Computational determination of fundamental pathway and activation barriers for acetohydroxyacid synthase-catalyzed condensation reactions of α-keto acids

Computational Determination of Fundamental Pathway

and Activation Barriers for Acetohydroxyacid Synthase-

Catalyzed Condensation Reactions of a-Keto Acids

YING XIONG,1,2* JUNJUN LIU,

1,2* GUANG-FU YANG,1CHANG-GUO ZHAN

2

1Key Laboratory of Pesticide and Chemical Biology of the Ministry of Education, College ofChemistry, Central China Normal University, Wuhan 430079, People’s Republic of China2Department of Pharmaceutical Sciences, College of Pharmacy, University of Kentucky,

725 Rose Street, Lexington, Kentucky 40536

Received 11 January 2009; Revised 5 March 2009; Accepted 18 May 2009DOI 10.1002/jcc.21356

Published online 24 June 2009 in Wiley InterScience (www.interscience.wiley.com).

Abstract: Acetohydroxyacid synthase (AHAS) is the first common enzyme in the biosynthetic pathway leading to

the production of various branched-chain amino acids. AHAS is recognized as a promising target for new antituber-

culosis drugs, antibacterial drugs, and herbicides. Extensive first-principles quantum mechanical (QM) and hybrid

quantum mechanical/molecular mechanical (QM/MM) calculations have enabled us, in this study, to uncover the

fundamental reaction pathway, determine the activation barriers, and obtain valuable insights concerning the specific

roles of key amino acid residues for the common steps of AHAS-catalyzed condensation reactions of a-keto acids.

The computational results reveal that the rate-determining step of the AHAS-catalyzed reactions is the second reac-

tion step and that the most important amino acid residues involved in the catalysis include Glu1440, Gln2070,Gly1210, and Gly511 that form favorable hydrogen bonds with the reaction center (consisting of atoms from the sub-

strate and cofactor) during the reaction process. In addition, Glu1440 also accepts a proton from cofactor thiamin

diphosphate (ThDP) through hydrogen bonding during the catalytic reaction. The favorable interactions between the

reaction center and protein environment remarkably stabilize the transition state and, thus, lower the activation bar-

rier for the rate-determining reaction step by �20 kcal/mol. The activation barrier calculated for the rate-determining

step is in good agreement with the experimental activation barrier. The detailed structural and mechanistic insights

should be valuable for rational design of novel, potent AHAS inhibitors that may be used as promising new anti-

tuberculosis drugs, antibacterial drugs, and/or herbicides to overcome drug resistance problem.

q 2009 Wiley Periodicals, Inc. J Comput Chem 31: 1592–1602, 2010

Key words: enzyme; catalytic mechanism; reaction pathway; QM/MM calculation

Introduction

Acetohydroxyacid synthase (AHAS; also known as acetolactate

synthase; EC 2.2.1.6; formerly EC 4.1.3.18) is the first common

enzyme in the biosynthetic pathway leading to the production of

branched-chain amino acids, including valine, leucine, and iso-

leucine, in plants and a wide range of microorganisms (such as

Escherichia coli, Saccharomyces cerevisiae, and Arabidopsisthaliana).1 This essential enzyme catalyzes the condensation of

two a-keto acid molecules, e.g., the condensation of two pyru-

vate molecules to form (S)-a-acetolactate and the condensation

of one pyruvate molecule with one a-ketobutyrate molecule to

form (S)-a-aceto-a-hydroxybutyrate. In addition, AHAS has been

proven to be an efficient catalyst in chiral synthesis and a potent

target in biochemistry engineering.2,3

AHAS is recognized as a promising target for new antituber-

culosis drugs,4 antibacterial drugs,5 and herbicides.6 For exam-

ple, Mycobacterium tuberculosis is the pathogen of tuberculosis

that remains a major threat to the human population. This

human disease is responsible for 2–3 millions deaths per year

worldwide.7 The emergence of drug-resistant and multidrug-

Contract/grant sponsor: Kentucky Science and Engineering Foundation;

contract/grant number: KSEF-925-RDE-008

Contract/grant sponsor: National Natural Science Foundation of China;

contract/grant numbers: 20602014, 20503008, 20432010

*These two authors contributed equally to this work.

Correspondence to: C.-G. Zhan; e-mail: [email protected]; G.-F. Yang;

e-mail: [email protected]

q 2009 Wiley Periodicals, Inc.

resistant tuberculosis has greatly increased the need to identify

new antituberculosis target proteins. It was shown that branched

amino acids auxotrophic strain of Mycobacterium failed to pro-

liferate because of the inability to use amino acids from their

hosts,8 indicating that inhibitors for the branched-chain amino

acid biosynthesis could be used as an antituberculosis agents.9

These observations suggested that AHAS could be a potential

target of new antituberculosis drugs. It was found that the

recombinant AHAS from M. avium, which is another human

tuberculosis pathogen, was efficiently inhibited by sulfonylureas

(SU),10 a herbicide that inhibits plant AHAS.

A number of structurally diverse, potent AHAS inhibitors,

have been reported in literature. Some of the known AHAS

inhibitors, e.g. SU, imidazolinones (IM), triazolopyrimidine sul-

fonanilides (TP), and pyrimidinyloxybenzoates (PB), have been

being used commercially as herbicides.6,11–16 Since their first

introduction in the early 1980s, AHAS inhibitors have been used

worldwide and now constitute the most important herbicide fam-

ily in use due to their unique advantages such as broad-spectrum

weed control at very low application rates, extremely low toxic-

ity to animals, and flexible application timing in a wide variety

of crops. However, constantly extensive use of AHAS-inhibiting

herbicides has resulted in about 95 tolerant weeds worldwide,

and this number has shown to be increasing at an exponential

rate. Most seriously, because the structurally diverse AHAS

inhibitors are competitive with one another with respect to the

binding with the enzyme, tolerance toward a particular herbicide

has resulted in varying degrees of cross-tolerance to the other

chemicals. Therefore, because of the widespread occurrence of

AHAS inhibitor-resistant weed species, the AHAS enzyme has

received considerable attention.

However, the currently known AHAS inhibitors, including all

the existing AHAS-inhibiting herbicides, have been proved to be

‘‘extraneous site inhibitors.’’ That is to say, the binding site of

the known AHAS inhibitors is not the active site of AHAS.

These compounds just bind within the tunnel connecting to the

active site, thus blocking substrate entry into the active site. As

a result, the mutations on amino acid residues in the inhibitor-

binding site resulted in resistance to the drugs/herbicides while

the enzyme activities were kept.17 An ideal strategy to develop

novel AHAS inhibitors for overcoming the drug resistance is to

design novel inhibitors that bind to the catalytic active site of

the enzyme, as amino acid residues in the active site are rather

conservative. With the inhibitor binding to the active site, one

would not need to worry about the resistance due to mutations

on the active site residues, as the mutations on the active site

residues would likely make the enzyme inactive. It is important

for rational design of the novel inhibitors of AHAS to under-

stand the detailed structure and fundamental catalytic mechanism

of the enzyme.

Recently, six X-ray crystal structures of A. thaliana AHAS in

complex with five different SU and one imidazolinone herbicide

have been reported.18 Like almost all thiamin diphosphate

(ThDP)-dependent enzymes,19 the active site of AHAS20–22 is

formed at the interface between two monomers and, therefore,

the minimum quaternary structure for catalysis is a dimer.

The enzyme-sequestered ThDP (cofactor) plays a central role

in the catalytic mechanism as shown in Figure 1.23 Initially,

ThDP is in its protonated form (R or ES) that then ionizes to the

reactive ylide (INT1); A molecule of pyruvate is attacked by the

ThDP anion to form the lactyl-ThDP (LThDP) intermediate

(INT2) which undergoes decarboxylation.24 In subsequent steps,

the hydroxyethylthiamin diphosphate (HEThDP) enamine/car-

banion (INT3) formed from the decarboxylation attacks the car-

bonyl of a second substrate (pyruvate or 2-ketobutyrate) to form

the product-ThDP adduct. Finally, the product-ThDP adduct dis-

sociates to form ThDP and the free product.25 Direct competi-

tion between alternative substrates for the bound HEThDP deter-

mines the ratio of products formed. In the wild-type enzyme, the

product ratio depends only on the relative amounts of the sub-

strates present and kcat is nearly independent of the amount or

identity of the substrates.25,26 This implies that kcat is determined

Figure 1. Catalytic cycle of AHAS.

1593AHAS-Catalyzed Condensation Reactions

Journal of Computational Chemistry DOI 10.1002/jcc

by the reaction step preceding the product-determining,

carboligation step so that the steps contributing to discrimination

among ‘‘second substrates’’ have little effect on the overall rate

of reaction. The ThDP adducts of LThDP, HEThDP, and the

product acetohydroxyacids (ALThDP and/or AHBThDP) can be

detected quantitatively in the mixture after rapid quenching.25

Determination of the distribution of the key reaction intermedi-

ates by 1H NMR analysis then makes it possible to calculate the

forward unimolecular rate constants for individual microscopic

steps. The forward (net) rate constant for formation of LThDP,

the first detectable step, is overwhelmingly rate determining for

catalysis, whereas the subsequent steps occur with similar, but

much larger rates (e.g., the rates of decarboxylation, carboliga-

tion, and product release are comparable).24,26 Such relative

rates explain why kcat for a given enzyme is essentially the

same for acetohydroxybutyrate (AHB) and acetolactate (AL)

formation, despite the 60-fold preference for 2-ketobutyrate as

substrate.

The present computational study was aimed to understand

the fundamental reaction pathway and energetics for the com-

mon reaction steps concerning the formation of HEThDP enam-

ine/carbanion intermediate before the further reaction with a sec-

ond substrate, particularly for the rate-determining reaction step.

The purpose of this computational study is twofold. One is to

provide fundamental mechanistic insights for a generally inter-

esting type of chemical and biochemical reactions, because the

condensation reactions catalyzed by an enzyme leading to the

eventual formation of branched-chain amino acids, such as

valine, leucine, and isoleucine, are a type of fundamentally inter-

esting chemical/biochemical reactions in biological systems. In

addition, the mechanistic insights obtained from the detailed

computational study can provide a solid, valuable mechanistic

base for rational design of the highly desirable novel AHAS

inhibitors that can tightly bind with the catalytic residues in the

active site. The novel AHAS inhibitors may be used as promis-

ing new antituberculosis drugs, antibacterial drugs, and/or herbi-

cides to overcome the drug resistance. For these purposes, we

have carried out detailed reaction coordinate calculations, for the

first time, on the common steps of AHAS-catalyzed condensa-

tion reactions by using first-principles quantum mechanical

(QM) and hybrid quantum mechanical/molecular mechanical

(QM/MM) methods. The reaction coordinate calculations have

led to valuable mechanistic insights concerning the detailed

reaction pathway and the specific role of some key residues, par-

ticularly for the rate-determining step.

Computational Methods

QM Reaction Coordinate Calculations

Geometries of all molecular structures, including reactants, tran-

sition states, and intermediates, involved in this study were opti-

mized by using density functional theory (DFT) using Becke’s

three-parameter hybrid exchange functional and the Lee-Yang-

Parr correlation functional (B3LYP)27–29 with the 6-311G(d)

basis set. Vibrational frequency calculations were carried out to

ensure that the optimized geometries are indeed associated with

local minima or saddle points on the potential energy surfaces

and to determine the zero-point vibrational energies (ZPVEs)

and thermal corrections to Gibbs free energies at 310 K. Intrin-

sic reaction coordinate (IRC)30,31 calculations were performed at

the B3LYP/6-311G(d) level to confirm the optimized transition

state geometries. The geometries optimized at the B3LYP/

6-311G(d) level were also used to perform single-point energy

calculations with the 6-311G(d), 6-3111G(d,p), and 6-

31111G(d,p) basis sets. All of the QM calculations were per-

formed by using Gaussian03 program.32

Preparation of Initial Structure for QM/MM Calculations

The initial structure used in the QM/MM geometry optimizations

was chosen from the X-ray crystal structure of A. thalianaAHAS in complex with a herbicide molecule (PDB code:

1Z8N). After the herbicide molecule was removed, pyruvate was

docked into the active site of AHAS. The missing hydrogen

atoms were added by using Leap module of Amber8 program.33

Histidine residues were assigned to (neutral) protonation state

HID or HIE based on the local hydrogen bonding network. The

partial atomic charges of substrate pyruvate and cofactors ThDP

and flavin adenine dinucleotide (FAD) required for the structural

preparation using Amber8 program were determined by perform-

ing ab initio QM calculations at the HF/6-31G* level following

by restrained electrostatic potential (RESP)-fitting calculations

using the RESP module of Amber8 program. All other force

field parameters were from the parm99 parameter library.

After the energy minimization of the added atoms using

Amber8 program in the gas phase, the AHAS-pyruvate complex

was solvated in a rectangular box of TIP3P water molecules

with a minimum solute-wall distance of 10 A and neutralized by

addition of counterions (Na1) using the Leap module of Amber8

program. Thus, a system of 95,600 atoms was obtained. To equi-

librate the solvated system, first of all, the protein system was

frozen and the solvent molecules with counterions were allowed

to move during a 3000-step energy minimization process. Sec-

ond, all the atoms were allowed to move during a 5000-step full

minimization process. Then, the water molecules beyond 2.5 A

of the complex were removed and the remained system was

used as the initial structure of QM/MM calculations described

below.

QM/MM Calculations

QM/MM calculations were performed by using a pseudobond

QM/MM method.34,35 The pseudobond QM/MM method was

initially implemented in revised Gaussian03 and Tinker pro-

grams.34,35 The revised Gaussian03 and Tinker programs can be

used to carry out the QM and MM parts of the QM/MM calcula-

tion iteratively until the full self-consistency is achieved. The

pseudobond QM/MM method uses a seven-valence-electron

atom with an effective core potential35 constructed to replace

the boundary atom of the environment part and to form a pseu-

dobond with the boundary atom of the active part. The main

idea of the pseudobond approach is as follows: one considers

that a large molecule is partitioned into two parts, an active part

and an environment part, by cutting a covalent r-bond Y-X. Y

and X refer to boundary atoms of the environment part and the

1594 Xiong et al. • Vol. 31, No. 8 • Journal of Computational Chemistry


active part, respectively. Instead of using a hydrogen atom to

cap the free valence of X atom as in the conventional link-atom

approach, a pseudobond Yps-X is formed by replacing the Y atom

with a one-free-valence boundary Y atom (Yps). The Yps atom is

parameterized to make the Yps-X pseudobond mimic the original

Y-X bond with similar bond length and strength, and also to have

similar effects on the rest of the active part.34,35 In the pseudo-

bond approach, the Yps atom and all atoms in the active part form

a well-defined QM subsystem which can be treated by a QM

method. Excluding Y atom, the remaining atoms in the environ-

ment part form the MM subsystem treated by a MM method. The

pseudobond ab initio QM/MM approach has been demonstrated

to be powerful in studies of enzyme reactions.36–38

In this study, we used a newly revised version39 of Gaus-

sian03 and Amber8 programs, instead of the revised Gaussian03

and Tinker programs, to perform the QM/MM calculations,

because the Amber program is capable of parallel computing. In

all of our QM/MM calculations, the QM subsystem included all

atoms of the substrate pyruvate, most atoms of cofactor ThDP,

amino acid residues Gly511 and Ala512 (from one AHAS mole-

cule of the homodimer), and residues Gly1200, Gly1210,Glu1440, and Gln2070 (from the other AHAS molecule of the

homodimer). See below for a figure (Fig. 3) in which the QM

atoms are highlighted. The remaining atoms of the protein

(including Mg21 and all atoms of nonreactive cofactor FAD that

do not directly participate in the reaction) and water molecules

were regarded as MM atoms. All water molecules were included

in the MM subsystem, as none of the water molecules are

expected to be involved in the covalent bond formation/breaking

during the reaction based on the X-ray crystal structure and the

structures modeled in the present study.

The boundary between the QM and MM subsystems was

treated according to the original pseudobond approach.34 The

total energy of the QM/MM system is

ETotal ¼ EMM þ EQM þ EQM=MM (1)

The QM-MM interactions consist of bonding and nonbonding

interactions. The nonbonding interactions between the two sub-

systems include the van der Waals (vdw) and electrostatic inter-

actions calculated through the Lennard-Jones potential and Cou-

lombic term, respectively, in the effective Hamiltonian. The

energy corresponding to the effective Hamiltonian, which is

obtained by QM calculation, is the sum of the QM energy of the

QM subsystem (EQM) and the electrostatic interaction between

the QM and MM subsystems.34 We used the reaction coordinate

driving method37,40 to search for transition states and intermedi-

ates. For example, during the QM/MM reaction coordinate cal-

culations on the second reaction step (rate-determining step) and

also on the first step, the reaction coordinate is represented by

the C2-C internuclear distance, where C2 refers to the carbon

atom at position-2 of ThDP as shown in Figure 1 and C refers

to the carbonyl carbon of pyruvate molecule. It should be noted

that many other geometric parameters should also change while

the C2-C distance changes during the reaction. The changes of

the other geometric parameters are automatic during the QM/

MM reaction coordinate calculations. The same reaction

coordinate approach has been used in many other computational

studies.39,41

Our initial QM/MM reaction coordinate calculations were per-

formed at the HF/3-21G*:Amber level, i.e., the QM calculations

were carried out at the HF/3-21G* level while the MM calcula-

tions were carried out by using the Amber force field imple-

mented in the Amber8 program. The geometry optimizations

were converged to the default criteria of the Gaussian03 (for QM

part) and Amber8 (for MM part) programs. During the QM ge-

ometry optimization process, the pseudobonds were treated with

the well-established effective core potential parameters associated

with 3-21G* basis set.35 In the MM energy minimization process,

only atoms within 20 A of ThDP were allowed to move. No cut-

off for nonbonding interactions was used in the QM/MM calcula-

tions and the MM energy minimizations. The iterative, restrained

geometry optimization/energy minimization processes were

applied repeatedly to different points along the reaction coordi-

nate, resulting in a minimum energy path for the reaction in the

enzymatic environment and its associated potential energy sur-

face. Given that the determined minimum energy path is smooth

and continuous, Hessian matrices for degrees of freedom involv-

ing atoms in the QM subsystem were calculated at stationary

points, leading to determination of the corresponding vibrational

frequencies.41 An energy maximum on the path with one and

only one imaginary frequency is a transition state, whereas an

energy minimum along the path without any imaginary frequency

is characterized as an intermediate. Finally, the geometries opti-

mized at the HF/3-21G*:Amber level along the reaction path

were then used to perform single-point energy calculations at

higher levels, including B3LYP/6-31G*:Amber, B3LYP/

6-311G*:Amber, B3LYP/6-3111G**:Amber, MP2/6-31G*:

Amber, and MP2/6-3111G**:Amber levels.

Most of the QM and QM/MM calculations were performed

in parallel on an IBM X-series Cluster (with 340 nodes and

1,360 processors) at the Center for Computational Sciences, Uni-

versity of Kentucky. Some computations were carried out on a

34-processors IBM x335 Linux cluster and SGI Fuel worksta-

tions in our own laboratory.

Results and Discussion

Fundamental Reaction Pathway and Activation Barriers

from QM Reaction Coordinate Calculations on the Model

Reaction System.

As depicted in Figure 1, the first three reaction steps are com-

mon for all of concerned condensation reactions of two a-ketoacid molecules no matter whether the second a-keto acid mole-

cule involved in the later reaction step is still pyruvate or not. In

addition, the aforementioned discussion indicates that the rate-

determining step of the condensation reactions is always the

second reaction step. So, our QM reaction coordinate calcula-

tions were focused on the first three reaction steps depicted in

Figure 1. To simplify the QM reaction coordinate calculations,

we used a simplified model system. Specifically, we replaced

the ��P2O7 group of ThDP with ��OH and the protein atoms

were not included in the reaction model. The fundamental reac-



tion pathway for the initial reaction step determined by the QM

reaction coordinate calculations is qualitatively consistent with

the mechanistic hypothesis depicted in Figure 1. AHAS is

believed to be activated in the same way as other ThDP-depend-

ent enzymes42 in which Glu1440, a highly conserved residue

among AHAS and other ThDP-dependent enzymes, protonates

the N10 atom of the pyrimidine ring43 and induces the formation

of the 10,40-iminotautomer.44–46 This basic 40-imino group is in

close proximity (3.3 A in the crystal structure of 1Z8N) to the

C2 catalytic centre of ThDP as a result of the cofactor’s V-con-

formation.18,47 The abstraction of the proton from C2 by the

10,40-iminotautomer (R) generates the highly reactive ylide

required for catalysis.43,48,49 According to the QM reaction coor-

dinate calculations, during the first reaction step, the proton on

C2 gradually transfers to the nearby N atom (N40) of the 40-imino

group on the pyrimidine ring to form the first intermediate

(INT1, which is the highly reactive ylide proposed previously)

through the first transition state (TS1) depicted in Figure 2.

Further, in the second step of the catalytic cycle of AHAS, C2

atom of the ylide (INT1) gradually attacks the carbonyl carbon of

substrate pyruvate, whereas the proton on N40 gradually transfers

to the carbonyl oxygen of the pyruvate molecule. This reaction

step gives the second intermediate LThDP (INT2) through the

second transition state (TS2). In the third step, LThDP is decar-

boxylated through the third transition state (TS3) to give the reso-

nating HEThDP-enamine intermediate (INT3), when a C��C

bond gradually breaks. Depicted in Figure 2 are the optimized

geometries of the reactants, transition states, and intermediates.

Figure 2. Geometries of the reactant (ES), transition states, and intermediates optimized at the

B3LYP/6-311G(d) level for the first three steps of proposed catalytic cycle of AHAS.



The energetic results listed in Table 1 show that the highest

activation barrier is associated with the second step, suggesting

the second step is rate determining. This is also qualitatively

consistent with the aforementioned experimental observation.25

However, the activation barrier, �36 kcal/mol calculated at the

B3LYP/6-31111G** level is significantly higher than the acti-

vation barrier (�16 kcal/mol) derived from experimental kinetic

data25 according to the well-known transition state theory in

which k(T) 5 (kBT/h) exp(2DG=/RT). We must account for the

effects of the protein environment on the activation barrier.

Reaction Pathway and Activation Barriers from QM/MM

Calculations

To account for the effects of protein environment on the reaction

pathway and the corresponding activation barrier of the enzy-

matic reaction, we performed QM/MM reaction coordinate

calculations on the first two reaction steps, including the rate-

determining step (i.e. the second step), of the entire enzymatic

reaction system. The QM/MM-optimized geometries of the

enzyme-substrate complex (ES), TS1, INT1, TS2, and INT2 are

depicted in Figure 3.

As seen in the optimized geometries of ES, TS1, and INT1,

during the first reaction step, the proton on C2 of ThDP gradu-

ally transfers to the nearby N atom (N40) of the 40-imino group

on the pyrimidine ring, whereas the proton on N10 atom of the

pyrimidine ring of ThDP gradually transfers to an oxygen atom

of the Glu1440 side chain. So, the first reaction step in the pro-

tein environment is a double-proton transfer process, instead of

the single-proton transfer process found in the aforementioned

model reaction system. The protein environment remarkably

changes the chemical nature of the first reaction step through

coupling with an additional proton transfer from ThDP to the

Glu1440 side chain of the protein. The additional proton transfer

from ThDP to the Glu1440 side chain is expected to significantly

stabilize the TS1 structure and, thus, significantly lower the acti-

vation barrier for this reaction step. The double-proton process

is completed when the first intermediate (INT1) is formed. In

fact, the activation barrier determined for the first reaction step

by the QM/MM calculations at the B3LYP/6-311G*:Amber//HF/

3-21G*:Amber and B3LYP/6-3111G**:Amber//HF/3-21G*:

Amber levels are only 1.90 and 1.94 kcal/mol, respectively. The

QM/MM-calculated activation barrier for this reaction step is

�6 to 7 kcal/mol lower than that calculated for the corresponding

step of the model reaction system.

Because of the different chemical nature of the first reaction

step, the chemical nature of the second reaction step in the protein

environment is also remarkably different from that in the model

reaction system. Without accounting for the protein environment,

the QM reaction coordinate calculations on the aforementioned

model reaction system demonstrated that the proton on N40 gradu-

ally transfers to the carbonyl oxygen of pyruvate, whereas the C2

atom gradually attacks the carbonyl carbon of substrate pyruvate.

However, according to the QM/MM reaction coordinate calcula-

tion, the proton on N40 only forms a hydrogen bond with the

carbonyl oxygen atom of pyruvate (in INT2), whereas the C2

atom gradually attacks the carbonyl carbon of substrate pyruvate.

The proton on N40 does not transfer to the carbonyl oxygen of

pyruvate according to the QM/MM calculations.

In the INT1, TS1, and INT2 geometries depicted in Figure 3,

pyruvate atoms form two hydrogen bonds with amino acid resi-

dues of AHAS. One hydrogen bond exists between the carbonyl

oxygen of pyruvate and the NH2 group of Gln2070 side chain

(through 1HE2 atom on the NH2 group). The other hydrogen bond

exists between the carboxyl oxygen of pyruvate and the backbone

NH of Gly1210. In addition, ThDP atoms also form two hydrogen

bonds with amino acid residues of AHAS. One of the hydrogen

bonds exists between the carbonyl oxygen of Gly511 backbone

and the N40 atom of ThDP (through an H atom on N40). The other

exists between the N10 atom of ThDP and the protonated oxygen

on the side chain of Glu1440. The later is consistent with the

experimental observation reported by Bar-Ilan.42 Altogether, the

four hydrogen bonds between pyruvate-ThDP and the four resi-

dues of AHAS are expected to stabilize the TS2 structure and,

therefore, lower the activation barrier.

Further, a sequence alignment of 24 available AHAS pro-

teins6 from different sources, including plant, fungal, algal, and

bacterial species, reveals that the aforementioned four key resi-

dues forming hydrogen bonds with pyruvate or ThDP are all

highly conserved for AHAS enzymes, suggesting that these four

residues (i.e., Glu144, Gln207, Gly121, and Gly511) may play

an important role in the catalysis for all of the AHAS enzymes.

Our structural results are qualitatively consistent with available

experimental kinetic data in literature. For example, Glu47Gln

and Glu47Ala mutations on E. coli AHAS II (corresponding to

Glu144Gln and Glu144Ala mutations on A. thaliana AHAS II)

decreased the catalytic rate constant (kcat) of the enzyme by

about 10- and 13-fold, respectively.42 This is because the muta-

tions destroy the hydrogen bond between the N10 atom of ThDP

and the protonated oxygen on the side chain of Glu144 (or

Glu47 in E. coli AHAS II). For the same reason, substitution of

ThDP with an analog without N10 or the 40-amino group also

considerably decreased the enzymatic activity.50 These experi-

mental data qualitatively confirm the importance of Glu1440 resi-due in stabilizing the TS2 geometry depicted in Figure 3. Chip-

man and coworkers51 also reported that mutation of a highly

conserved residue, i.e., Gln110 in E. coli AHAS II correspond-

Table 1. Activation Barriers (DG=, in kcal/mol) Obtained from the QM

Calculations on the Model System for the First Three Steps of

AHAS-catalyzed Condensation Reactions.a

Method DG1= b DG2

= b DG3= b

B3LYP/6-311G* 9.27 37.50 0.25

B3LYP/6-3111G** 7.65 37.29 0.29

B3LYP/6-31111G** 8.09 35.83 0.00

Expt.c 16.21

aAll the geometries were optimized at B3LYP/6-311G* level.bDG1

=, DG2=, and DG3

= refer to calculated activation barriers for reaction

steps 1, 2, and 3, respectively, in Figure 1. Included also in DG1=, DG2

=,

and DG3= values are thermal corrections to free energies calculated at

B3LYP/6-311G* level.cThe experimental activation barrier was based on the experimental data

in Ref. 25 and the transition state theory in which k(T) 5 (kBT/h)

exp(2DG=/RT).



ing to Gln207 in A. thaliana AHAS II, led to ‘‘a significant loss

of activity,’’ although they did not report specific kinetic param-

eters for the mutations on the residue. Their experimental

observation qualitatively confirms the importance of Gln2070 instabilizing the TS2 geometry depicted in Figure 3. The hydrogen

bond between the N40 atom of ThDP and the backbone oxygen

atom of Gly511 existed in all of the QM-MM-optimized geome-

tries depicted in Figure 3, which is consistent with the observa-

tion by Duggleby et al.52 that such a hydrogen bond existed in

all of the X-ray crystal structures of AHAS.

Depicted in Figure 3(F) are the plots of the relative potential

energies calculated at the HF/3-21G*:Amber, B3LYP/6-31G*,

B3LYP/6-311G*:Amber, B3LYP/6-3111G**:Amber, and

MP2/6-31G*:Amber levels versus the reaction coordinate (the

Figure 3. QM/MM-optimized geometries of ES (A), TS1 (B), INT1 (C), TS2 (D), and INT2 (E) and

the potential energy surface along the reaction coordinate for the rate-determining step (F). In the

optimized geometries, the QM atoms used on the QM/MM calculations are represented by the balls.



minimum-energy path). It would be very time consuming to

perform QM/MM calculations on all of the structures along

the reaction path at the MP2/6-3111G**:Amber level. So,

single-point QM/MM energy calculations at the MP2/

6-3111G**:Amber level were only performed on the INT1 and

TS2 geometries used for the QM/MM calculations at the MP2/

6-31G*:Amber level to estimate the activation barrier at the

MP2/6-3111G**:Amber level. The QM/MM-calculated values

of the activation barrier are summarized in Table 2. As one can

see in Table 2, the QM/MM calculations at the HF/3-

21G*:Amber level considerably overestimated the activation bar-

rier for this reaction step. The QM/MM calculations at the

B3LYP/6-31G*:Amber level also significantly overestimated the

activation barrier. Nevertheless, the QM/MM calculations at

more sophisticated levels, including the B3LYP/6-311G*:

Amber, B3LYP/6-3111G**:Amber, MP2/6-31G*:Amber, and

MP2/6-3111G**:Amber levels, all lead to very close results

(15.20 to 15.82 kcal/mol) that are all in good agreement with

the experimental activation barrier of 16.21 kcal/mol.25 We note

that various new density functionals were reported in the past a

few years and that some newly developed functionals could out-

perform B3LYP.53,54 To examine the effect of the choice of the

density functional on the calculated activation barrier, the activa-

tion barrier of the rate-determining step (step 2) was also

calculated by using several other functionals available in the

Gaussian03 program. As shown in Table 2, the activation barrier

calculated with B3LYP is closest to the result calculated with

the MP2 method and the experimental activation barrier of

16.21 kcal/mol25 for this particular QM/MM system.

The activation barrier calculated with the QM/MM method

considering the effects of protein environment is �20 kcal/mol

lower than the corresponding activation barrier calculated with

the QM method neglecting the protein environment. To better

understand how the protein environment contributes to the

�20 kcal/mol decrease of the activation barrier, we also

determined the single-point energy surface of a tailored QM/

MM system in which the MM part includes only the residues

having covalent bonds with the QM atoms. The activation

barrier calculated at the B3LYP/6-3111G**:Amber level for

the tailored QM/MM system is 15.97 kcal/mol, which is only

slightly higher than 15.20 kcal/mol calculated for the complete

QM/MM system. These results suggest that the protein environ-

ment affects the reaction and activation barrier mainly through

maintaining the active site of the enzyme.

To further understand the importance of Glu144 in catalysis,

we also carried out the QM/MM reaction coordinate calculations

on the second reaction step (i.e. the rate-determining reaction

step) associated with the Glu144Ala mutant at the same QM/

MM level of theory used for the native enzyme. The QM/MM-

optimized INT1 and TS2 geometries for the mutant are depicted

in Figure 4. Compared with the corresponding QM/MM-

optimized INT1 and TS2 geometries (in Fig. 3) associated with

the native enzyme, the hydrogen bonding interactions in the

INT1 and TS2 geometries (in Fig. 4) associated with the

Glu144Ala mutant are all similar, except that the hydrogen bond

between residue #144 and ThDP no longer exists in the mutant.

As a result, the activation barrier calculated (at the same MP2/

6-3111G**:Amber//HF/3-21G*:Amber level) for the second

reaction step of the reaction catalyzed by the Glu144Ala mutant

is 17.0 kcal/mol, which is 1.7 kcal/mol higher than the corre-

sponding activation barrier (15.3 kcal/mol in Table 2) calculated

for the second reaction step of the reaction catalyzed by the

native enzyme at the same level of theory. The calculated acti-

vation barrier increase of 1.7 kcal/mol is in good agreement

with the experimental observation that the Glu47Ala mutation

on E. coli AHAS II (corresponding to Glu144Ala mutation on

A. thaliana AHAS II) decreased the catalytic rate constant (kcat)of the enzyme by �13-fold,42 as a �13-fold decrease in kcat cor-responds to a �1.5 kcal/mol increase in activation barrier

according to the conventional transition state theory (CTST).55,56

It should be pointed out that the starting structures used for

the above QM/MM reaction coordinate calculations were all

based on the X-ray crystal structure. Warshel and coworkers57

noted that QM/MM reaction coordinate calculations on an enzy-

matic reaction system using different starting structures could

lead to significantly different activation barrier values. More

recently, Zhang and coworkers38 performed pseudobond QM/

MM reaction coordinate calculations on an enzymatic reaction

by using multiple initial structures, i.e., multiple snapshots of a

molecular dynamics (MD) simulation of the enzyme-substrate

complex. According to the QM/MM calculations by Zhang and

coworkers,38 the fluctuation of the calculated energy barriers is

only 61.1 kcal/mol and the barrier fluctuation has a strong cor-

relation with the values of the geometric parameters associated

Table 2. Activation Barrier (DG2=, in kcal/mol) for Calculated by

Performing QM/MM Calculations on the Second Reaction Step of the

AHAS Catalytic Cycle.

Methoda DG2= (kcal/mol)

QM/MM(HF/3-21G*:Amber) 22.33

QM/MM(B3LYP/6-31G*:Amber) 18.79

QM/MM(B3LYP/6-311G*:Amber) 15.82

QM/MM(B3LYP/6-3111G**:Amber) 15.20

QM/MM(MPWKCIS1K/6-3111G**:Amber) 18.19

QM/MM(BHandHLYP/6-3111G**:Amber) 20.25

QM/MM(B97-2/6-3111G**:Amber) 14.48

QM/MM(mPW1PW91/6-3111G**:Amber) 12.93

QM/MM(B98/6-3111G**:Amber) 14.10

QM/MM(MP2/6-31G*:Amber) 15.33

QM/MM(MP2/6-3111G**:Amber)b 15.31

Expt.c 16.21

aCalculated activation barrier (DG2=) is calculated as the energy change

from INT1 to TS2 on the corresponding minimum-energy path. Thermal

correction to Gibbs free energy at the HF/3-21G* level at T 5 310 K

was included in the calculation of DG2=.

bQM/MM reaction coordinate driving was not carried out at the MP2/6-

3111G**:Amber level because it would be very time-consuming at this

level of theory for this particular enzymatic reaction system. Instead, we

only performed the single-point energy calculations on the local mini-

mum (associated with INT1) and first-order saddle point (associated with

TS2) geometries determined at the MP2/6-31G*:Amber level.cThe experimental activation barrier was based on the experimental data

in Ref. 25 (determined at T 5 310 K) and the classic transition state

theory in which k(T) 5 (kBT/h) exp(2DG=/RT).



with the reaction coordinate. When the values of the geometric

parameters associated with the reaction coordinate in a snapshot

are closer to the corresponding average values of the geometric

parameters in the simulated enzyme-substrate complex, the

energy barrier calculated with this snapshot is closer to the aver-

age value of the energy barriers calculated with all of the chosen

snapshots. The pseudobond QM/MM reaction coordinate

approach used in the present study is very similar to that used

by Zhang and coworkers38 Hence, the similar performance and

similar structure-barrier fluctuation correlation, and hopefully the

similarly small energy barrier fluctuation, may be expected for

the present pseudobond QM/MM reaction coordinate calcula-

tions. To examine the possible barrier fluctuation for the current

reaction system, we further carried out an MD simulation on the

INT1 structure for 2 ns and obtained a stable MD trajectory.

The MD simulation was performed in the same way as we did

in our previous computational studies on other protein

systems.58–60 The final snapshot of the MD-simulated INT1

structure was used as the initial structure to repeat the QM/MM

reaction coordinate calculations and calculate the activation

barrier for the second reaction step. The activation barrier calcu-

lated at the MP2/6-3111G**:Amber//HF/3-21G*:Amber level

starting from the MD-simulated INT1 structure is 15.1 kcal/mol,

which is close to the activation barrier of 15.3 kcal/mol calcu-

lated at the same level starting from the X-ray crystal structure.

The close activation barrier values calculated by using different

starting structures suggest that the energetic results calculated in

this study are reliable.

The good agreement between the QM/MM-calculated activa-

tion barrier for the rate-determining step and the corresponding

experimental kinetic data suggests that the reaction pathway

identified in this study is reasonable and that the QM/MM proto-

col used is satisfactory. As the activation barrier calculated by

the QM/MM method accounting for the effects of protein envi-

ronment is �20 kcal/mol lower than the corresponding activa-

tion barrier calculated by the QM method neglecting the protein

environment, the protein environment stabilizes the rate-deter-

mining transition state TS2 more favorably than stabilizing the

intermediate INT1. In light of these new insights, it should be

very interesting to design stable analogs of the substructure of

transition state TS2. The substructure of transition state TS2

may include all atoms of pyruvate and ThDP and there is no

covalent bond between the substructure and the remaining part

of the protein. The stable analogs of the substructure are

expected to be novel, potent AHAS inhibitors that may be used

as promising new antituberculosis drugs, antibacterial drugs,

and/or herbicides to overcome the drug resistance problem.

Conclusions

This is the first computational study to uncover the detailed cata-

lytic mechanism for the common steps of AHAS-catalyzed con-

densation reactions of a-keto acids. The first-principles QM and

hybrid QM/MM reaction coordinate calculations have led us to

uncover the fundamental reaction pathway, determine the activa-

tion barriers, and obtain valuable insights concerning the specific

roles of several key amino acid residues for the common steps

of AHAS-catalyzed condensation reactions of a-keto acids. The

QM/MM reaction coordinate calculations have provided valuable

details concerning the reaction process and role of the protein

environment. The most important amino acid residues involved

in the catalysis include Glu1440, Gln2070, Gly1210, and Gly511;

these residues form favorable hydrogen bonds with the reaction

center (consisting of atoms from substrate pyruvate and cofactor

ThDP) during the reaction process to stabilize the transition

states. In addition, Glu1440 also accepts a proton from ThDP

through hydrogen bonding during the catalytic reaction process.

The optimized geometries of the transition states are qualita-

tively consistent with available experimental observations,

including data from site-directed mutagenesis, and provide more

detailed structural and mechanistic information for transition

states and their evolution during the key reaction steps. Com-

pared to the high activation barrier calculated for the model

Figure 4. QM/MM-optimized geometries of INT1 (A) and TS2 (B) for the reaction catalyzed by the

Glu144Ala mutant of A. thaliana AHAS II. The QM atoms used on the QM/MM calculations are

represented by the balls in the figure.



reaction system neglecting the protein environment, the favor-

able interactions between the reaction center and protein envi-

ronment remarkably stabilize the transition state and, thus, lower

the activation barrier for the rate-determining reaction step by

�20 kcal/mol. All of the computational results indicate that the

rate-determining step of the AHAS-catalyzed reactions is the

second reaction step and the activation barrier calculated for

the rate-determining step is in good agreement with the experi-

mentally derived activation barrier. The detailed structural and

mechanistic insights should be valuable for rational design of

novel, potent AHAS inhibitors hat may be used as promising

new anti-tuberculosis drugs, antibacterial drugs, and/or herbi-

cides to overcome the drug resistance problem.

Acknowledgment

The authors acknowledge the Center for Computational Sciences

(CCS) at University of Kentucky for supercomputing time on

IBM X-series Cluster with 340 nodes and 1,360 processors.

References

1. Singh, B. K.; Shaner, D. L. Plant Cell 1995, 7, 935.

2. Engel, S.; Vyazmensky, M.; Geresh, S.; Barak, Z.; Chipman, D. M.

Biotechnol Bioeng 2003, 83, 833.

3. Ito, T.; Nakashimada, Y.; Kakizono, T.; Nishio, N. J Biosci Bioeng

2004, 97, 227.

4. Choia, K.-J.; Yub, Y. G.; Hahnc, H. G.; Choid, J.-D.; Yoon, M.-Y.

FEBS Lett 2005, 579, 4903.

5. Boigegrain, R.-A.; Liautard, J.-P.; Kohler, S. Antimicrob Agents

Chemother, 2005, 49, 3922.

6. Duggleby, R. G.; Pang, S. S. J. Biochem Mol Biol 2000, 33, 1.

7. Bloom, B. R.; Murray, C. J. Science 1992, 257, 1055.

8. Guleria, I.; Teitelbaum, R.; McAdam, R. A.; Kalpana, G.; Jacobs,

W. R., Jr.; Bloom, B. R. Nat Med 1996, 2, 334.

9. Grandoni, J. A.; Marta, P. T.; Schloss, J. V. J Antimicrob Chemother

1998, 42, 475.

10. Zohar, Y.; Einav, M.; Chipman, D.M.; Barak, Z. Biochim Biophys

Acta 2003, 1649, 97.

11. Mazur, B. J. Falco, S. C. Annu Rev Plant Physiol Plant Mol Biol

1989, 40, 441.

12. Geier, P. W.; Stahlman, P. W.; Hargett, J. G. Weed Sci 2001, 49, 788.

13. Gerwick, B. C.; Subermanian, V. I.; Loney-Gallant, V. I.; Chander,

D. P. Pestic Sci 1990, 29, 357.

14. Shimizu, T.; Nakayama, I.; Nakao, T.; Nezu, Y.; Abe, H. J. Pestic

Sci 1994, 19, 59.

15. LaRossa, R. A.; Schloss, J. V. J Biol Chem 1984, 259, 8753.

16. Shaner, D. L.; Anderson, P. C.; Stidham, M. A. Plant Physiol 1984,

76, 545.

17. Tranel, P. J.; Wright, T. R. Weed Sci 2002, 50, 700.

18. McCourt, J. A.; Pang, S. S.; King-Scott, J.; Duggleby, R. G.;

Guddat, L. W. Proc Natl Acad Sci USA 2006, 103, 569.

19. Frank, R. A.; Titman, C. M.; Pratap, J. V.; Luisi, B. F.; Perham, R. N.

Science 2004, 306, 872.

20. Pang, S. S.; Duggleby, R. G.; Guddat, L. W. J Mol Biol 2002, 317,

249.

21. Pang, S. S.; Guddat, L. W.; Duggleby, R. G. J Biol Chem 2003,

278, 7639.

22. McCourt, J. A.; Pang, S. S.; Duggleby, R. G.; Guddat, L. W. Bio-

chemistry 2005, 44, 2330.

23. Breslow, R. J Am Chem Soc 1958, 80, 3719.

24. Nemeria, N.; Tittmann, K.; Joseph, E.; Zhou, L.; Vazquez-Coll, M.;

Arjunan, P.; Hubner, G.; Furey, W.; Jordan, F. J Biol Chem 2005,

280, 21473.

25. Tittmann, K.; Golbik, R.; Uhlemann, K.; Khailova, L.; Schneider,

G.; Patel, M.; Jordan, F.; Chipman, D. M.; Duggleby, R. G.; Hubner,

G. Biochemistry 2003, 42, 7885.

26. Tittmann, K.; Vyazmensky, M.; Hubner, G.; Barak, Z. Chipman, D. M.

Proc Natl Acad Sci USA 2005, 102, 553.

27. Becke, A. D. J Chem Phys 1993, 98, 5648.

28. Lee, C.; Yang, W.; Parr, R. G. Phys Rev B 1988, 37, 785.

29. Stephens, P. J.; Devlin, F. J.; Chabalowski, C. F.; Frisch, M. J.

J Phys Chem 1994, 98, 11623.

30. Gonzalez, C.; Schlegel, H. B. J Chem Phys 1989, 90, 2154.

31. Gonzalez, C.; Schlegel, H. B. J Phys Chem 1990, 94, 5523.

32. Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb,

M. A.; Cheeseman, J. R.; Montgomery, J. A., Jr.; Vreven, T.; Kudin,

K. N.; Burant, J. C.; Millam, J. M.; Iyengar, S. S.; Tomasi, J.; Bar-

one, V.; Mennucci, B.; Cossi, M.; Scalmani, G.; Rega, N.; Petersson,

G. A.; Nakatsuji, H.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.;

Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.;

Nakai, H.; Klene, M.; Li, X.; Knox, J. E.; Hratchian, H. P.; Cross,

J. B.; Adamo, C.; Jaramillo, J.; Gomperts, R.; Stratmann, R. E.;

Yazyev, O.; Austin, A. J.; Cammi, R.; Pomelli, C.; Ochterski, J. W.;

Ayala, P. Y.; Morokuma, K.; Voth, G. A.; Salvador, P.; Dannenberg,

J. J.; Zakrzewski, V. G.; Dapprich, S.; Daniels, A. D.; Strain, M. C.;

Farkas, O.; Malick, D. K.; Rabuck, A. D.; Raghavachari, K.; Fores-

man, J. B.; Ortiz, J. V.; Cui, Q.; Baboul, A. G.; Clifford, S.; Cio-

slowski, J.; Stefanov, B. B.; Liu, G.; Liashenko, A.; Piskorz, P.;

Komaromi, I.; Martin, R. L.; Fox, D. J.; Keith, T.; Al-Laham, M.

A.; Peng, C. Y.; Nanayakkara, A.; Challacombe, M.; Gill, P. M. W.;

Johnson, B.; Chen, W.; Wong, M. W.; Gonzalez, C.; Pople, J. A.

Gaussian 03, Revision B. 05, Gaussian: Pittsburgh, PA, 2003.

33. Case, D. A.; Darden, T. A.; Cheatham, T. E., III; Simmerling, C. L.;

Wang, J.; Duke, R. E.; Luo, R.; Merz, K. M.; Wang, B.; Pearlman,

D. A.; Crowley, M.; Brozell, S.; Tsui, V.; Gohlke, H.; Mongan, J.;

Hornak, V.; Cui, G.; Beroza, P.; Schafmeister, C.; Caldwell, J. W.;

Ross, W. S.; Kollman, P. A. AMBER 8; University of California:

San Francisco, 2004.

34. Zhang, Y.; Lee, T.; Yang, W. J Chem Phys 1999, 110, 46.

35. Zhang, Y. J Chem Phys 2005, 122, 024114.

36. Corminboeuf, C.; Hu, P.; Tuckerman, M. E.; Zhang, Y. J Am Chem

Soc 2006, 128, 4530.

37. Zhang, Y.; Liu, H.; Yang, W. J Chem Phys 2000, 112, 3483.

38. Hu, P.; Zhang, Y. J Am Chem Soc 2006, 128, 1272.

39. Zheng, F.; Yang, W.; Ko, M.-C.; Liu, J.; Cho, H.; Gao, D.; Tong, M.;

Tai, H.-H.; Woods, J. H.; Zhan, C.-G. J Am Chem Soc 2008, 130, 12148.

40. Williams, I. H.; Maggiora, G. M. Theochem 1982, 6, 365.

41. Zhang, Y.; Liu, H.; Yang, W. Ab Initio QM/MM and Free Energy

Calculations of Enzyme Reactions. In Computational Methods for

Macromolecular Modeling - Challenges and Applications; Schlick, T.;

Gan, H. H., Eds.; Springer-Verlag: New York, 2002; pp. 332–354.

42. Bar-Ilan, A.; Balan, V.; Tittmann, K.; Golbik, R.; Vyazmensky, M.;

Hubner, G.; Barak, Z.; Chipman, D.M. Biochemistry 2001, 40,

11946.

43. Kern, D.; Kern, G.; Neef, H.; Tittmann, K.; Killenberg-Jabs, M.;

Wickner, C.; Schneider, G.; Hubner, G. Science 1997, 275, 67.

44. Jordan, F.; Zhang, Z.; Sergienko, E. Bioorg Chem 2002, 30, 188.

45. Jordan, F. Nat Prod Rep 2003, 20, 184.

46. Nemeria, N.; Baykal, A.; Joseph, E.; Zhang, S.; Yan, Y.; Furey, W.;

Jordan, F. Biochemistry 2004, 43, 6565.

47. Dyda, F.; Furey, W.; Swaminathan, S.; Sax, M.; Farrenkopf, B.;

Jordan, F. Biochemistry 1993, 32, 6165.



48. Jordan, F.; Mariam, Y. F. J Am Chem Soc 1978, 100, 2534.

49. Lie, M. A.; Celik, L.; Jørgensen, K. A.; Schiøtt, B. Biochemistry

2005, 44, 14792.

50. Golbik, R.; Neef, H.; Hubner, G.; Konig, S.; Seliger, B.; Meshalkina,

L.; Kochetov, G. A.; Schellenberger, A. Bioorg Chem 1991, 19, 10.

51. Engel, S.; Vyazmensky, M.; Vinogradov, M.; Berkovich, D.;

Bar-Ilan, A.; Qimron, U.; Rosiansky, Y.; Barak, Z.; Chipman, D. M.

J Biol Chem 2004, 279, 24803.

52. Duggleby, R. G.; McCourt, J. A.; Guddat, L. W. Plant Physiol

Biochem 2008, 46, 309.

53. Zhao, Y.; Gonzlez-Garca, N.; Truhlar, D. G. J Phys Chem A 2005,

109, 2012.

54. Sousa, S. F.; Fernandes, P. A.; Ramos, M. J. J Phys Chem A, 2007,

111, 10439.

55. Alvarez-Idaboy, J. R.; Galano, A.; Bravo-Perez, G.; Ruiz, M. E.

J Am Chem Soc 2001, 123, 8387.

56. Pan, Y; Gao, D.; Zhan, C.-G. J Am Chem Soc 2008, 130, 5140.

57. Klahn, M.; Braun-Sand, S.; Rosta, E.; Warshel, A. J Phys Chem B

2005, 109, 15645.

58. Pan, Y.; Gao, D.; Yang, W.; Cho, H.; Yang, G.; Tai, H.-H.; Zhan,

C.-G. Proc Natl Acad Sci USA 2005, 102, 16656.

59. Xiong, Y.; Lu, H.; Zhan, C.-G. J Comput Chem 2008, 29, 1259.

60. Xiong, Y.; Lu, H.; Li, Y.; Yang, G.; Zhan, C.-G. Biophys J 2006,

91, 1858.



Documents

Computational determination of fundamental pathway and activation barriers for acetohydroxyacid synthase-catalyzed condensation reactions of α-keto acids