COMPARATIVE MOLECULAR DYNAMICS COMPARATIVE MOLECULAR DYNAMICS SIMULATIONS TO STUDY ENZYMATIC SIMULATIONS TO STUDY ENZYMATIC

COLD ADAPTATIONCOLD ADAPTATION

Luca De GioiaLuca De GioiaMolecular Modeling Laboratory,

Department of Biotechnology and Biosciences, University of Milano-Bicocca,

Italy

PSYCHROPHILIC ORGANISMSPSYCHROPHILIC ORGANISMS

PSYCHROPHILIC ENZYMESPSYCHROPHILIC ENZYMES: catalysis in extreme : catalysis in extreme conditionsconditions

rational design of biocatalysts and biotechnological rational design of biocatalysts and biotechnological applicationsapplications

• ARCTIC AND ANTARCTICARCTIC AND ANTARCTIC

½ Earth’s surface: oceans 1°C - 4°C½ Earth’s surface: oceans 1°C - 4°C

Deep sea – 1°C to 4°CDeep sea – 1°C to 4°C

Georlette et al, FEMS Microbiol. Rev., 28 (2004) 25.

PSYCHROPHILIC ENZYMES: PSYCHROPHILIC ENZYMES: an OVERVIEWan OVERVIEW

HIGH CATALYTIC HIGH CATALYTIC EFFICIENCYEFFICIENCY at 0-30°C

THERMOLABILITYTHERMOLABILITY

STRUCTURAL FLEXIBILITY ?STRUCTURAL FLEXIBILITY ?

• fewer intramolecular interactions

• more PROTEIN-SOLVENT interactions

Georlette et al, FEMS Microbiol. Rev., 28 (2004) 25.

A general theory of enzymatic cold adaptation cannot A general theory of enzymatic cold adaptation cannot be formulated because… be formulated because…

Cold adaptation in different families is most probably Cold adaptation in different families is most probably obtained byobtained by different different EVOLUTIONARY STRATEGIESEVOLUTIONARY STRATEGIES

COMPARATIVE and COMPARATIVE and STATISTICAL STATISTICAL

INVESTIGATIONSINVESTIGATIONS

• general features

• overlooking subtle structural modifications

Gianese, G., Bossa, F., Pascarella, S., Proteins, 47 (2002) 236.

Detailed INTRA-FAMILY structural comparisons

Molecular dynamics

Proteins are not rigid molecules• Conformational changes• Protein folding• Molecular recognition (drug design)• Ion transport

iii amF

VF ii

2

2

dt

rdm

dr

dV ii

i

The method is based on the Newton’s equation of motion:

•(Numerical) integration of the equation of motion yields a trajectory. •The average values of properties can be determined from the trajectory

MD shortcomings

• The integration step (dt) must be very small (1fs) [supercomputingsupercomputing]

• The trajectory must be very long (to compute properties the simulation must pass through all possible states corresponding to the particular thermodynamic constraints) [supercomputingsupercomputing]

MD protocolMD protocol

Multiple MD SIMULATIONS: Gromacs (50 ns, explicit solvent)

To properly sample the phase space:

•Rmsd (mainchain)N = number of atomsr = position; r0 = initial position

Up to 10 ns

20

1

)(1

rrN

rmsdN

ii

MD protocolMD protocol

•Protein gyration radius•Total and potential energy

Elastases (serine protaeses)Elastases (serine protaeses) 3D STRUCTURE3D STRUCTURE: 2 DOMAINS : 2 DOMAINS antiparallel antiparallel ββ-type fold-type fold ( (12 12 ββ-strands -strands

and 3 and 3 αα-helices).-helices).

COLD-ADAPTED COLD-ADAPTED == atlantic atlantic salmon elastase salmon elastase (SE)(SE)

MESOPHILIC MESOPHILIC == porcine elastase porcine elastase (PE)(PE)

FUNCTIONAL SITESFUNCTIONAL SITES: catalytic : catalytic triad triad (H57, D102 and S195)(H57, D102 and S195) and and

specificity pocket specificity pocket

Psychrophile/Mesophile comparison:Psychrophile/Mesophile comparison: primary primary sequencessequences

Primary sequence Primary sequence (PE and (PE and SE, SE, ~ 210-250 aa~ 210-250 aa ): 68.2% ): 68.2%

identityidentity

76 amino acidic 76 amino acidic substitutionssubstitutions (45 completely (45 completely

unrelated aa).unrelated aa).

Maiale VVGGTEAQRNSWPSQISLQYRSGSSWAHTCGGTLIRQNWVMTAAHCVDRELTFRVVVGEHBovina VVGGTAVSKNSWPSQISLQYKSGSSWYHTCGGTLIKQKWVMTAAHCVDSQMTFRVVLGDHMerluzzoB VVGGEDVRVHSWPWQASLQYKSGNSFYHTCGGTLIAPQWVMTAAHCIGSR-TYRVLLGKHSalmone VVGGRVAQPNSWPWQISLQYKSGSSYYHTCGGSLIRQGWVMTAAHCVDSARTWRVVLGEH **.* . ::** * *** .. : *.***:*: **:*****:. :** :* * Maiale NLNQ-NNGTEQYVGVQKIVVHPYWNTDDVAAGYDIALLRLAQSVTLNSYVQLGVLPRAGTBovina NLSQ-NDGTEQYISVQKIVVHPSWNSNNVAAGYDIAVLRLAQSATLNSYVQLGVLPQSGTMerluzzoB NMQDYNEAGSLAISPAKIIVHEKWD—-SSRIRNDIALIKLASPVDVSAIITPACVPDAEVSalmone NLNT-NEGKEQIMTVNSVFIHSGWNSDDVAGGYDIALLRLNTQASLNSAVQLAALPPSNQ .: : .:.:* *: *:*:::: . . : . :*  Maiale ILANNSPCYITGWGLTRTNGQLAQTLQQAYLPTVDYAICSSSSYWGSTVKNSMVCAGGDGBovina ILANNTPCYITGWGRTKTNGQLAQTLQQAYLPSVDYATCSSSSYWGSTVKTTMVCAGGDGMerluzzoB LLANGAPCYVTGWGRLWTGGPIADALQQALLPVVDHAHCSRYDWWGSLVTTSMVCAGGDGSalmone ILPNNNPCYITGWGKTSTGGPLSDSLKQAWLPSVDHATCSSSGWWGSTVKTTMVCAGG-G :*.. **:**** *.* . *:*. : .: ** :*** : . *:*.** *

Comparative molecular dynamics (MD) Comparative molecular dynamics (MD) simulationssimulations

Comparative MD simulationsComparative MD simulations of proteins of proteins

•TIME-EVOLUTION of MOLECULAR PROPERTIES

• evaluation of PROTEIN FLEXIBILITY

Molecular flexibilityMolecular flexibility is difficult to estimate experimentally is difficult to estimate experimentally but possiblybut possibly crucial to understand cold-adaptation crucial to understand cold-adaptation

Analysis of MD trajectoriesAnalysis of MD trajectories

Secondary Structure (SS) Secondary Structure (SS) contentcontent

Hydrogen bondsHydrogen bonds

Solvent accessible Solvent accessible surfacesurface

Psychrophile/Mesophile comparison:Psychrophile/Mesophile comparison: flexibilityflexibility

Root mean square Root mean square fluctuation fluctuation (Rmsf)(Rmsf) profiles: highlight profiles: highlight

STRUCTURAL STRUCTURAL FLEXIBILITYFLEXIBILITY..

• IdentificationIdentification of regions characterized by of regions characterized by different flexibilitydifferent flexibility in SE and PEin SE and PE

2

1

)(1

rrN

rmsfN

ii

N = number of atomsr = position; <r> = average position

Psychrophile/Mesophile comparisonPsychrophile/Mesophile comparison

Differences Differences that could be relatedthat could be related to cold adaptation to cold adaptation

Different RMSFDifferent RMSF Amino acid COMPOSITIONAmino acid COMPOSITION LOCALIZATION on the 3D structureLOCALIZATION on the 3D structure

SESE PEPE

Insight obtained by MD simulations

• COLD-ADAPTED ELASTASES:COLD-ADAPTED ELASTASES: localized localized flexibility (proximity of catalytic flexibility (proximity of catalytic site/specificity pocket). site/specificity pocket).

• MESOPHILIC ELASTASES:MESOPHILIC ELASTASES: scattered scattered flexibility (far from protein functional flexibility (far from protein functional sites).sites).

Papaleo, E., Fantucci, P., De Gioia L., J. Chem. Theory Comput., 1 (2005) 1286.

Design of “wet” experiments: site-directed mutagenesisDesign of “wet” experiments: site-directed mutagenesis

Trypsins (serine proteases)• Specific for peptide cleavage at Lys and Arg

sites• Bind a Ca2+ ion

• Factors regulating autoproteolysis (genetic disorders)

MD investigation

• Bovine and salmon trypsins• Apo and holo forms• Multiple MD simulations: ~ 200 ns

Role of Ca2+ in structure stabilization and autolysis?

- The region K60-R117 (including the Ca2+

binding loop) can be a target for autolysis.- Ca2+ has been proposed to induce an autolysis-resistant conformation- Autolysis in fish trypsins is less Ca2+ dependent

Investigation of autoproteolysis sites

• Effects due to Ca removal Flexibility of R117 and K188 is enhanced

in BT

Insight from MD simulations

• Ca2+ removal increases the flexibility of residues forming the binding site, but…

• …it also leads to enhanced flexibility in remote regions

• Ca2+ affects the flexibility of some autolysis sites in bovine trypsin but not in salmon trypsin (experimental data)

Papaleo E., Riccardi L., Villa C., Fantucci P., De Gioia L., Biochim. Biophys. Acta, 1764 (2006) 1397.

Design of “wet” experiments: site-directed mutagenesisDesign of “wet” experiments: site-directed mutagenesis

AcknowledgmentsAcknowledgments

Department of Biotechnology and

Biosciences, University of Milano-Bicocca, Milano, Italy

• Elena Papaleo

• Prof. Piercarlo Fantucci

• Chiara Villa, Laura Riccardi, Marco Pasi, Rodolfo Gonella Diaza, Paolo Mereghetti, Gianluca Santarossa

Department of Biochemistry,

University La Sapienza, Roma, Italy

• Prof. Stefano Pascarella

• Giulio Gianese

• Daniele Tronelli

Norwegian Structural Biology Centre, Tromso University,

Tromso, Norway

• Prof. Arne Smalas

• Bjorn Bransdal

• Magne Olufsen