminal truncation
on the overall structure of the enzyme and on the dimensions and architecture of both the active
site and CoA binding site were examined by calculating the RMSD values, measuring the
distances between alpha carbons, and the phi and psi angles.
tt4(85)
The tt4(85) allele was the first Arabidopsis CHS mutation to be reported (Koornneef,
1990). Although plants carrying this allele accumulate wild-type levels of CHS protein that
appears to dimerize normally, flavonoid levels in these plants are reduced to almost undetectable
levels (data not shown, Saslowsky et al., 2000). The tt4(85) allele carries a point mutation that
results in replacement of a glycine at position 268 with serine (G268S) (Shirley et al., 1995).
This glycine residue appears to be absolutely conserved in all type III PKSs and is located in a
beta sheet (β11) in linear and spatial proximity to amino acids involved in CoA binding (L273
and K275) as well as to determinants of substrate specificity (I260 and F271) and product length
(G262) (Jez et al., 2000a) (Figures 2.2 and 2.4), and near an arginine (R265) that has been shown
to be essential for activity of raspberry CHS1 (Zheng et al., 2001). A way of measuring the
difference between two proteins is to fit one onto another structure and calculate the RMSD
52
between the two. The RMSD for the tt4(85) when compared to the wild-type structure is 2.48 Å,
also indicative of significant structural differences between the two proteins. To investigate the
effect of the G268S substitution on the geometry of the active site, the distances between the
alpha carbons of the four key active site residues were measured (Table 2.2). The results
indicate that the active site histidine (H309) appears closer to the critical active site cysteine
(C169), but is further from the active site asparagine (N342) and phenylalanine (F220) in tt4(85)
(Table 2.2). In the wild-type enzyme, C169 functions as a nucleophile, removing the CoA
moiety from either coumaroyl-CoA or malonyl-CoA and binding the reaction intermediates
during polyketide formation (Ferrer et al., 1999). Both the phi and psi angles for this residue
appear to be distorted in tt4(85), indicating that the side chain may be in an unfavorable
orientation for catalysis. The phi angle for F271, which is one of two ‘gatekeeper’ residues just
outside the active site, is also much larger than wild-type (Table 2.3), which could affect entry of
substrate into the active site. Moreover, almost all of the residues involved in CoA and substrate
binding appear to be further apart than in the wild-type protein (Table 2.4). The increase in these
distances, some being almost 2 Å larger than that of wild-type, indicates that this protein might
be incapable of binding or correctly positioning the CoA moiety within the active site. The
homology model of the tt4(85) protein also indicates that helix a3, which contains three of the
CoA binding residues is distorted relative to the wild-type, with a kink in the middle of this helix
(Figure 2.4). Although, the tt4(85) protein does retain some activity, as indicated by the leaky
phenotype of mutant plants, it provides a good example of how a single amino acid change can
have substantial structural and mechanistic effects on enzyme function.
53
tt4(UV113)
The tt4(UV113) mutation results in the substitution of proline for threonine at position
174 (T174P). This highly-conserved amino acid is located in helix α7 (Figure 2.2; Figure 2.4C)
and is five residues C-terminal to the active site cysteine. As in the case of tt4(85), plants
carrying this mutation produce wild-type levels of CHS protein that appears to dimerize
normally (Saslowsky et al., 2000). However, no detectable flavonoids are produced. T174
appears to be absolutely conserved in CHS enzymes and most other type III PKSs, with the
exception of valerophenone synthase from Hops, where there is a lysine at this position (Figure
2.2). Homology modeling indicates that, although the tt4(UV113) protein maintains its overall
tertiary structure, the spatial relationship of the active site cysteine (C169) to the other active site
residues is altered (Table 2.2). There are also changes in the phi angle for the C169 backbone
relative to the wild-type protein (Table 2.3), which could indicate that the side chain is being
forced into an orientation that is inaccessible to the substrate. Measurement of the distances
between the alpha carbons of the CoA binding residues indicates that, for the most part, the
geometry of these residues is unchanged. However, insertion of a proline residue into the a7
helix is likely to reduce the flexibility of this region, which is indicated by an decrease in the
RMSD for the a7 helix (1.09 ± 0.071 Å for tt4(UV113) and 1.49 ± 0.091 Å for wild-type).
When the same measurement is performed for residues 166-172, the loop containing the active
site cysteine, the RMSD is 0.614 ± 0.106 Å for UV113 and 0.882 ± 0.093 Å for wild-type. Thus,
although the T174P substitution appears to have little effect on the overall structure of the active
site pocket, it could affect the dynamic movement of the active site cysteine during catalysis.
The tt4(UV113) substitution has an even more dramatic effect on enzyme function than the one
in tt4(85), presumably due to a loss in flexibility of the loop containing the active site cysteine.
54
tt4(38G1R)
The point mutation in tt4(38G1R) shifts the reading frame starting at codon 381,
introducing 3 altered residues and a premature stop codon so that 15 residues are lost from the C
terminus. The protein accumulates at much lower levels than the wild-type CHS, is catalytically
inactive, and does not form dimers (Table 2.1) (Saslowsky et al., 2000). The first two residues
altered by this mutation are part of the conserved GFGPG loop that provides a scaffold for the
cyclization reaction in type III PKSs (Austin and Noel, 2003; Suh et al., 2000), and are located
on the opposite side of the protein from the dimerization interface (Figure 2.4D).
The model for tt4(38G1R) bears the most striking changes in overall tertiary structure of
all the altered proteins (Figure 2.4). Due to the truncation, beta sheet 15, which appears to be
required for the formation and stabilization of a series of three beta sheets, is lost. The RMSD
between this structure and that of the wild-type enzyme is 2.92 Å, indicating significant
differences in the secondary and tertiary structures of the two proteins. The homology model
also indicates that the residues comprising beta sheets 14 and 7 in the wild-type no longer retain
any beta sheet structure in tt4(38G1R). Interestingly, the loss of this series of beta sheets also
affects one of the active site residues, H309, which functions with N342 as an electron sink to
stabilize the transition state dur ing the transfer of substrate intermediates to C169 (Austin and
Noel, 2003). This residue is located at one end of beta sheet 14 in the wild-type protein and is
moved in tt4(38G1R) (Table 2.2). Moreover, the phi angles for both the gatekeeper amino acids,
F220 and F271, and the psi angles for F271 are significantly different than in the wild-type
protein (Table 2.3), which suggests that these residues could be obstructing the active site
entrance. Also, the CoA binding residues are substantially further apart than in the wild-type
protein (Table 2.4), indicating that these residues may not be able to bind substrate. However,
55
from the analyses performed in this study, no reason for the loss of dimerization was determined.
These results suggest the apparent lack of catalytic activity may result from the loss of three beta
sheets required for protein stability and catalytic function.
tt4(UV01)
tt4(UV01) is a temperature-sensitive allele that results in the replacement of a threonine
with an isoleucine at position 49 (T49I). As is the case for G268 in the tt4(85) allele, this residue
appears to be invariant in all type III PKSs (Figure 2.2). Position 49 is near the CoA binding
residues in both the primary sequence and the tertiary structure (Figure 2.3). This amino acid
change does not appear to affect the ability of the enzyme to dimerize, consistent with the fact
that it is located on the opposite side of the enzyme from the dimerization interface, but does
appear to decrease protein stability at all temperatures (Saslowsky et al., 2000) (Table 2.1).
These plants exhibit a temperature-dependent reduction in the accumulation of flavonoid end
products, with almost no flavonoids present at 27°C, very low levels at 20°C (the optimum
growth temperature for Arabidopsis), and moderate levels at 12°C (Saslowsky et al., 2000).
After subjecting the tt4(UV01) homology model to molecular dynamics simulations at 27°, 20°,
and 12°C, and superimposing the resulting structures on that of the wild-type protein, no
substantial changes in overall secondary or tertiary structure were apparent. The phi and psi
angles do not deviate substantially from the wild-type for the majority of the residues with the
exception of F271 (Table 2.3), which is involved in substrate specificity. Interestingly, the phi
angle for F271 is significantly different from wild-type at all three temperatures investigated.
The dimensions of the CoA binding tunnel did vary with temperature, however the greatest
changes occurred at lower temperatures, where the enzyme exhibits some catalytic activity
56
(Table 2.4). Overall, the homology model did not provide any clues regarding the temperature-
sensitive phenotype of the tt4(UV01) enzyme.
tt4(UV25)
The tt4(UV25) allele is characterized by the replacement of arginine at position 334 with
a cysteine (R334C) (Saslowsky et al., 2000). This mutation is located eight residues N-terminal
to the active site asparagine (N342) and is highly conserved among type III PKSs. The known
exceptions are two confirmed and two suspected isoforms of acridone synthase from rue
(Junghanns et al., 1995) (accession numbers S60241, Q9FSC0, Q9FSC1, and Q9FSC2,
respectively), which have conservative substitutions of lysine at this position (Figure 2.2).
Similar to tt4(UV01), the tt4(UV25) enzyme is present at reduced levels in mutant plants relative
to wild-type and exhibits a temperature-dependent reduction in flavonoid accumulation,
however, it also appears to have lost the ability to form homodimers (Table 2.1). Molecular
dynamics simulations were performed at 12º, 20º, and 27º C. Analysis of the dihedral angles of
the active site residues as well as the distances between the active site residues, CoA binding
residues, and substrate specificity residues, provided no obvious explanation for the phenotypes
of the tt4(UV25) enzyme. However, the RMSD values are indicative of a structure that is not
very stable at 12º C. Also, the RMSD between the wild-type and the UV25 structures at 12º C is
2.50 Å, indicating that the two structures are different from each other. Both of these results are
opposite to what was expected, as the protein should be more stable at lower temperatures.
Interestingly, this substitution occurs in the region of the protein that is proposed to be important
for interaction with CHI (Figure 2.3) (Chapter 3). Perhaps the alteration of this residue affects
this predicted interaction domain in a temperature-dependent manner, thus impacting not only
57
CHS protein accumulation, but its ability to function as part of a proposed flavonoid enzyme
complex.
Discussion
This study indicates that homology modeling can be a useful tool for the analysis of
structure-function relationships in enzymes such as CHS. An allelic series of mutations in the
CHS gene had previously been characterized on the molecular and genetic level. For most of the
alleles, molecular dynamics simulations of homology models were able to suggest a structural
basis for the loss of function, usually due to distortion of the active site pocket, an overall change
in the dimensions of the CoA binding tunnel dimensions, the loss of flexibility in loop, or a loss
of substantial tertiary structure. The molecular dynamics simulations indicated that the
substitutions caused changes in the structures of tt4(85), tt4(UV113), and tt4(38G1R) that may
explain the changes in function and accumulation. However, in the case of the temperature-
sensitive alleles, the molecular dynamics were unable to provide an explanation for the
temperature-dependent loss of function and stability. Also, for the tt4(38G1R) and tt4(UV01)
alleles, this study was unable to provide any predictions for the loss of dimerization of the
protein. It is important to note that the dynamics performed in this study were done on the
monomeric form of CHS, thus simulations on the dimeric form of the protein could provide
additional useful information. Future studies could also include in silico docking of substrate
into the CHS active site to determine if the proteins are able to bind the CoA moiety, which is
required for proper positioning of the substrate.
58
Modeling and molecular dynamics simulations can also be applied to other systems
where biochemical data exist for amino acid substitutions in order to gain information about
effects on secondary and tertiary structure. These methods could be used as an inexpensive
approach to rationally engineering a gain or loss of function within proteins. It might also be
possible to engineer novel catalytic activities by first modeling amino acid substitutions and then,
using quantum mechanical calculations, simulate the reaction that would be performed.
Moreover, the techniques described in this study could be used to elucidate the architecture of
multi-enzyme complexes. First, through in silico docking techniques and molecular dynamics
simulations, the identity and location of residues that contribute to protein-protein interactions
could be identified and then verified by experimental techniques such as yeast two-hybrid and
surface plasmon resonance refractometry. Once the interaction has been identified, it might then
be possible to engineer stronger or weaker interactions through amino acid substitutions in order
to modify metabolic flux creating new activities or causing the accumulation of specific end
products.
59
Acknowledgments
The authors would like to thank Jory Zmuda Ruscio for her assistance with the molecular
dynamics simulations. This work was supported by the National Science Foundation (grants
MCB-9808117 and MCB-0131010) and by grants from the Virginia Tech Graduate Research
Development Project to C.D.D.
60
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Jez, J. M., Ferrer, J. L., Bowman, M. E., Dixon, R. A., and Noel, J. P. (2000b). Dissection of
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63
Table 2.1 Biochemical and genetic characteristics of Arabidopsis CHS alleles.
Allele Mutationa CHS protein levelsb
Allele type Flavonoid glycoside levelsc
Homodimer crosslinkingd
wild-type N.A.e ++++ Wild-type +++ +++
tt4(85)e G268S ++++ Leaky + +++ tt4(UV113) T174P ++++ Null - +++ tt4(38G1R) P381S,
G382H, L383C, T384stop
+ Null - +
tt4(UV01) T49I ++ Temperature-sensitive
+ +++
tt4(UV25) R334C ++ Temperature- sensitive
+ +
a Amino acid(s) altered in the predicted protein. b Determined by immunoblot analysis (Saslowsky et al., 2000). c Determined by HPLC ana lysis (data not shown, Saslowsky et al., 2000). d Determined using disuccinimidyl glutarate and N-succinimidyl-[4-vinylsulfonyl] benzoate
(Saslowsky et al., 2000). e N.D., not determined.
64
Table 2.2. Dimensionsa of the CHS proteins
27°C 20ºC 12ºC
ArabidopsisCHS
tt4 (85)
tt4 (UV113)
tt4 (38G1R)
tt4 (UV01)
tt4 (UV25)
Arabidopsis CHS
tt4 (UV01)
tt4 (UV25)
Arabidopsis CHS
tt4 (UV01)
tt4 (UV25)
RMSDb
vs. wt N/A 2.48 1.79 2.92 1.74 1.54 N/A 1.17 1.50 N/A 1.23 2.50
RMSDc
over 100 ps 1.81
(0.06) 2.07
(0.06) 1.87
(0.06) 1.77 (0.1)
1.88 (0.08)
2.16 (0.19)
1.59 (0.07)
1.69 (0.1)
1.67 (0.06)
1.76 (0.07)
1.61 (0.06)
2.08 (0.10)
F220 to N342
4.75 (0.22)
4.78 (0.19)
4.74 (0.18)
4.63 (0.17)
4.80 (0.18)
4.84 (0.22)
4.72 (0.19)
4.65 (0.20)
4.88 (0.19)
4.61 (0.17)
4.61 (0.17)
4.58 (0.17)
C169 to H309
7.74 (0.38)
6.76* (0.22)
7.17 (0.29)
8.22 (0.30)
7.50 (0.29)
7.66 (0.31)
7.64 (0.31)
7.92 (0.26)
8.37 (0.97)
7.44 (0.34)
7.82 (0.26)
7.16 (0.31)
C169 to F220
10.78 (0.42)
11.86* (0.33)
10.49 (0.31)
9.71* (0.34)
10.72 (0.26)
10.83 (0.33)
11.34 (0.32)
10.99 (0.39)
10.42 (0.57)
10.60 (0.33)
11.26 (0.31)
10.42 (0.32)
H309 to N342
8.18 (0.22)
9.14* (0.30)
8.48 (0.24)
7.96 (0.27)
8.52 (0.22)
8.37 (0.22)
7.90 (0.23)
8.28 (0.25)
8.16 (0.25)
8.13 (0.25)
8.01 (0.27)
8.49 (0.25)
C169 to N342
9.19 (0.32)
9.34 (0.27)
8.61* (0.29)
9.22 (0.36)
8.85 (0.22)
9.25 (0.26)
9.90 (0.28)
9.36* (0.31)
9.27 (0.31)
9.24 (0.28)
9.91 (0.27)
8.87 (0.29)
F220 to H309
12.21 (0.33)
13.44* (0.33)
12.64 (0.26)
11.43* (0.28)
12.69 (0.25)
12.41 (0.31)
11.84 (0.32)
12.30 (0.31)
12.16 (0.43)
11.94 (0.32)
11.19 (0.27)
12.27 (0.25)
aValues are in angstroms and represent the average of distances between alpha carbons of the indicated residues in the final 100 structures generated by dynamic simulation. Numbers in parentheses are standard deviations. bRMSD values, which indicate overall similarity of structures relative to Arabidopsis wild-type CHS, were calculated using Swiss-PdbViewer v3.7. cRMSD values, which indicate the overall stability of the Ca backbone, was calculated using Amber7 (Pearlman et al., 1995). An asterisk (*) indicates a 1 Å or greater deviation from the wild-type.
65
Table 2.3. Phi-psi torsion angles within the CHS active sitea.
27°C 20ºC 12ºC
Wild-type
tt4 (85)
tt4 (UV113)
tt4 (38G1R)
tt4 (UV01)
tt4 (UV25)
Wild-type
tt4 (UV01)
tt4 (UV25)
Wild-type
tt4 (UV01)
tt4 (UV25)
C169 φ -58.63 (10.61)
41.46* (10.3)
-44.50 (12.1)
-62.49 (10.0)
-49.95 (10.3)
-58.62 (10.2)
-54.47 (8.23)
-60.72 (9.2)
-57.40 (10.46)
-56.92 (7.9)
-54.29 (10.0)
-48.26 (12.1)
C169 ψ -19.71 (14.3)
-100.98* (11.8)
-37.84 (12.0)
-7.04 (10.5)
-29.12 (10.3)
-13.00 (8.5)
-28.12 (10.3)
-14.01 (9.6)
-17.93 (10.3)
-25.69 (9.1)
-23.81 (10.0)
-35.71 (11.17)
F220 φ -65.59 (11.0)
-56.17 (8.9)
-67.35 (9.0)
-76.58* (9.6)
-68.8 (8.4)
-61.47 (10.7)
-72.94 (11.6)
-87.83 (13.7)
-63.77 (9.1)
-75.98 (9.8)
-83.21 (10.1)
-80.89 (9.7)
F220 ψ 142.6 (10.2)
133.1 (8.7)
137.1 (7.4)
150.2 (8.1)
136.4 (9.6)
143.5 (10.3)
147.5 (8.1)
153.3 (7.2)
140.7 (8.7)
156.59 (7.0)
152.9 (6.4)
152.17 (7.0)
H309 φ -68.6 (10.3)
-66.6 (9.5)
-72.5 (11.0)
-68.5 (11.1)
-74.0 (11.6)
-73.42 (12.4)
-72.5 (11.0)
-71.7 (13.2)
-71.3 (10.0)
-74.0 (12.0)
-66.7 (10.7)
-66.0 (11.6)
H309 ψ 120.0 (7.5)
108.4 (8.6)
118.5 (7.2)
115.1 (6.7)
118.6 (7.0)
115.2 (7.1)
113.2 (6.8)
113.7 (5.9)
115.1 (7.1)
114.8 (6.5)
115.4 (6.4)
115.5 (5.8)
N342 φ -87.02 (11.7)
-73.5 (8.5)
-89.6 (18.9)
-83.1 (10.9)
-128.7* (23.7)
-81.4 (10.4)
-79.8 (10.2)
-79.9 (12.2)
-81.6 (12.6)
-81.42 (10.0)
-78.3 (11.4)
-79.8 (10.6)
N342 ψ 96.0
(10.7) 97.6
(10.4) 93.8
(14.0) 99.7 (8.0)
135.21* (12.0)
96.5 (9.7)
104.1 (12.2)
112.4 (12.9)
94.9 (10.1)
96.5 (10.7)
112.6* (16.3)
103.3 (10.2)
F271 φ -78.5 (15.3)
-148.0* (9.0)
-126.0* (34.6)
-56.5* (8.7)
-146.1* (10.2)
-155.5* (8.9)
-149.9 (34.2)
-77.3* (19.4)
-88.3* (18.4)
-89.6 (22.2)
-150.8* (8.4)
-146.7* (8.4)
F271 ψ 120.7 (8.7)
138.7* (11.4)
144.3* (8.0)
134.2* (9.8)
136.5* (13.2)
143.0* (11.3)
129.2 (9.2)
149.5* (7.9)
121.2 (12.2)
127.7 (36.7)
133.9* (103.5)
125.5 (9.1)
aValues are in degrees. The phi angle (φ) indicates rotation around the N-Cα bond, while the psi angle (ψ), indicates rotation around the Cα -C bond. Positive and negative values indicate right-handed and left-handed rotation, respectively. Standard deviations are given in parentheses. An asterisk (*) indicates rotation 15º greater than wild-type.
66
Table 2.4. Distances between CoA binding residues.
27°C 20ºC 12ºC
Arabidopsis CHS
tt4 (85)
tt4 (UV113)
tt4 (38G1R)
tt4 (UV01)
tt4 (UV25)
Arabidopsis CHS
tt4 (UV01)
tt4 (UV25)
Arabidopsis CHS
tt4 (UV01)
tt4 (UV25)
K67 to K275
17.7 (0.5)
19.2* (0.8)
16.6* (0.4)
18.8 (0.7)
18.3 (0.5)
17.1 (0.7)
17.6 (0.6)
17.8 (0.6)
17.4 (0.5)
16.8 (0.6)
17.1 (0.5)
17.0 (0.4)
K67 to L273
15.7 (0.4)
16.4 (0.8)
14.8* (0.4)
16.9* (0.8)
16.0 (0.5)
15.1 (0.6)
15.3 (0.6)
15.8 (0.6)
15.4 (0.5)
15.3 (0.8)
13.8* (0.5)
15.3 (0.4)
K60 to K275
18.0 (0.4)
20.8* (0.6)
17.4 (0.6)
19.9* (0.5)
18.9* (0.5)
17.8 (0.7)
18.8 (0.5)
19.9 (0.6)
18.0 (0.4)
17.8 (0.5)
18.7 (0.5)
18.0 (0.5)
K60 to L273
15.8 (0.3)
17.9* (0.4)
15.5 (0.4)
17.2* (0.5)
15.8 (0.5)
15.3 (0.5)
15.8 (0.4)
16.9* (0.7)
16.1 (0.4)
15.8 (0.5)
15.0 (0.5)
15.7 (0.4)
R63 to K275
18.8 (0.4)
21.0* (0.6)
18.2 (0.5)
20.6* (0.5)
19.5 (0.6)
18.4 (0.7)
19.1 (0.5)
17.8* (0.6)
19.0 (0.4)
18.2 (0.7)
18.9 (0.5)
18.5 (0.4)
R63 to L273
16.7 (0.4)
18.0* (0.5)
16.3 (0.3)
18.2* (0.7)
16.7 (0.6)
16.0 (0.6)
16.3 (0.4)
15.8* (0.6)
16.9 (0.3)
16.4 (0.8)
15.3* (0.5)
16.4 (0.4)
K67 to A314
8.9 (0.3)
11.0* (0.6)
9.2 (0.4)
9.4 (0.5)
9.6 (0.3)
9.4 (0.5)
9.2 (0.4)
9.6 (0.4)
9.7 (0.4)
9.0 (0.4)
9.5 (0.4)
9.0 (0.3)
F220 to F271
10.5 (0.3)
10.6 (0.3)
10.6 (0.4)
10.1 (0.3)
10.5 (0.4)
10.3 (0.3)
10.7 (0.3)
9.6 (0.3)
9.1 (0.4)
10.9 (0.5)
10.6 (0.3)
11.1 (0.3)
K60 to I260
20.6 (0.4)
22.4* (0.5)
20.9 (0.4)
21.9* (0.4)
20.5 (0.4)
20.4 (0.6)
20.1 (0.4)
20.9 (0.7)
20.8 (0.4)
20.9 (0.7)
20.4 (0.5)
20.2 (0.5)
K60 to G262
22.8 (0.4)
22.8 (0.4)
22.2 (0.4)
23.3 (0.5)
21.8 (0.4)
21.9 (0.5)
22.4 (0.4)
22.6 (0.7)
23.1 (0.5)
22.0 (0.4)
22.8 (0.4)
22.2 (0.5)
R63 to I260
21.3 (0.5)
22.4* (0.5)
21.3 (0.3)
22.3* (0.5)
20.8 (0.5)
20.7 (0.7)
20.3 (0.4)
20.6 (0.7)
21.4 (0.4)
21.7 (0.9)
20.4* (0.5)
20.6 (0.4)
R63 to G262
23.9 (0.4)
23.8 (0.4)
23.4 (0.4)
24.5* (0.5)
23.2 (0.5)
23.0 (0.5)
23.5 (0.4)
22.9 (0.7)
24.1 (0.4)
22.9 (0.5)
23.3 (0.5)
23.8 (0.4)
K67 to I260
19.7 (0.6)
20.3 (0.6)
18.9 (0.4)
20.2 (0.7)
19.1 (0.5)
18.8 (0.9)
18.6 (0.6)
18.3 (0.6)
19.2 (0.6)
20.3 (0.9)
18.1* (0.5)
18.8* (0.4)
K67 to G262
22.9 (0.4)
22.7 (0.6)
22.2 (0.6)
23.5 (0.7)
22.9 (0.6)
22.2 (0.6)
22.9 (0.5)
21.4* (0.6)
22.6 (0.5)
21.7 (0.5)
21.8 (0.5)
23.2* (0.5)
67
00.2
0.40.60.8
1
1.21.41.6
1.82
0 100 200 300 400 500
Time (ps)
RM
SD
(A
ngst
rom
s)
Dana, et al., Figure 2.1
68
Figure 2.1. The RMSD of the backbone atoms for wild-type CHS from the starting
confirmation throughout the simulation.
69
* * * * *************** Arabidopsis CHS …YFRITNSEHMTDLKEKFKRMCDKS…………YQQGCFAGGTVLRIAKD…………AIDGHLREVGLTFHLLKD…………RATRHVLSEYGNMSS…………GFGPGLTVETVVLHSVPL. 100% Tea CHS2 …YFRITNSEHKTELKEKFQRMCDKS…………YQQGCFAGGTVLRLAKD…………AIDGHLREVGLTFHLLKD…………RATRHVLSEYGNMSS…………GFGPGLTVETVVLHSVST. 84% Snapdragon CHS …YFRITNSEHMTELKEKFKRMCDKS…………YQQGCFAGGTVLRMAKD…………AIDGHLREVGLTFHLLKD…………RSTRQVLSEYGNMSS…………GFGPGLTVETVVLHSVPLN. 84% Parsley CHS …YFRITNSEHMTDLKLKFKRMCDKS…………YQQGCFAGGTVLRLAKD…………AIDGHLREVGLTFHLLKD…………RATRQVLSDYGNMSS…………GFGPGLTVETVVLHSVPATFTH. 84% Raspberry CHS1 …YFRITKSEHKTELKEKFQRMCDKS…………YQQGCFAGGTVLRLAKD…………AIDGHLREVGLTFHLLKD…………EATRNILSEYGNMSS…………GFGPGLTVETVVLHSVAAST. 84% Maize CHS C2 …YFRITKSEHLTDLKEKFKRMCDKS…………YQQGCFAGGTVLRVAKD…………AIDGHLREVGLTFHLLKD…………RATRHVLSEYGNMSS…………GFGPGLTVETVVLHSVPITTGAATA. 82% Alfalfa CHS2 …YFKITNSEHKTELKEKFQRMCDKS…………YQQGCFAGGTVLRLAKD…………AIDGHLREAGLTFHLLKD…………NATREVLSEYGNMSS…………GFGPGLTIETVVLRSVAI. 81% Hops VPS …YFRVTKSEHMTDLKKKFQRMCEKS…………YQLGCYAGGKVLRIAKD…………AIAGHVTEAGLTFHLLRD…………KASREMLSEYGNMSC…………GFGPGLTVETVVLHH. 74% Grape THS2 …YFRVTKSEHMTALKKKFNRICDKS…………DQQGCYAGGTVLRTAKD…………AIAGNLREVGLTFHLWPN…………EATRHVLSEYGNMSS…………GFGPGLTIETVVLHSIPMVTN. 73% Rue ACS2 …YFRITNSEHMTDLKEKFKRMCDKS…………YQQGCYAGGTVLRLAKD…………AIEGHIREEGLTVHLKKD…………RASKHVMSEYGNMSS…………GFGPGLTVETVVLRSVPVEA. 72% Hydrangea CTAS …YFRVTKSDHLTDLKSKFKRMCERS…………YQQGCHAGGTGLRLAKD…………AIDGHLRQEGLTFHLRKD…………RVSRHILSEYGNMSS…………GFGPGFTVETIVLHH. 71% Daisy PS …YFRVTKSEHMVDLKEKFKRICEKT…………YQQGCAAGGTVLRLAKD…………AMKLHLREGGLTFQLHRD…………RASRHVLSEYGNLIS…………GFGPGMTVETVVLRSVRVTAAVANGN. 68% Orchid BBS …YFRVTNSEHLVDLKKKFQRICEKT…………YQQGCFAGGTTLRLAKC…………AIGGHVSEGGLLATLHRD…………SVSRHVLAEYGNMSS…………GFGPGLTVETVVLRSVPL. 65% Peanut STS …YFRVTNGEHMTDLKKKFQRICERT…………YHQGCFAGGTVLRLAKD…………AIGGLLREVGLTFYLNKS…………KATRDVLSNYGNMSS…………GFGPGLTIETVVLRSMAI. 64% Pine DPSS …YFRITGNEHNTELKDKFKRICERS…………FQHGCFAGGTVLRMAKD…………AIGGKVREVGLTFQLKGA…………IPTRHVMSEYGNMSS…………GFGPGLTIETVVLKSVPIQ. 64% •• • ••• • •• •• • • • ••• •• •• • • • ••• ••••••• •• ••
Dana, et al., Figure 2.2
165
188
276
259
331
345
378 TT4(UV113)
TT4(85)
TT4(UV25)
TT4(38G1R)
45
68 TT
4(UV01)
α2 α3 α7 α11 β10 β11 β5 β14 β15
70
Figure 2.2. Multiple sequence alignment of selected regions of a representative group of plant
type III polyketide synthases. CHS, acridone synthase (ACS), bibenzyl synthase (BBS),
coumaroyl triacetic acid synthase (CTAS), dihydropinosylvin-forming stilbene synthase (DPS),
2-pyrone synthase (PS), trihydroxystilbene synthase (THS), and valerophenone synthase (VPS)
sequences from a variety of plant species were aligned using CLUSTAL W (Thompson et al.,
1994). Highlighting indicates catalytic residues (red), CoA binding residues (purple), and active
site residues that are structural (yellow), control polyketide length (green), or determine substrate
specificity (blue) (Jez et al., 2000b). Residues that are altered in the four alleles are indicated
with asterisks; numbering is relative to the Arabidopsis CHS protein sequence. Percentages to
the right of the sequences refer to amino acid identity relative to Arabidopsis CHS. Pink dots
below the sequences indicate residues that are absolutely conserved among type II PKSs; green
dots indicate those conserved in CHS but not other type II PKSs. Elements of secondary
structure in the crystal structure of Arabidopsis CHS are identified below the sequences.
71
Dana, et al., Figure 2.3
A. B.
72
Figure 2.3. Structure of the Arabidopsis wild-type CHS enzyme. The structure represented
here is the 100 ps average from the molecular dynamics simulations at 27º C. Labeled on this
structure are the active site (red), determinants of substrate specificity (orange), product length
determinant (green), amino acids responsible for the binding of the CoA moiety (blue), the
locations of the tt4 substitutions or truncation (purple), and the residues proposed to be involved
in the interaction between CHS and CHI (yellow). A, front view; B, side view.
73
Dana, et al., Figure 2.4
A. B.
C. D.
ß15
a3 ß10
ß11
a7 ß14
74
Figure 2.4. Models of the Arabidopsis wild-type and tt4 CHS enzymes. The structures
were generated based on the crystal structure CHS from Arabidopsis as described in the
Methods. Active site residues (wild-type) and substituted residues (alleles) are labeled in
red. The secondary elements labeled in green indicate structural changes relative to the
wild-type. A, 27º C wild-type CHS structure; B, tt4(85) with alpha helix a3, showing
disorder, and beta sheets ß10 and ß11 labeled to indicate the location of the substitution;
C, tt4(UV113) with alpha helix a7 and the loop containing the active site cysteine
labeled; D, tt4(38G1R) with the areas corresponding to the location of beta sheets ß7,
ß12, ß13, and ß14 in the wild-type labeled to identify the loss of secondary structure
resulting from the truncation.
75
Chapter 3
Structural Characterization of the Chalcone Synthase-Chalcone Isomerase
Interaction
Christopher D. Dana1, Stéphane B. Richard2, Susan Krueger3, Joesph P. Noel2, and
Brenda S. J. Winkel1
1Department of Biology and Fralin Biotechnology Center, Virginia Tech, 2Structural
Biology Laboratory, The Salk Institute for Biological Sciences, and 3NIST Center for
Neutron Research
76
Abstract
Biosynthetic pathways are often organized within cells as groups of interacting enzymes
known as enzyme complexes or metabolons. Although this organization appears to be
widespread in biological systems, it is still poorly understood. The flavonoid pathway of
Arabidopsis thaliana has been developed in our laboratory as a model for studying
enzyme complexes (Burbulis and Winkel-Shirley, 1999). Several of the enzymes of this
pathway have been shown to interact in vitro, and have also been found to be co- localized
in roots (Burbulis and Winkel-Shirley, 1999; Saslowsky and Winkel-Shirley, 2001). Our
studies are currently focusing on the first enzymes of the flavonoid biosynthetic pathway,
chalcone synthase (CHS) and chalcone isomerase (CHI), which catalyze the condensation
and cyclization of coumaroyl-CoA and 3 malonyl-CoA into the central flavonoid
backbone. We propose a structure of the Arabidopsis CHS-CHI bienzyme complex as
deduced by X-ray crystallography, small-angle neutron scattering (SANS), in silico
docking, and molecular dynamics simulations. Surface-exposed residues thought to be
involved in this interaction have been altered and tested by yeast 2-hybrid analysis.
These experiments provide the first structural insights into the organization of flavonoid
biosynthesis as well as establishing SANS as a technique that can be used in the study of
metabolic organization.
77
Introduction
The study of multi-enzyme complexes, or metabolons, dates to the late 1950s with
the isolation of a complex of enzymes involved in the citric acid cycle (Green, 1958). As
time progressed, many more examples of multi-enzyme complexes were discovered,
introducing the idea that biosynthetic pathways are organized as metabolons and leading
to a broader understanding of how the cytoplasm of the cell is organized. Metabolic
complexes can be characterized as either static, which are very stable and require little
energy for association (Ovadi and Srere, 2000), or dynamic, requiring constant energy
input for complex integrity (Welch, 1977). This organization also has the potential to
offer numerous advantages to the cell such as coordinated flow of substrate from one
active site to another, high local substrate concentration, and sequestering of substrates as
protection for the both the cell and the pathway (Ovadi and Srere, 2000). Metabolic
complexes also provide a mechanism by which the types of end products being produced
can be quickly and effectively altered. It has even been suggested that all biosynthetic
pathways are organized as multi-enzyme complexes (Beeckmans et al., 1994; Beeckmans
et al., 1989; Gontero et al., 1988; Robinson et al., 1987).
Flavonoids constitute an important class of secondary metabolites produced in
higher plants. Chalcone synthase (CHS), catalyzes the first enzymatic reaction in
flavonoid biosynthesis, the condensation of three malonyl-CoA (from acetate
metabolism) molecules with coumaroyl-CoA (from the general phenylpropanoid
pathway) to create tetrahydroxychalcone (Figure 3.1). Chalcone isomerase (CHI),
catalyzes the creation of naringenin, which serves as the main flavonoid backbone for
78
ensuing enzymatic reactions that create flavonols, anthocyanins, condensed tannins, and
isoflavonoids (Figure 3.1). The products of general flavonoid biosynthesis have diverse
roles in plants, including serving as pigments in seeds, flowers and fruits and as UV
sunscreens (reviewed in Winkel-Shirley, 2002). These plant products also have anti-
oxidant, anti-dipsotrophic, and anti-cancer properties in mammals (reviewed in Havsteen,
2002). Recent metabolic engineering efforts have been directed at altering the amounts
and types of these compounds for nutritional enhancement of plants as well as
engineering plants with novel flower pigmentation (Forkmann and Martens, 2001; Muir
et al., 2001; Yu et al., 2003).
Some 30 years ago, Helen Stafford speculated that the flavonoid pathway
assembles as a multi-enzyme complex (Stafford, 1974a; Stafford, 1974b). The first
indirect evidence for the existence of a flavonoid metabolon was published by Fritsch and
Griseback (1975) who showed that operationally-soluble enzymes involved in flavonoid
biosynthesis localize to the endoplasmic reticulum (ER). Later sucrose density and
immunolocalization experiments verified that enzymes of both the general
phenylpropanoid and flavonoid pathways are localized to the cytoplasmic face of the ER
(Hrazdina and Wagner, 1985; Hrazdina et al., 1987; Wagner and Hrazdina, 1984). More
recent work demonstrated the first direct evidence of interactions between flavonoid
enzymes via affinity chromatography, yeast 2-hybrid analysis, and
coimmunoprecipitation experiments (Burbulis and Winkel-Shirley, 1999).
Immunofluorescence and immunoelectron microscopy experiments have shown that CHS
and CHI co- localize at the ER and that the intracellular distribution of these enzymes is
altered in an flavonoid 3’-hydroxylase (F3’H) mutant, consistent with a previously-
79
proposed role for F3’H as a membrane anchor for the complex (Stafford, 1990). This
work also showed an asymmetric distribution in root cortex cells that points to a possible
physiological significance of the organization in the control of auxin transport by
flavonoids. Additional evidence for a flavonoid metabolon comes from the expression of
anti-CHI antibodies in transgenic plants. These antibodies did not appear to change the
catalytic activity of CHI, but did alter the production of flavonoids in seedlings, possibly
by interfering with assembly of CHI into the flavonoid metabolon (Santos et al., 2004).
Deducing the architecture of the flavonoid complex and the mechanisms governing its
assembly and localization could yield critical new insights for effective engineering of
this and other metabolic systems.
Small angle neutron scattering (SANS) is a technique that probes three-
dimensional structure in a non-destructive manner (Koch et al., 2003). Data from SANS
experiments provides a low resolution structure for molecules in an aqueous
environment, independent of the packing inherent in crystal structures. This technique
has many useful applications in polymer science, materials science, and in the life
sciences. Examples of the latter include aiding in the determination of the structure of the
30S ribosomal subunit (Capel et al., 1987), elucidating better ways to crystallize a protein
by determining the amount of protein that is aggregated (Velev et al., 1998), structural
characterization of the GroEL/ES complex (Krueger et al., 2003), and structural changes
in SecA resulting from nucleotide binding (Bu et al., 2003).
SANS, together with in silico docking algorithms and molecular dynamics
simulations were used to develop a model of the CHS-CHI bienzyme complex. To
further define the interactions between CHS and other enzymes in flavonoid biosynthesis,
80
four surface-exposed phenylalanine and tryptophan residues on CHS were converted to
alanine and assayed by yeast 2-hybrid analysis. The molecular dynamics simulations
helped identify a series of residues that may be involved in an electrostatic interaction
between CHS and CHI that are being assessed in parallel 2-hybrid experiments. By
understanding the interaction between CHS and CHI, it is hoped that a better perspective
on metabolon architecture can be achieved, which in turn can be used in experiments to
better understand protein complex assembly and regulation as a whole.
Materials and Methods Site Directed Mutagenesis of pET32a (+)
The pET32a (+) vector was modified to allow cleavage of both the thioredoxin
(TRX) and hexa-histadine tags from the protein of interest, leaving just one spurious
amino acid (serine) on the N-terminus. Mutagenesis of pET32a(+) was performed using
the Quik Change site-directed mutagenesis kit (Stratagene La Jolla, CA). Primers were
designed to incorporate an NcoI site next to the thrombin proteolytic cleavage site. The
primers were 5’-GGTGCCACGCGGTTCCATGGTATGAAAGAA ACC-3’, with a
second primer containing the complementary sequence. The underlined portion of the
primer denotes the sequence that was altered. Mutagenesis was performed with Pfu
Turbo (Stratagene) under the following conditions: 95ºC for 30 s as an initial denaturing
step followed by 18 cycles of 95ºC for 30 s, 55ºC for 1 min, and 68ºC for 12 min. The
PCR product was treated with DpnI (Promega) for 1 h at 37ºC to digest the methylated
template DNA, then used to transform E. coli XL1-Blue MRF’ (Novagen) cells using a
heat shock method (Ausubel et al., 1989). The transformed cells were grown overnight at
81
37ºC on LBAmp100 plates. Confirmation of successful mutagenesis was via PCR using the
primer, 5’-GGTGCCACGCGGTTCCAT-3’, and the T7 terminator primer and then
sequenced using the BigDye Terminator kit (Stratagene) in order to verify sequence
fidelity. This modified pET32a plasmid was given the designation pCD1.
Creation of Expression Constructs
The CHS and CHI coding regions were subcloned into the NcoI and NotI or SalI
sites, respectively, of the pCD1 expression vector to create pCD1-CHS and pCD1-CHI.
PCR was performed using Pfu turbo (Stratagene) and the following primers: 5’-CATGC
CATGGTGATGGCTGGTGC-3’ and 5’-AGCGGCCGCTTAGAGAGGAACGC TGTG-
3’ for CHS and 5’-CATGCCATGGGAATGTCTTCATCCAACGC-3’ and 5’-
CGGTCGACTCAGTTCTCTTTGGCTAG-3’ for CHI, with pCHS.cr2 or pCHI.cr as the
templates (Pelletier and Shirley, 1996). Reactions were carried out under the following
conditions: 95ºC for 2 min as an initial denaturing step followed by 50 cycles of 94ºC for
30 s, 52ºC for 30 s, and 72ºC for 2 min and then a final elongation step of 72ºC for 10
min. The PCR products were then digested with NcoI and NotI (CHS) or SalI (CHI). T4
DNA Ligase (Promega, Madison, WI) was used to insert these fragments into the pCD1
expression vector. The ligation reaction was then used to transform E. coli DH5a cells
by electroporation (Dower et al., 1988). Transformed colonies were recovered on
LBAmp100 medium and screened by isolating plasmids using an alkaline lysis miniprep
(Ausubel et al., 1989; Birnboim and Doly, 1979) which were then digested with with
NcoI and NotI (CHS) or SalI (CHI). Positive clones were sequenced using the BigDye
82
Terminator kit (Stratagene, La Jolla, CA) in order to verify sequence fidelity. Plasmids
were then used to transform E.coli BL21(DE3) pLys-S (Novagen) using a heat shock
method (Ausubel et al., 1989) for expression and purification of recombinant protein.
Expression and Purification of pCD1-CHS and -CHI
A single colony containing either pCD1-CHS or pCD1-CHI was used to inoculate
LBAmp100-Cm34, which was grown overnight, then diluted 1:100 into the same medium.
The cultures were grown to mid- log phase (OD595 = 0.5-0.7) at 37ºC (approximately 4h),
then isopropyl-beta-D-thiogalactopyranoside (Alexis Biochemicals) was added to a final
concentration of 0.5 mM to induce protein expression. The cultures were grown at room
temperature with shaking (250 RPM) for a further 4 h. The cells were harvested by
centrifugation at 2500 x g for 10 min at 4ºC and frozen at -80º C until protein
purification.
Frozen cells were resuspended in lysis buffer (50 mM Tris, pH 8.0; 150 mM
NaCl; 10% glycerol; 1% Tween-20 and 10 mM ß-mercaptoethanol, approximately 33 ml
of lysis buffer per one liter of culture) and resuspended by stirring at 4ºC for 30 min. The
mixture was then sonicated six times for 30 sec each time on ice, with 2 min between
sonication. This lysate was centrifuged at 21,000 xg for 1 h at 4ºC. The supernatant
(crude extract) was passed over a Ni-NTA (Qiagen) column, which was packed and
equilibrated with 10 bed volumes of ddH2O and then 10 bed volumes of lysis buffer. The
column was washed with 10 bed volumes of lysis buffer and then with the same volume
of wash buffer (50 mM Tris, pH 8.0; 500 mM NaCl; 10 mM imidazole, pH 8.0; 10%
83
glycerol; and 10 mM ß-mercaptoethanol). Elution buffer (lysis buffer containing 250
mM imidazole, pH 8.0, but no Tween-20) was then passed over the column and four
fractions were collected (0.5, 2, 1 and 1 bed volumes). The fractions were analyzed by
SDS-PAGE in order to determine purity. Next, the TRX and hexa-histadine fusion
partner was removed by the addition of the protease, thrombin (Sigma) (1:1000 dilution
of a 1U/µl solution), into the protein preparation during dialysis into lysis buffer,
performed using SpectraPor 12-14,000 MWCO dialysis tubing (Spectrum), overnight at
4ºC, with stirring.
The dialyzed sample was analyzed by SDS-PAGE to confirm complete cleavage
of the TRX and hexa-histadine fusion partner from the protein of interest. The protein
preparation was then passed over a benzamidine-sepharose 4B (Amersham Biosciences)
to remove the thrombin. The TRX and hexa-histidine partner was removed by passing
the protein solution back over the Ni-NTA column and collecting the flow-through.
After sample purity was assessed by SDS-PAGE, the protein was dialyzed into 25 mM
HEPES, pH 7.5, 100 mM NaCl, 2 mM dithiothreitol (DTT), and 30-50% glycerol (in
order to concentrate the protein). The final purification step was carried out using a
Superdex 200 (Amersham Biosciences) gel filtration column on an Äkta FPLC system at
a flow rate of 0.5 ml/min with a pressure limit of 0.5 MPa. The column was prepared by
first passing over 10 bed volumes of ddH2O and then the same volume of FPLC buffer
(25 mM HEPES, pH 7.5, 100 mM NaCl, and 2-5 mM DTT). Fractions were collected,
assessed by SDS-PAGE, and those containing proteins of the correct size were pooled.
Protein concentration was determined either by the Bio-Rad microassay or based on an
A280 extinction coefficient calculated for each of the proteins. The protein preparation
84
was then concentrated to 20-30 mg/ml using Centriprep and Centricon (Millipore)
centrifugal filter devices.
Determination of the CHS Crystal Structure
CHS crystals were grown by vapor diffusion in hanging drops containing a 1:1
mixture of protein and crystallization buffer (16% PEG 8000 and 0.1 M TAPS pH 7.7) at
4º C. The crystals were stabilized in 18% PEG 8000, 0.1M TAPS, pH 7.7, and 15%
glycerol. CHS crystals grew in the space group P21 with 4 monomers per asymmetric
unit cell, with unit cell dimensions of a= 55.06, b=139.27 and c=109.60. Diffraction data
were collected from a single crystal mounted in a cryoloop and flash frozen in a nitrogen
stream at 105K. Data were collected at beamline 7-1 at the Stanford Synchrotron
Radiation Laboratory (SSRL 7-1) on a 30 cm MAR imaging plate detector. All images
were indexed and integrated using DENZO and the reflections merged with
SCALEPACK (Otwinowski and Minor, 1997). Data reduction was completed using
programs in CCP4 (Collaborative Computational Project, 1994) (Table 3.1). Structures
were determined using AMoRE (Navaza, 1994) with an Arabidopsis CHS homology
model (Saslowsky et al., 2000) as the starting structure. Refinement of the protein model
was performed with CNS (Brunger et al., 1998). Model building was carried out with the
program O (Jones et al., 1991) using SIGMAA-weighted |2Fo-Fc|, |Fo-Fc| electron density
maps (Collaborative Computational Project, 1994). Refinement consisted of iterative
cycles of simulated annealing, positional refinement, and B-value refinement. Model
quality was assessed with PROCHECK (Laskowski et al., 1993). All structure images
85
were manipulated with SwissPDB Viewer (Guex and Peitsch, 1997) and rendered with
POV-Ray (www.povray.org).
Multiple Sequence Alignment of CHS Proteins
A multiple sequence alignment of 15 representative members of the plant type III
PKS superfamily was generated using Clustal W (Thompson et al., 1994) using the
Megalign program in DNAStar (Madison, WI). Included in this analysis were CHS from
Arabidopsis (accession number P13114), alfalfa (P30074), maize (SYZMCC), parsley
(S42523), raspberry (AAK15174), snapdragon (P06515), and tea (P48387); acridone
synthase 2 from rue (Q9FSC0); bibenzyl synthase from orchid (S71619); coumaroyl
triacetic acid synthase from hydrangea (BAA32733); dihydropinosylvin-forming stilbene
synthase from pine (Q02323); PS from daisy (P48391); trihydroxystilbene synthase
sequences from grape (P51070) and peanut (S00334); and valerophenone synthase
(O80400) from hops.
Site-Directed Mutagenesis
Mutagenesis of CHS was carried out using the pCD1-CHS construct and the
QuikChange® system. The sequences of the primers used for F293A, F305A, W306A,
and W373A are given in Table 3.2. Mutagenesis was performed with Pfu Turbo
(Stratagene, La Jolla, CA) under the following conditions: 95ºC for 30 s as an initial
denaturing step followed by 16 cycles of 95ºC for 30 s, 55ºC for 1 min, and 68ºC for 7
86
min. Recovery of modified CHS plasmid constructs was as described as above for
construction of pCD1. Confirmation of the mutated CHS coding region was by PCR
using the appropriate confirmation primers (Table 3.2) and by sequencing.
Yeast Two -Hybrid Analysis
The mutated CHS coding regions were amplified using the primers listed in Table
3.2, digested with XhoI and NotI, and then cloned into the yeast 2-hybrid vectors, pBI-
880 (containing the Gal41-147 DNA-binding domain) and pBI-881 (containing the Gal4768-
881 transactivation domain) (Kohalmi et al., 1998). The ligation ractions were used to
transform E.coli DH10b cells by electroporation (Dower et al., 1988). Clones were
screened by PCR using the same primers used for amplification. The recombinant
plasmids were isolated using an alkaline lysis miniprep method (Ausubel et al., 1989;
Birnboim and Doly, 1979) and then used to transform Saccharomyces cerevisiae HF7c
cells (Feilotter et al., 1994) in pairwise combinations using the method of Gietz and
Schiestl (1995). Double transformants were selected on leu-, trp- synthetic dextrose
minimal medium (Ausubel et al., 1989). Interactions between fusion proteins were
assayed after 4 d at 30º C on leu-, trp-, his- minimial medium containing 5 mM 3-
aminotriazole (Sigma).
87
Small-Angle Neutron Scattering
Protein samples for SANS were purified as described above, then diluted to the
desired concentration (0.75, 1, 2, or 4 mg/ml) in FPLC buffer containing 5% glycerol.
For 2H2O studies, the samples were diluted to the appropriate concentration in FPLC
buffer prepared in 2H2O (Cambridge Isotopes) from stock solutions, which were made in
H2O, (resulting in approximately 9.5% H2O in the final solution), and dialyzed overnight
using Slide-A-Lyzer 10,000 MWCO cassettes (Pierce) at 4ºC against 2H2O buffer with
one buffer change at approximately 3 h.
SANS experiments were performed on the CHRNS NG3 30-m SANS (Glinka et
al., 1998) at the NIST Center for Neutron Research (NCNR). The neutron wavelength, ?,
was 5.50 Å with a wavelength spread, ??/?, of 0.150. Sample-to-detector distances of
5.0 and 1.5 m were used to obtain a wavevector transfer range of 0.009 Å-1 = Q = 0.3335
Å-1, where Q = 4psin(?)/? and 2? is the scattering angle. Data were collected at 25ºC
with total protein concentrations ranging from 0.75 to 4 mg/ml.
Neutron intensities were corrected for scattering from the buffers and from
background neutrons. Data were placed on an absolute scale by normalizing the scattered
intensity to the incident beam flux. Finally, the data were radially averaged to produce
scattered intensity, I(Q), vs Q curves. Distance distribution functions, P(r), were
calculated using the GNOM program (Semenyuk and Svergun, 1991), along with the
radius of gyration, Rg, forward scattered intensity, I(0), and the maximum dimension,
Dmax. Rg and I(0) values calculated from Guinier plots (Guinier and Fournet, 1955) were
used as a guide to determine the best P(r) function.
88
In Silico Docking
The CHS and CHI structures were docked using the geometric-hashing
methodology within the program Protein-Protein Dock (PPD) (Norel et al., 1994; Norel
et al., 1995; Norel et al., 1999; Norel et al., 2001). PPD performs rigid body docking of
one molecule into another via three steps: generation of a molecule’s critical points by a
molecular surface calculation, docking of the molecules using the critical points through
a matching algorithm, and evaluation of the solution. Intensities for each of the docked
complexes were scored against the SANS 1 mg/ml data set using the program CRYSON
(Svergun et al., 1995).
Molecular Dynamics Simulations
The CHS-CHI complex that best fit the SANS data was refined by molecular
dynamics simulations. The structure was first solvated with water, and sodium ions were
added to give the entire system a net charge of zero. Minimization of the solvent and
counterions was performed for 200 steps using Amber8 using steepest descent (Pearlman
et al., 1995). Molecular dynamics was then performed using the Sander module of
Amber8 for a total of 5 ns with a time step of 2.0 fs and a structure being collected every
1 ps. The dynamics simulations were performed using 16 processors on Virginia Tech’s
Laboratory for Advanced Scientific Computing and Applications Linux cluster. The
resulting structure was again compared against the SANS data as described above.
Interatomic distances, hydrogen bonding patterns, and root mean square deviation
89
(RMSD) values were determined using the Carnal program within Amber7 (Pearlman et
al., 1995). An average model was generated by coordinate averaging of the last 100 ps of
the dynamics simulation. The solvent and sodium ions were manually stripped from the
average structure and the system was minimized again as described above. The final,
minimized model was again compared against the SANS H20 and 2H2O data.
Multiple Sequence Alignments of CHS and CHI
Multiple sequence alignments of CHS and CHI from different Arabidopsis
ecotypes, members of the Brassicaceae family, and diverse plant species were generated
using ClustalW (Thompson et al., 1994) using the Megalign program in DNAStar
(Madison, WI). The ecotypes included in the CHS alignment are as follows, with
abbreviations and accession numbers given in parentheses: Arabidopsis thaliana
Landsberg erecta (Ler P13114), Maerkt (Mrk-0 CAF04429), Kashmir (Kas-1
CAF04430), Llagostera (Ll-0 CAF04432), Columbia (Col-0 CAF04433), and Lipowiec
(Lip-0 CAF04434). The CHI alignment included the following ecotypes: Landsberg
erecta (Ler AAA32766), Canary (Can-0 CAB94969), Champex (Cha-0 CAB94970),
Condhara (CAB94972), Granollers (Gran1 CAB94973), Graponne (Grap1 CAB94974),
Ibel Tazekka (Ita-0 CAB94975), Kashmir (Kas-1 CAB94976), Mechtshausen (Me-0
CAB94977), Muehlen (Mh-0 CAB94978), Monte (Mr-0 CAB94979), Wilp (Wlp2
CAB94982), Cape Verdi (Cvi-0 CAB94983), Eden (Ed1 CAB94984), Graz (Gr-5
CAB94985), Lulep (Lu1 CAB94986), Perm (Per-1 CAB94987), Richmond (Ri-0
CAB94988), Turk Lake (Tul-0 CAB94989), Yosemite (Yo-0 CAB94990), Rubezhnoe
90
(Rub-1 CAB94991), Ruds Vedby (RV8 CAD42211), and Tvärminne (TV5 CAD42220).
The sequence alignment for CHS from the Brassicaceae were A. thaliana (P13114),
Aethionema grandiflora (AAF23557), A. lyrata (CAF04461), A. griffithiana
(AAF23568), A. halleri (CAF04425), Arabis alpina (Q9SEP4), Cardamine amara
(Q9SEP2), Aubrieta deltoidea (AAF23584), Barbarea vulgaris (AAF23583), Arabis
turrita (AAF23582), Capsella rubella (AAF23581), Arabis procurrens (AAF23580),
Arabis pauciflora (AAF23577), Arabis parishii (AAF23576), Arabis lyallii (AAF23574),
Arabis lignifera (AAF23573), Arabis jacquinii (AAF23572), Arabis hirsuta
(AAF23571), Halimolobos perplexa (AAF23569), Arabis glabra (AAF23566), Arabis
fendleri (AAF23565), Arabis drummondii (AAF23564), and Arabis blepharophylla
(AAF23562). Sequences from Brassicaceae CHI family members were A. thaliana
(AAA32766) and A. lyrata (Q9LKC3). The multi-species aligment included CHS from
A. thaliana (accession number P13114), china aster (CAA91930), orange CHS1
(BAA81664), clove pink (CAA91923), morning glory CHS1 (BAA75310) and CHS2
(BAA36224), kudzu vine (BAA01075), maize (P24825), alfalfa CHS2 (P30074), petunia
(AAF60297), radish (AAB87072), rice (CAA61955), and grape (BAA31259). The
analysis using CHI proteins included sequences from the following species: A. thaliana
(AAA32766), china aster (CAA91921), orange (BAA36552), clove pink (CAA06202),
morning glory (AAB86474), kudzu vine (BAA09795), maize (S41570), alfalfa CHI1
(P28012), petunia CHI1 (ISPJCB) and CHI2 (ISPJA1), radish (AAB87071), rice
(AAO65886), and grape (CAA53577).
91
Results
CHS Structure
In order to solve the crystal structure of Arabidopsis CHS, recombinant protein
was expressed, purified, assayed for activity, and crystallized. The structure was solved
at 1.71 Å resolution with molecular replacement using a homology model for
Arabidopsis CHS (Saslowsky et al., 2000). The Arabidopsis CHS crystal structure
(Figure 3.2A) bears substantial similarity to that of Medicago sativa CHS2 (pdb id: 1BI5)
(Ferrer et al., 1999). When overla id, the Arabidopsis and Medicago CHS structures are
nearly identical, with the exception of a four amino acid insertion at the N-terminus of the
Arabidopsis protein (Figure 3.2B). The RMSD between the two proteins is 0.66 Å,
indicating very few structural differences. Arabidopsis CHS maintains the same aßaßa
core motif as other enzymes in the plant type III polyketide synthase superfamily (Ferrer
et al., 1999). The amino acids involved in catalysis, substrate specificity, and CoA
binding, are all conserved and in a similar location as in the Medicago CHS structure.
Experimental Evidence for a Role of Specific Residues in CHS in Assembly of the
Flavonoid Enzyme Complex
Ma et al. (2003) were able to identify phenylalanine and tryptophan residues that
are grouped together on the surface of a protein as important for interactions through
analysis of binding sites using the structure comparison algorithm MUSTA (Leibowitz et
92
al., 2001a; Leibowitz et al., 2001b). CHS residues F293, F305, W306, and W373 were
selected for analysis as these residues are surface-exposed on the same area of CHS.
Interestingly, each of these residues is highly conserved among plant type III polyketide
synthases. Both F293 and F305 are strictly conserved across 15 representative members
of this enzyme super-family, while W306 is conserved in all but soybean, and W373 has
substitutions in CHS and two stilbene synthases from pine.
The effects of these amino acid substitutions on the ability of CHS to interact with
other flavonoid enzymes were assayed using a yeast 2-hybrid system after alanine
substitution using site-directed mutagenesis. This system had previously been used by
Burbulis and Winkel-Shirley (1999) to identify interactions among wild-type CHS, CHI,
and dihydroflavonol 4-reductase (DFR). In this experiment, each of the CHS variants
was fused to either the binding domain (BD) or the transcriptional activation domain
(TA) of the yeast GAL4 protein and tested in all pairwise combinations with Arabidopsis
CHI and DFR. The wild-type constructs were tested to reproduce the original
experiments, showing interactions between the Gal4-TA CHS and Gal4-BD CHI
constructs as well as between the Gal4-TA DFR and the Gal4-BD CHS constructs (Table
3.3). Remarkably, each of the four introduced changes appeared to disrupt both of these
interactions. These results suggest that F293, F305, W306, and W373 define a surface
domain that functions in the interactions of CHS with several other flavonoid enzymes.
It is also possible that these substitutions have indirect effects on other surface domains
involved in protein-protein interactions. However, there are no indications of significant
structural changes from homology modeling and molecular dynamics simulations (data
not shown).
93
Small-Angle Neutron Scattering
SANS was used to examine the structure of the CHS and CHI bienzyme system in
solution. SANS data were collected for CHS and CHI at 0.75 and 1 mg/ml in either a
H2O or 2H2O buffer. The resulting scattered intensity curves are shown in Figure 3.4.
The data were normalized to a scattered intensity of I(Q = 0) = 1.0 so that the shapes of
the curves can be more easily compared. In this case, data were collected to a Q value of
0.3335 Å-1, which translates into a resolution of approximately 33 Å using the relation D
= 2p/Qmax (Jacrot et al., 1976).
Neutron scattering parameters calculated from the scattered intensity curves using
both Guinier and distance distribution function, P(r), analyses are shown in Table 3.4.
Although there were slight differences, the data from the P(r) analyses generally
concurred with the data from the Guinier approximation. Data from the P(r) analysis are
considered to be more reliable in comparisons to model structures because P(r) analysis
uses the entire Q range to calculate the radius of gyration and forward scattering intensity
[I(0)] values.
Interestingly, there seemed to be a difference in the makeup of the CHS-CHI
complex in H2O and 2H2O. From I(0), it is possible to calculate a rough molecular
weight estimate by the following equation:
2)(
)0(
vc
NIeightMolecularW A
ρ∆= Equation 1
where c is the concentration in g/cm3, ∆? is the contrast [scattering length density of the
protein minus that of the solvent (for protein in 2H2O: -3.40*1010 cm-2 and for protein in
94
H2O: 2.36*1010 cm-2)], v bar is the partial specific volume (0.73 cm3/g ) and I(0) is the
intensity at Q=0 (cm-1) from the normalized scattering data. When the molecular weight
was calculated for the 1 mg/ml data sets, there was a significant difference in the
predicted molecular weight of the complex in H2O and 2H2O (Table 3.4). It appears that
two CHI monomers interact with each CHS dimer in H2O, whereas only one CHI
monomer interacts with the dimer in 2H2O. 2H2O easily exchanges from H on solvent-
exposed carbons and nitrogens with 2H. This result suggests that the presence of 2H on
the protein interferes with the interaction, possibly by disrupting either hydrogen bonds
or electrostatic bonds between CHS and CHI.
In Silico Docking and Molecular Dynamics Analysis of the CHS-CHI Complex
The interaction of CHS and CHI was modeled using the crystal structures of
Arabidopsis CHS and CHI (J.P.N. unpublished results) with the program Protein-Protein
Dock (Norel et al., 1994; Norel et al., 1995; Norel et al., 1999; Norel et al., 2001), which
performs a rigid body docking of the two molecules based on the surface shape and
charge complementarily. This process produced 55 potential docking solutions that were
compared to the SANS intensity data using CRYSON (Svergun et al., 1995). The
proposed complex model that best fit the SANS data (Figure 3.5) was then subjected to
molecular dynamics simulations to allow for any structural changes resulting from the
interaction. The interaction of CHI with CHS in this model did not obscure either the
substrate channel or the surface exposed-residues on CHS involved in the binding of
95
substrate. Interestingly, the location of the CHS-CHI interface did not include the
residues that were analyzed in the yeast 2-hybrid experiments.
The molecular dynamics simulation did not identify any significant structural
changes at the interaction interface, as indicated by a RMSD value of 2.33 Å for the
entire system. In particular, two alpha helicies on CHI (a3 and a7) and one on CHI (a11)
remained relatively static (Table 3.5). The dynamics simulations identified three salt
bridges that are present between charged residues in the two enzymes: between E327 and
E328 on CHS and K18 on CHI, between R71 on CHS and E219 on CHI, and K361 of
CHS and E87 CHI (Figures 3.9 and 3.10). The distances between the alpha carbon atoms
remained fairly constant over the last 100 ps of the simulation, with standard deviations
no greater than 0.31 Å, and, in most cases, the residues moved closer to each other during
the simulation (Table 3.5). The model also predicted a hydrogen bond between T69 of
CHS and Q222 on CHI (Figures 3.9 and 3.10). To further investigate the function of
these residues in the CHS-CHI interaction, each is currently being altered to alanine for
analysis in the yeast 2-hybrid system.
CHS and CHI each exhibited one relatively mobile region throughout the
dynamics simulations. In CHS, this region corresponded to the first 13 residues, which is
solvent exposed in the model. The most mobile regions in the entire complex were sheets
ß4 and ß5 of CHI (Figure 3.6). Over the last 1 ns of simulation, the alpha carbon of
residue G53, a residue located in the turn between ß4 and ß5, moved 5.61 Å (Figure 3.7)
with a RMSD of 2.43 ± 0.682 Å. Interestingly, ß4 and ß5 help form the naringenin
binding cleft and include residues involved in the active site hydrogen bonding network
96
(Jez et al., 2000). It is possible that the presence of bound substrate stabilizes these two
sheets.
Conservation of Residues Involved in the CHS-CHI Interaction
In order to investigate conservation of residues predicted by these experiments to
be involved in the CHS-CHI interaction, multiple sequence alignments were generated
using representative CHS and CHI sequences from different ecotypes of Arabidopsis
thaliana, members of the Brassicaceae family, and more distantly-related plant species
for which sequences of both enzymes are known (Figure 3.10). For both CHS and CHI
there is absolute conservation of these residues as well as the surrounding sequences
among proteins from the various ecotypes of Arabidopsis (Figure 3.10). However, only
two of the residues in CHS, -R71 and -E328, are absolutely conserved among members
of the Brassicaceae family. In other Brassicaceae species, CHS-E327 is an alanine.
Interestingly, CHS-K361 is conserved in 14 of the species surveyed, and the other species
contain a glutamic acid at this position, which has the opposite charge (Figure 3.10).
Unfortunately, the corresponding CHI sequence is not available for these species to
determine whether compensatory changes have occurred in the other enzyme.
Investigation of the sequences from distantly-related plant species indicated many
differences between CHS and CHI at the proposed interaction interface. Across the CHS
species, two conserved residues were observed, R71 and E328, with few non-conserved
substitutions (Figure 3.10). Among the CHI proteins, the only proposed interaction
97
residue that appears to be conserved is E87. China aster contains the only significant
difference, with an alanine at this position; in all other species surveyed, position 87
retains a negative charge (Figure 3.10C).
Discussion
This study presents an experimental model for the interaction of CHS and CHI,
which catalyze the first two enzymatic reactions in flavonoid biosynthesis. Previous work
had implicated specific surface-exposed phenylalanine and tryptophan residues as
‘hot spots’ that are critical for protein-protein interactions (Ma et al., 2003). However,
from the data presented here, it appears that the surface-exposed phenylalanines and
tryptophans on CHS that were tested are not directly involved in the interaction between
CHS and CHI, but may play an indirect role by maintaining the structure of adjacent
domains that function in the interactions.
The model presented here encompasses only the first two enzymes of the
flavonoid pathway. However, many other questions relating to the flavonoid metabolon
remain to be answered, including the organization of the entire complex both in vitro and
in vivo as well as the effects of substrates and end products on its stability and
composition. The next step in the characterization of the flavonoid metabolon is to
determine how other flavonoid enzymes interact with the CHS-CHI bienzyme complex.
Previous studies from our laboratory indicate that DFR and F3H also interact with CHS
(Burbulis and Winkel-Shirley, 1999) as part of the flavonoid metabolon. Further
structural and SANS studies could help elucidate how these proteins interact with each
98
other. Surface plasmon resonance refractometry is a relatively new technology that could
be used to determine the kinetics of protein association and dissociation. Amide
hydrogen/deuterium exchange-MS experiments could also give information on both the
rates of association and dissociation as well as the solvent-accessible area present on a
protein (Mandell et al., 2001). Once more is known about the complex as a whole, it
might then be possible to alter the flux of the pathway to lead to the production of novel
flower coloration or more nutritious plants.
SANS is strictly an in vitro technique, and in vivo verification of potential models
is required. Validation of a SANS-developed model can be performed by site-directed
mutagenesis and yeast two-hybrid analysis as described here. Another way to validate a
model of such a complex could be through tandem affinity purification (TAP) tagging.
Recently, TAP tagging, coupled with mass spectrometry, has been used to identify
protein complexes present in yeast (Gavin et al., 2002; Graumann et al., 2004), mammals
(Brajenovic et al., 2004; Knuesel et al., 2003), and plants (Rohila et al., 2004) and could
easily be applied to the flavonoid metabolon.
The SANS experiments presented herein investigated two proteins in an
environment that is not crowded, unlike the environment present in the cell. Future
SANS experiments should be performed in the presence of a crowding agent, such as
polyethylene glycol (PEG), to provide a crowded environment, similar to the cell. PEG
has been shown previously to serve as a suitable crowding agent in studying metabolic
flux (Rohwer et al., 1998) and interactions (Kozer and Schreiber, 2004), however, there
are no examples of PEG being used as a crowding agent for specific SANS experiments.
99
Currently, little is known about the structure of metabolic enzyme complexes.
One of the few structural models of such organization is of enzymes involved in the citric
acid cycle (Vélot et al., 1997). The work presented here represents the first effo rt to use
SANS in the determination of the structure of a metabolic enzyme complex. SANS
coupled with in silico docking algorithms provided a powerful approach for predicting
the structure of the CHS-CHI bienzyme complex, which is now being tested
experimentally. These techniques are likely to find applications in the study of other
metabolic complexes where at least some structural information is available.
100
Acknowledgements
The authors would like to thank Mike Austin and Marianne Bowman of the Noel lab for
assistance with CHS purification and crystallization, the staff at the NIST Center for
Neutron Research for support with the SANS experiments, and Dr. David Bevan and Jory
Zmuda Ruscio for assistance with the molecular dynamics simulations. This work was
supported by the National Science Foundation (grants MCB-9808117 and MCB-
0131010) and by a grant from the Virginia Tech Graduate Research Development Project
to CDD. Portions of this research were carried out at the Stanford Synchrotron Radiation
Laboratory, a national user facility operated by Stanford University on behalf of the U.S.
Department of Energy, Office of Basic Energy Sciences. The SSRL Structural Molecular
Biology Program is supported by the Department of Energy, Office of Biological and
Environmental Research, and by the National Institutes of Health, National Center for
Research Resources, Biomedical Technology Program. We also acknowledge the
National Institute of Standards and Technology, U.S. Department of Commerce, in
providing facilities used in this work which are supported by the National Science
Foundation under Agreement No. DMR-9986442.
101
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Table 3.1: Crystallographic data Space Group P21 Unit Cell dimensions (Å) a = 55.06, b = 139.27, c = 109.60 Wavelength (Å) 1.08 Resolution (Å) 29.387 - 1.710 Unique reflections 152185
111
Table 3.2: Primers used for PCR and site directed mutagenesis for yeast 2-hybrid constructions A: Mutagenesis Primers (sections underlined indicate the location of the mutation): F293A (sense): 5'-GAAGAGTCTAGACGAAGCGGCAAAACCTTTGGGGATAAGTGAC-3' F293A (antisense): 5'-GTCACTTATCCCCAAAGGTTTTGCCGCTTCGTCTAGACTCTTC-3' F305A (sense): 5'-TGACTGGAACTCCCTCGCATGGATAGCCCACCCTG-3' F305A (antisense): 5'-CAGGGTGGGCTATCCATGCGAGGGAGTTCCAGTCA-3' W306A (sense): 5'-CTGGAACTCCCTCTTCGCAATAGCCCACCCTGGAG-3' W306A (antisense): 5'-CTCCAGGGTGGGCTATTGCGAAGAGGGAGTTCCAG-3' W373A (sense): 5'-CAGGAGAAGGGTTGGAGGCAGGTGTCTTGTTTGGTTTCG-3' W373A (antisense): 5'-CGAAACCAAACAAGACACCTGCCTCCAACCCTTCTCCTG-3' B: CHS amplification primers for yeast 2-hybrid constructs: CHS forward primer: 5’-CCGCTCGAGCATGGTGATGGCTGGTGC-3’ CHS reverse primer: 5’-AGCGGCCGCTTAGAGAGGAACGCTGTG-3’ C: Confirmation primers: F293A confirmation: 5’-CCCCAAAGGTTTAGC-3’ F305A confirmation: 5’-GGGTGGGCTATCCATGC-3’ W306A confirmation: 5’-GTGGGTGGGCTATCGC-3’ W373A confirmation: 5’-CCAAACAAGACACCCGC-3’
112
Table 3.3: Yeast 2-hybrid analysis of amino acid substitutions. Gal4-DB construct Gal4-TA construct
CHS CHI DFR CHSF239A CHSF305A CHSW306A CHSW373A
CHS +/- +/- +++ N/T N/T N/T N/T CHI +++ +/- - - - - - DFR +/- +++ +/- - - - - CHSF293A N/T - - N/T N/T N/T N/T CHSF305A N/T - - N/T N/T N/T N/T CHSW306A N/T - - N/T N/T N/T N/T CHSW373A N/T - - N/T N/T N/T N/T
+++ : Growth of yeast cells +/-, - : No growth of yeast cells N/T: Not tested
113
Table 3.4 Neutron scattering parameters for CHS and CHI in solution Gunier analysis P(r) Analysis Rg (Å) I(0) Rg (Å) I(0) CHS/CHI, H2O (1 mg/ml) 28.57 ± 0.827 0.0838 27.37 ± 0.393 0.0846 ± 0.0097 CHS/CHI, H2O (0.75 mg/ml) 30.99 ± 1.188 0.0380 27.70 ± 0.427 0.0336 ± 0.0084 CHS/CHI, D2O (1 mg/ml) 28.97 ± 0.242 0.120 26.67 ± 0.103 0.105 ± 0.0044 CHS/CHI, D2O (0.75 mg/ml) 28.47 ± 0.330 0.0615 26.80 ± 0.139 0.0599 ± 0.0045 Calculated molecular weigh of the CHS/CHI complexa
CHS/CHI, H2O (1 mg/ml) 174 kDa CHS/CHI, 2H2O (1 mg/ml) 117 kDa Predicted weight for complex composed of 1 CHS homodimer 140 kDa and 2 CHI monomers Predicted weight for complex composed of 1 CHS homodimer 113 kDa and 1 CHI monomer aMolecular weights from SANS data were calculated using equation 1.
114
Table 3.5: RMSD and distance measurements of secondary structure and residues proposed to be involved in the CHS-CHI interaction. (A): RMSD measurements for secondary structural elements involved in the CHS-CHI interaction. CHS a11 CHS ß13 CHS ß3 CHI a7 CHI a3 CHI ß1 CHS a1 Average of last 100 ps
1.72 (0.08)
0.911 (0.07)
1.22 (0.06)
1.04 (0.04)
1.75 (0.09)
0.927 (0.07)
3.32 (0.13)
Average of last 1 ns
1.56 (0.13)
0.852 (0.10)
1.34 (0.14)
0.991 (0.06)
1.56 (0.18)
0.934 (0.11)
3.43 (0.23)
(B): Distance averages of proposed residues involved in the CHS-CHI interaction. CHS residue # and atom type
E327 CD
E327 CA
E328 CD
E328 CA
T69 OG1
T69 CA
R71 NH1
R71 CA
K361 NZ
K361 CA
K361 NZ
K361 CA
CHI residue # and atom type
K18 NZ
K18 CA
K18 NZ
K18 CA
Q222 CD
Q222 CA
E218 CD
E218 CA
T86 OG1
T86 CA
E87 OE2
E87 CA
Average over last 100 ps of simulation
3.63 (0.31)
9.00 (0.29)
3.31 (0.13)
9.77 (0.29)
5.12 (0.42)
8.19 (0.26)
3.98 (0.37)
10.6 (0.31)
2.88 (0.11)
9.90 (0.20)
2.78 (0.12)
11.3 (0.19)
115
COSCoA
OHOH
COOH
NH2
Fatty Acid Metabolism
phenylalanine 4-coumaroyl-CoA
General Phenylpropanoid Pathway
3
Malonyl Co-A
+
CHS
OH
O
OHOH
OH
tetrahydroxychalcone
OH
O
OOH
OH
naringenin
CHI
OH
O
OOH
OH
OH
F3’H
F3H F3H OH
O
OOH
OH
OH
OH
O
OOH
OH
OH
OH
eriodictyol
DFR
F3’H
OH
OH
OOH
OH
OH
OH
OH
O+OH
OH
OH
OH
ANS
Anthocyanins
3GT, 5GT
ANR (BAN)
Condensed Tannins (proanthocyanidins)
OH
OOH
OH
OH
OH
LAR
OH
OOH
OH
OH
R
O
FLS
FLS
Flavonol glycosides
dihydrokaempferol dihydroquercetin
leucopelargonidin
leucocyanidin
cyanidin
Figure 3.1: Schematic of the flavonoid pathway in Arabidopsis thaliana . The pathway creates a diverse set of compounds used in UV protection, signaling, defense, and pigmentation. CHS represents that first committed step in the pathway, where 4-coumaroyl-CoA (from phenylpropanoid biosynthesis) and 3 units of malonyl-CoA (from fatty acid metabolism) are used as substrates. Structures in the figure represent the three enzymes in the pathway that crystal structures have been solved for, CHS (pdb id:1BI5) and CHI (pdb id:1EYQ) (both from Medicago sativa), and anthocyanidin synthase (ANS) (pdb id:1GP6) (from Arabidopsis thaliana). Structures in orange are homology models of dihydroflavonol 4-reductase (DFR), flavanone 3-hydroxylase (F3H), flavonoid 3’ hydroxylase (F3’H), and flavonol synthase (FLS). Other enzyme names are abbreviated as follows: anthocyanidin reductase (ANR), cinnamate 4-hydroxylase (C4H), p-coumarate:CoA ligase (4CL), leucoanthocyanidin reductase (LAR), phenylalanine ammonia-lyase (PAL). Arrows labeled in grey indicate branches of the pathway not present in Arabidopsis.
HOOC
COSCoA
Isoflavonoids
CHS/CHR
PAL C4H 4CL
3GT, RT
116
Figure 3.2: CHS crystal structure. A. Structure of the CHS dimer. Each monomer is labeled in a different color. B. Overlay of Medicago sativa CHS2 (gray) with Arabidopsis thaliana CHS (purple).
A. B.
117
Figure 3.3: Residues on CHS tested for effects on interactions with other flavonoid enzymes by yeast 2-hybrid analysis. The front (a) and side (b) views. The surface exposed phenylalanines and tryptophans selected for alanine substitutions are labeled in blue and the active site residues are labeled in red.
A. B.
118
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0 0.05 0.1 0.15 0.2 0.25 0.3
-0.02
0
0.02
0.04
0.06
0.08
0.1
0.12
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35
0
0.00002
0.00004
0.00006
0.00008
0.0001
0.00012
0.00014
0.00016
0.00018
0 10 20 30 40 50 60 700
0.00002
0.00004
0.00006
0.00008
0.0001
0.00012
0.00014
0.00016
0.00018
0 10 20 30 40 50 60 70
Dana, et al. Figure 3.4
A. B.
C. D.
Q (Å-1) Q (Å-1)
r (Å) r (Å)
I(Q
)
I(Q
)
P(r)
P(r)
119
Figure 3.4. Normalized SANS data. The CHS/CHI data in either H2O (A) or 2H2O (B) solvent. Normalized distance distribution function, P(r), for the CHS-CHI complex in H2O (C) or 2H2O (D) solvent. The CHS-CHI data at 0.75 mg/ml is labeled as x and the CHS-CHI data at 1.0 mg/ml is labeled as ?.
120
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
0.04
0.05
0 0.05 0.1 0.15 0.2 0.25 0.3
1mg/ml H2O data
Docked Structure
I(Q)
Figure 3.5: Data fit of the Docked CHS-CHI Complex. The optimized structure was fit to the 1 mg/ml data set from the SANS analysis. Data fit was performed using CRYSON (Svergun, et al., 1995).
Q (Å-1)
121
Figure 3.6: Proposed structure of the CHS-CHI enzyme complex. The CHS homodimer is represented in purple, CHI is in yellow, active site residues are labeled in red and the residues involoved in CoA binding are labeled in blue. (A) front view, (B) view from 45º on the left, (C) side view, and (D) top view.
A. B.
C. D.
122
Figure 3.7: Movement of beta sheets ß3a and ß3b of CHI at 100 ps intervals over the last 500 ps of dynamics simulation. Color labels are as follows, red: 4500 ps, orange: 4600 ps, yellow: 4700 ps, green: 4800 ps, blue: 4900 ps, and violet: 5000 ps. Over the course of the dynamics simulations the residue on the loop connecting the two beta sheets, glutamine 53 moves 5.61Å.
123
Figure 3.8: Residues proposed to participate in the CHS-CHI interaction. (a) front view and (b) top view. Residues contributed to the interaction by CHS are labeled in blue and the residues contributed by CHI are labeled in orange. In all of the structures, the active site residues are labeled in red.
A. B.
124
Figure 3.9: Close up of the interaction interface between CHS and CHI from the (a) front and (b) top. CHS is in purple, CHI is in yellow. The residues proposed to be important in this interaction are labeled with: basic residues in blue, acidic residues in red, and polar residues are in green.
A. B.
K18
K18
E327
E328
E218
E327
E328 Q222 T69
R71
Q222
R71
T69
E218
K361
E87
T86
125
Ler CHS …CDKSTIRKRHM…………LGLKEEKMRA…………RKSAKDGVA… 100% Mrk-0 CHS …...........…………..........………….........… 100% Kas-1 CHS …...........…………..........………….........… 100% Ll-0 CHS …...........…………..........………….........… 99.7% Col-0 CHS …...........…………..........………….........… 100% Lip-0 CHS …...........…………..........………….........… 100% Ler CHI …PAVTKLHVD…………KGKTTEELTE…………LSVAERLSQLMMK… 100% Can-0 CHI ….........…………..........………….............… 100% Cha-0 CHI ….........…………..........………….............… 99.6% Condhara CHI….........…………..........………….............… 100% Gran1 CHI ….........…………..........………….............… 100% Grap1 CHI ….........…………..........………….............… 100% Ita-0 CHI ….........…………..........………….............… 99.6% Kas-1 CHI ….........…………..........………….............… 100% Me-0 CHI ….........…………..........………….............… 100% Mh-0 CHI ….........…………..........………….............… 99.6% Mr-0 CHI ….........…………..........………….............… 100% Wlp2 CHI ….........…………..........………….............… 100% Cvi-0 CHI ….........…………..........………….............… 99.6% Ed1 CHI ….........…………..........………….............… 100% Gr-5 CHI ….........…………..........………….............… 99.6% Lu1 CHI ….........…………..........………….............… 100% Per-1 CHI ….........…………..........………….............… 99.6% Ri-0 CHI ….........…………..........………….............… 100% Tul-0 CHI ….........…………..........………….............… 100% Yo-0 CHI ….........…………..........………….............… 100% Rub-1 CHI ….........…………..........………….............… 100% RV8 CHI ….........…………..........………….............… 99.6% TV5 CHI ….........…………..........………….............… 100%
14
22
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91
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Dana, et al. Figure 3.10A
126
Arabidopsis thaliana CHS …CDKSTIRKRHM…………LGLKEEKMRA…………RKSAKDGVA… 100% Aethionema grandiflora CHS ….V.........…………....P.....…………K..RE..AV… 89.0% Arabidopsis lyrata CHS …-...M......………….........M………….........… 98.0% Arabidopsis griffithiana CHS …....M......…………..........………….........… 99.0% Arabidopsis halleri CHS …-...M......…………..........………….........… 98.5% Arabis alpine CHS …....M......…………....A.....…………K......A.… 96.7% Cardamine amara CHS …...........…………..........…………K........… 95.7% Aubrieta deltoidea CHS …....M......…………....A...K.…………K..EE..A.… 93.2% Barbarea vulgaris CHS …....M......…………....A.....…………K........… 94.9% Arabis turrita CHS …....M......…………....A.....…………K..VE..A.… 93.4% Capsella rubella CHS …....M......…………..........………….........… 98.5% Arabis procurrens CHS …....M......…………....A.....…………K..VE..A.… 93.7% Arabis pauciflora CHS …....M......…………....A.....…………..A.E..A.… 89.4% Arabis parishii CHS …....M......…………....A.....………….........… 98.0% Arabis lyallii CHS …....M......…………....A.....………….........… 98.0% Arabis lignifera CHS …....M......…………....A.....………….........… 97.7% Arabis jacquinii CHS …....M......…………....A.....…………K..VE..A.… 93.4% Arabis hirsute CHS …....M......…………....A.....…………K..VE..A.… 93.7% Halimolobos perplexa CHS …....M......…………..........………….........… 98.7% Arabis glabra CHS …....M......…………..........………….........… 98.2% Arabis fendleri CHS …....M......…………....A.....………….........… 98.0% Arabis drummondii CHS …....M......…………....A.....………….........… 97.5% Arabis blepharophylla CHS …....M......…………....A.....…………K..VE..A.… 93.2% Arabidopsis thaliana CHI …PAVTKLHVD…………KGKTTEELTE…………LSVAERLSQLMMK… 100% Arabidopsis lyrata CHI ….S....Q..…………........S.…………..I....AK..T.… 89.4%
65
75
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332
357
365
14
22
82
91
214
226
Dana, et al. Figure 3.10B
127
Arabidopsis CHS …CDKSTIRKRHM…………LGLKEEKMRA…………RKSAKDGVA… 100% China Aster CHS …....M....Y.…………..........…………K...E..A.… 83.9% Orange CHS1 …....M.K..Y.…………....G..L..…………K..VEEAK.… 85.2% Clove pink CHS …....M.K..Y.…………........A.…………K..LR..AT… 79.8% Morning glory CHS …....M.K..Y.…………....P..L..…………KA.SNA.LG… 80.9% Morning glory CHS2…....M.T..Y.…………....P..L..…………KA.SN..LG… 83.5% Kudzu vine CHS …....M.T..Y.…………....P...K.…………R...EN.LK… 83.8% Maize CHS C2 …....M....Y.…………V..DKAR...…………KR..E..Q.… 82.5% Alfalfa CHS2 …....M.KR.Y.………….A..P...N.…………K..TQN.LK… 82.0% Petunia CHS ….E..M.K..y.…………....P..LK.…………KA...E.LG… 84.8% Radish CHS …....M......…………....A.....…………R..LD....… 94.9% Rice CHS …....Q....Y.…………V..DK.RM..…………KR..E..H.… 81.7% Grape CHS ….E.......Y.………….......L..…………K..IEE.K.… 85.8% Arabidopsis CHI …PAVTKLHVD…………KGKTTEELTE…………LSVAERLSQLMMK… 100% China aster CHI ….LT.G.Q.E…………....VA..LD…………Q.L.S...D..KQ… 58.6% Orange CHI ….S..E.Q.E…………....A.....…………K.L.....A.LNV… 68.0% Clove pink CHI …AEI.QIQ.E…………....AD...D…………K.LSA...K.INQ… 60.2% Morning glory CHI….C.AEVK.E…………N..SV....D…………Q.L.V...EMFIN… 55.2% Kudzu vine CHI …ATISAVQ.E…………...PS...V.…………R.L.S..PAVLSH… 47.8% Maize CHI …M.CRRWWST…………G...AD..AS…………..L.A.V.E.LA.… 56.3% Alfalfa CHI1 …ASI.AIT.E…………...SS...LE…………RCL.A..PA.LNE… 46.4% Petunia CHI …VS...VQ.E…………...SA...IH…………C.I.A.M.E.FKN… 61.4% Petunia CHI2 …VS..RM..E…………....P....D…………C.....VAE.LKK… 60.2% Radish CHI ….TAP..Q..…………E.........………….R.....A...KE… 81.0% Rice CHI …A..SEVE..…………A..SAD..AA…………R.I.A.V...LKA… 53.2% Grape CHI ….S..AVQ.E…………....V...AD…………K.L.A...E.FCK… 65.8%
14
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65
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Dana, et al. Figure 3.10C
128
Figure 3.10: Multiple sequence alignments of Arabidopsis CHS and CHI protein sequences against other ecotypes of Arabidopsis thaliana (A), members of the Brassicaceae family (B), and different plant species. A dot represents the same amino acids as the Landsberg erecta ecotype of Arabidopsis thaliana. Residues proposed to be important for the interaction are shaded and dashed lines indicate the interacting pairs of residues. Boxes indicate conservative changes. Percentages to the right of the sequences refer to total amino acid identity relative to the Arabidopsis proteins.
129
Chapter 4
Conclusions
130
The organization of metabolism has become a focus of study over the past 40
years. In our laboratory, the Arabidopsis flavonoid biosynthetic pathway has been
developed as a model system for the study of metabolic organization. More than 30 years
ago, Helen Stafford suggested that enzymes in flavonoid biosynthesis are organized as a
metabolon (Stafford, 1974a; Stafford, 1974b), and subsequent experiments investigating
both the subcellular localization, channeling and co-fractionation (Hrazdina, 1992;
Winkel-Shirley, 1999) and the direct interactions of the enzymes (Burbulis and Winkel-
Shirley, 1999) have supported her hypothesis. This work laid the foundation for the
structural studies of the flavonoid complex described herein, the goals of which were
two-fold: 1) to structurally characterize an allelic series of the gene encoding chalcone
synthase (CHS), the first enzyme of the flavonoid pathway, using homology modeling
and molecular dynamic simulations, and 2) to determine the molecular basis of the
complex formed by interaction between CHS and the second flavonoid enzyme, chalcone
isomerase (CHI).
Computational analyses contributed significantly to this project. In silico
techniques were used to develop structural models for a series of CHS variants that had
been characterized on the gene, protein and endproduct levels (Saslowsky et al., 2000).
The single amino acid substitutions or truncation characterizing these variants result in
proteins with altered activity, stability, and dimerization ability. These computational
techniques provide an efficient way to predict the effect of these changes on local and
global protein structure without solving the crystal structure. However, this methodology
yielded few insights into the molecular basis of the temperature-sensitive variants.
131
Coupling these in silico techniques with quantum mechanical algorithms should aid in the
determination of catalytic mechanisms leading to the engineering of proteins with altered
activities. Previous molecular dynamics and quantum mechanics studies into the reaction
mechanism of Medicago CHI demonstrated that the substrate, tetrahydroxychalcone,
undergoes significant conformational changes during catalysis to naringenin (Hur et al.,
2004). These same types of computational approaches could be applied in preliminary
engineering efforts to determine the catalytic or structural roles of specific residues.
For the first time, a three-dimensional model for the interactions between
enzymes involved in flavonoid metabolism has been developed. Using a series of both
experimental and computational techniques, we were able to determine the structure of
CHS, suggest a model for the interaction between CHS and CHI, and test the residues
predicted to be important for the interaction using site-directed mutagenesis and yeast
two-hybrid analysis. Surface plasmon resonance refractometry (SPR) showed promise as
a way to determine the binding affinities of the CHS-CHI complex (C. Dana and B.
Winkel, unpublished data) and could be expanded to other interacting enzymes in the
pathway.
The next important step will be to expand these analyses to other enzymes in the
pathway in order to obtain a complete picture of the flavonoid metabolon, both on a
biochemical and structural level. Structures for most of the other flavonoid enzymes
have been determined either through X-ray crystallography [CHS, CHI, and
anthocyanidin synthase (Wilmouth et al., 2002)] or by homology modeling [flavanone 3-
hydroxylase, flavonol synthase, and dihydroflavonol 4-reductase (C. Dana, D. Owens,
and B. Winkel, unpublished data)] and could be used in SANS studies to piece together
132
the overall structure of the complex. However, flavanone 3’-hydroxylase (F3’H), the
proposed membrane anchor, would be more difficult to include in this type of analysis
due to its N-terminal transmembrane domain. An alternative approach that may be useful
in this situation is neutron reflectivity, a technique similar to SANS that uses neutrons to
probe membrane-associated molecules. As with SANS, a structural picture could be
gained by docking the protein structures using in silico algorithms followed by molecular
dynamics simulations. Briefly, F3’H would be expressed in mammalian cells and
purified with the transmembrane domain incorporated into a membrane bilayer. The
purified protein could then be subjected to neutron reflectivity to confirm initial structure
of F3’H to that of a previously generated homology model (C. Dana and B. Winkel,
unpublished data). Adding the other flavonoid enzymes sequentially to the immobilized
F3’H could then be used to help build a general model of the metabolon. There are, as
yet, no examples of neutron reflectivity being used in this manner. However, a new
instrument at the NIST center for neutron research, the advanced neutron
diffractometer/reflectometer, has been designed to be used for investigations into the
structure of membrane-bound proteins as well as biological membrane structure. This
type of analysis could lead to the definition of the structure of the complex as well as the
channels available for substrate movement between active sites and determining the
molecular basis of the interaction between proteins in the metabolon.
The experiments presented herein represent a significant leap forward in the
understanding of the structure of the flavonoid metabolon. The structure of the CHS-CHI
provides, for the first time, details about the interfaces required for the interaction
between these two cooperating proteins. Once the residues required for the interaction
133
are verified by in vitro assays, it might then be possible to start metabolic engineering to
lead to novel flavonoid production in Arabidopsis, such as the production of specific
pigments. To rationally design a change in pathway flux or endproduct levels, it is
imperative that the structure and biochemistry of the remaining parts of the pathway be
determined. This information could lead to eventual engineering efforts of the flavonoid
pathway in other plants to produce more nutritious plants or flowers with novel
pigmentation.
The CHS-CHI bienzyme model helped to establish SANS as a technology
through which the structure of a metabolic complex can be determined. To our
knowledge, this investigation was the first application of SANS in the study of metabolic
complex structure and assembly, for which little is known. Our findings suggest that
SANS offers a powerful approach in characterizing multi-enzyme systems and should
have applications in other systems where little is known about the organization of the
complex, adding to the paltry knowledge of metabolon organization. The data gained
from these experiments can also be used to gain more information on the structure of
metabolic complexes and then later, in metabolic engineering projects to alter flux within
a pathway in such a way to alter substrate flux or create novel endproducts beneficial to
animals.
134
References Cited:
Burbulis, I. E., and Winkel-Shirley, B. (1999). Interactions among enzymes of the
Arabidopsis flavonoid biosynthetic pathway. Proc Natl Acad Sci U S A 96,
12929-12934.
Hrazdina, G. (1992). Compartmentation in Aromatic Metabolism. In Phenolic
Metabolism in Plants, H. A. Stafford, ed.
Hur, S., Newby, Z. E., and Bruice, T. C. (2004). Transition state stabilization by general
acid catalysis, water expulsion, and enzyme reorganization in Medicago savita
chalcone isomerase. Proc Natl Acad Sci U S A 101, 2730-2735.
Saslowsky, D. E., Dana, C. D., and Winkel-Shirley, B. (2000). An allelic series for the
chalcone synthase locus in Arabidopsis. Gene 255, 127-138.
Stafford, H. A. (1974a). The metabolism of aromatic compounds. Ann Rev Plant Physiol
25, 459-486.
Stafford, H. A. (1974b). Possible multi-enzyme complexes regulating the formation of
C6-C3 phenolic compounds and lignins in higher plants. Rec Adv Phytochem 8,
53-79.
Wilmouth, R. C., Turnbull, J. J., Welford, R. W., Clifton, I. J., Prescott, A. G., and
Schofield, C. J. (2002). Structure and mechanism of anthocyanidin synthase from
Arabidopsis thaliana. Structure (Camb) 10, 93-103.
Winkel-Shirley, B. (1999). Evidence for enzyme complexes in the phenylpropanoid and
flavonoid pathways. Physiol Plant 107, 142-149.
135
Appendix A
Homology Modeling of Arabidopsis flavonoid enzymes.
136
Homology models were generated for flavonone 3-hyrdoxylase, flavonoid 3’-
hydroxylase, and dihydroflavonol 4-reductase based on the crystal structures for
Arabidopsis anthocyanidin reductase (Turnbull et al., 2004; Wilmouth et al., 2002),
human cytochrome P450 2C9 (Williams et al., 2003) and E. coli UDP-galactose-4-
epimerase (Liu et al., 1997), respectively. Alignment of the amino acid sequences was
performed using Modeller6 of Sali and Blundell (1993). Five models were produced for
each protein and an average model was generated for each protein by coordinate
averaging. The averaged structures were minimized using the Sander module of Amber7
for 200 steps using steepest descent (Pearlman et al., 1995). All structure images were
manipulated with SwissPDB Viewer (Guex and Peitsch, 1997) and rendered with POV-
Ray (www.povray.org).
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Figure A.1: Homology models of flavanone 3-hydroxylase (a), flavonoid 3’ hydroxylase (b), and dihydroflavonol 4-reductase (c).
A. B.
C.
138
References Cited: Guex, N., and Peitsch, M. C. (1997). SWISS-MODEL and the Swiss-PdbViewer: an
environment for comparative protein modeling. Electrophoresis 18, 2714-2723.
Liu, Y., Thoden, J. B., Kim, J., Berger, E., Gulick, A. M., Ruzicka, F. J., Holden, H. M.,
and Frey, P. A. (1997). Mechanistic roles of tyrosine 149 and serine 124 in UDP-
galactose 4-epimerase from Escherichia coli. Biochemistry 36, 10675-10684.
Pearlman, D. A., Case, D. A., Caldwell, J. W., Ross, W. S., Cheatham, T. A., DeBolt, S.,
Ferguson, D. M., Seibel, G., and Kollman, P. (1995). AMBER, a package of of
computer programs for applying molecular mechanics, a normal mode analysis,
molecular dynamics and free energy calculations to simulate the structural and
energetic properties of molecules. Comput Phys Commun 91, 1-41.
Sali, A., and Blundell, T. L. (1993). Comparative protein modelling by satisfactoin of
spatial restraints. J Mol Biol 234, 779-815.
Turnbull, J. J., Nakajima, J. I., Welford, R. W., Yamazaki, M., Saito, K., and Schofield,
C. J. (2004). Mechanistic studies on three 2-oxoglutarate-dependent oxygenases
of flavonoid biosynthesis. J Biol Chem 279, 1206-1216.
Williams, P. A., Cosme, J., Ward, A., Angove, H. C., Matak Vinkovic, D., and Jhoti, H.
(2003). Crystal structure of human cytochrome P450 2C9 with bound warfarin.
Nature 424, 464-468.
Wilmouth, R. C., Turnbull, J. J., Welford, R. W., Clifton, I. J., Prescott, A. G., and
Schofield, C. J. (2002). Structure and mechanism of anthocyanidin synthase from
Arabidopsis thaliana. Structure (Camb) 10, 93-103.
139
Appendix B
SPR Analysis of Flavonoid Enzymes
140
Real-time surface plasmon resonance refractometry was performed on a Leica
AR600 automatic refractometer equipped with a 10% planar carboxymethyl PEG/PEG
mixed self assembled monolayer (CM PEG/PEG m SAM) gold chip (Reichert, Inc).
Onto the CM PEG/PEG mSAM chip a NTA moiety was attached by NHS/EDC coupling
and was then charged with NiCl2 (Lahiri et al., 1999) All experiments were carried out at
25ºC with a constant flow rate of 0.3 ml/min in PBS-T buffer. The chip was allowed to
equilibrate in PBS-T for 30 minutes before the start of the experiment. Upon the start of
the experiment, each following solution was passed over the flow cell for 10 minutes
each starting first with PBS-T, then 10µM BSA, a PBS-T wash step, next the his-tagged
protein to be immobilized is passed over the chip (anywhere from 1-3 µM), another PBS-
T wash is performed to remove any unbound protein, the unbound protein to be studied is
next passed over the chip (again, anywhere from 1-3 µM), followed by a final wash with
PBS-T.
The his-tagged protein to be immobilized onto the slide consisted of thioredoxin-
his fusions of chalcone synthase (CHS) or chalcone isomerase (CHI) that were expressed
and purified as in Chapter 3 except that the fusion partner was not cleaved. The unbound
protein consisted of CHS or CHI which was expressed and purified as in Chapter 3 with
cleavage of the fusion partner.
141
Figure B.1. Representative SPR output. In these experiments either his::TRX::CHI (a)
or his::TRX::CHS (b) was immobilized and CHS or CHI, respectively, was passed over
the immobilized protein to detect for interactions between the two.
-5
0
5
10
15
2 0
25
3 0
35
4 0
45
0 10 20 30 40 50 60 70 80 90 100
time (minutes)
PBS-T
PBS-T
PBS-T
PBS-T
10 uM BSA his::TRX::CHI
CHS
SPR Experiment, December 10, 2001. Flow rate: 0.3 ml/min. His::TRX::CHI at 3 uM. Free CHS 1 uM.
-0.01
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0 50 100 150 200 250 300 350 400 450
time - 10s
chan
ge
in r
efra
ctiv
e in
dex
PBS-T
PBS-T PBS-T
PBS-T
BSA
TRX::CHS
CHI
SPR experiment, August 21, 2001. His-tagged TRX::CHS (3 uM) immobilized on Ni-NTA gold slide with free CHI (3 uM) passed over. Flow rate: 0.3 ml/min for
10 min ea
A.
B.
142
References Cited:
Lahiri, J., Isaacs, L., Tien, J., and Whitesides, G. M. (1999). A strategy for the generation
of surfaces presenting ligands for studies of binding based on an active ester as a
common reactive intermediate: a surface plasmon resonance study. Anal Chem
71, 777-790.
143
Christopher David Dana http://main.biol.vt.edu/department/faculty/winkel/chris.htm
709 Earl of Chesterfield Lane 107 Fralin Biotechnology Center Virginia Beach, VA 23454 Virginia Tech (540)449-9770 Blacksburg, VA 24061 e-mail: [email protected] (540)231-9375 Education Virginia Polytechnic Institute and State University, Blacksburg, VA Ph.D. Student (expected graduation date: July, 2004) Major: Biology QCA: 3.4 James Madison University, Harrisonburg, VA Majors: Integrated Science and Technology; Biotechnology & Engineering/Manufacturing Concentrations German Minor: Music Graduation Date: May 1999 Cumulative GPA: 3.4 Work Experience and Professional Development Virginia Tech Dates: 8/99-12/03 Graduate Teaching Assistant • Teach upper level molecular biology laboratory class (Fall 2000-present) • Assisted with development of current molecular biology laboratory manual • Taught freshman level general and principles of biology laboratory class (Fall 1999-
Spring 2000)
PPD Pharmaco (Contract Research Organization) Dates: 5/98-8-98 2244 Dabney Road Richmond, VA 23230 • Received GLP training • Developed database-tracking system for audits • Developed database for all archived records on site James Madison University Dates: 8/96-5/99 • Laboratory technician • Assisted with teaching of biotechnology labs • Assisted with development of new laboratory experiments for the junior level
biotechnology class
144
Ondal France E.U.R.L. (Subsidiary of Wella AG) Dates: 5/97-7/97 2. Rue Dennis Papin - B.P. 70305 57203 Sarrguemines Cedex, France • Laboratory technician analyzing products for conformance to specifications • Assisted with ISO 9002 certification efforts
Wella Manufacturing of Virginia, Inc. Dates: 5/96-7/96 4650 Oakley’s Lane Richmond, VA 23231 • Assisted with ISO 9002 certification efforts
Extracurricular Activities and Affiliations • Serving on the Structural Biology Search Committee • Principal 2nd Violinist, New River Valley Symphony (9/99-present) • Summer Musical Enterprises, Violinist in performance of “King and I” (5/03-8/03) • Treasurer, Biology Graduate Student Association (1/00-present) • Member: Virginia Academy of Science • Member: Sigma Xi Scientific Honor Society • Alpha Phi Omega: National Co-ed Community Service Fraternity; Spring, 1999:
Chapter parliamentarian • Golden Key National Honor Society Presentations • Structural Analysis of Flavonoid Enzyme Interactions in Arabidopsis. Presentation to
Dean DellaPenna’s Lab at Michigan State University. October 2003. • Heterologous Gene Expression in Bacteria and Yeast. Plant Metabolism Working
Group. April 2003. • Structural Analysis of Flavonoid Enzyme Interactions in Arabidopsis. 4th Annual
Arabidopsis Minisymposium. University of Maryland, College Park. April 2003 • Structural Analysis of Flavonoid Enzyme Interactions in Arabidopsis. Plant
Molecular Biology Discussion Group, April 2003. • Characterizing the Functional and Structural Domains in Flavonoid Enzymes. NIST
Neutron Division. February 2003. (Received small Honorarium for this talk) • The Flavonoid Biosynthetic Pathway: A Model for Protein-Protein Interactions in
Plants? Gordon Research Conference “Stage Invasion.” Queen’s College, Oxford, England. August 2002.
• Characterizing the Functional and Structural Domains in Flavonoid Enzymes. Plant Molecular Biology Discussion Group. May 2002.
• Homology Modeling of the tt4 Mutants in Arabidopsis thaliana. Virginia Academy of Science Meeting. May 2001.
145
• Characterizing the Functional and Structural Domains in Arabidopsis Flavonoid Enzymes. Botany Seminar. April 2001
• Characterizing the Functional and Structural Domains in Arabidopsis Flavonoid Enzymes. Plant Molecular Biology Discussion Group. October 2000.
• Characterizing the Functional and Structural Domains in Arabidopsis Chalcone Isomerase. Virginia Academy of Science Meeting. May 2000.
• Determination of Interaction Domains in Arabidopsis Chalcone Isomerase. James Madison University, College of Integrated Science and Technology. March 2000.
Posters Presented • A.S. Duda, C.D. Dana, and B. Winkel. Substrate Specificify of Dihydroflavonol 4-
Reductase. ACS undergraduate research symposium. Poster was awarded “Best Poster Presentation.”
• C.D. Dana, S. Krueger, J.P. Noel, and B. Winkel. Structural Characterization of the Flavonoid Biosynthetic Enzyme Complex. 1st Annual Biology Department Research Symposium. September 2003.
• C.D. Dana, S. Krueger, J.P. Noel, and B. Winkel. Structural Characterization of the Flavonoid Biosynthetic Enzyme Complex. 14th International Conference on Arabidopsis Research. University of Wisconsin. June 2003.
• C.D. Dana, S. Krueger, J.P. Noel, and B. Winkel. Structural Characterization of the Flavonoid Biosynthetic Enzyme Complex. The Gordon Research Conference on Macromolecular Organization and Cell Function. Queen’s College, Oxford, England. August 2002.
• C.D. Dana, D.R. Bevan, and B. Winkel. Homology Modeling of Mutations in the Arabidopsis Chalcone Synthase Gene. Phytochemical Society of North America. Oklahoma City, OK, August 2001.
• C.D. Dana, D.R. Bevan, and B. Winkel. Homology Modeling of the tt4 Mutants in Arabidopsis thaliana. 17th Annual Research Symposium of Virginia Tech, March 2001. Received 2nd place ($150.00 award)
• C.D. Dana, D.R. Bevan, and B. Winkel. Homology Modeling of the tt4 Mutants in Arabidopsis thaliana. Virginia Tech Workshop on Bioinformatics and Computational Biology, March 2001.
• C.D. Dana, D.R. Bevan, and B. Winkel. Homology Modeling of the tt4 Mutants in Arabidopsis thaliana. The Gordon Research Conference on Macromolecular Organization and Cell Function. Queen’s College, Oxford, England. August 2000.
Publications • Dana, C., Bevan, D.R., and Winkel, B. (in preparation) Molecular Modeling of the
Chalcone Synthase Mutant Alleles. • Winkel, B., DeCourcy, K., Dana, C., Grabau, E., and Lederman, M. (2001)
Laboratory Manual: BIOL 4774 Molecular Biology Laboratory. • Saslowsky, D.E., Dana, C.D., and Winkel-Shirley, B. (2000) An allelic series for the
chalcone synthase locus in Arabidopsis. Gene. 255:127-138.
146
Meetings Organized • Helped organize the 1st Annual Biology Department Research Symposium.
September 2003. • Gordon Research Conference “Stage Invasion.” A brief symposium before the start
of the GRC for graduate students and post docs to present their research. Queen’s College, Oxford, UK. August 2002. (This is not affiliated with the GRC).
Grants Applied for and Received • GSA Travel Fund award, $200, with matching funds from department, for travel to
the Gordon Research Conference on Macromolecular Organization and Cell Function (August 2002).
• NIST Center for Neutron Research, ~$850, to attend the NIST summer school on Neutron Scattering (June 2002).
• Joint Institute for Neutron Sciences, $1000 ($500 matching from department), to attend workshop on “Using Neutrons to Probe Structure and Dynamics in Biological Systems” at Oak Ridge National Laboratory (April 2002).
• GSA Travel Fund award, $100, Fall 2001, for travel to Phytochemical Society of North America annual meeting in Oklahoma City, OK (August 2001).
• Phytochemical Society Travel Award, $150, for travel to Phytochemical Society of North America annual meeting in Oklahoma City, OK (August 2001).
• Graduate Research Development Project, $500, with matching funds from biology department (Spring 2001).
• GSA Travel Fund award, $300, with matching funds from biology department, Fall 2000, for travel to Gordon Research Conference on Macromolecular Organization and Cell Function (August 2000).
• Graduate Research Development Project, $300, with matching funds from biology department (Spring 2000).
Other • Supervised the training and work of 4 undergraduate researchers: Ashley Duda (5/03-
current), Eric McFadden (5/01-5/03), Elizabeth Tucker (5/00 to 8/00), and Anna Watson (5/01-8/01).
• Redesigned and maintain Winkel Lab web page. Collaboratorators • Dr. Joseph Noel, Salk Institute. Crystallization of Flavonoid Enzymes. • Dr. Susan Krueger, NCNR, NIST. Solution Structure of the Flavonoid Multienzyme
Complex. • Dr. Geza Hrazdina. Cornell. Homology Modeling and Refinement of Polyketide
Synthases from Raspberry.
147
• Dr. Craig Nessler, Virginia Tech, PPWS. Homology Modeling of Alkaloid O-Methyltransferases.
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