Multiscale Approaches to Protein Modeling: Structure Prediction, Dynamics, Thermodynamics and Macromolecular Assemblies

359 Pages·2011·7.748 MB·English

by  Andrzej Kolinski (auth.), Andrzej Kolinski (eds.)

Multiscale Approaches to Protein Modeling
Andrzej Kolinski
Editor
Multiscale Approaches
to Protein Modeling
123
Editor
AndrzejKolinski
DepartmentofChemistry
UniversityofWarsaw
ul.Pasteura1
02-093Warszawa
Poland
[email protected]
ISBN978-1-4419-6888-3 e-ISBN978-1-4419-6889-0
DOI10.1007/978-1-4419-6889-0
SpringerNewYorkDordrechtHeidelbergLondon
LibraryofCongressControlNumber:2010934732
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Preface
Thanks to enormous progress in sequencing of genomic data, presently we know
millions of protein sequences. At the same time the number of experimentally
solved protein structures is much smaller, ca. 60,000. This is because of large
cost of structure determination. Thus, the theoretical in silico prediction of pro-
tein structures and dynamics is essential for understanding the molecular basis of
drug action, metabolic and signaling pathways in living cells, and designing new
technologiesinthelifescienceandmaterialsciences.Unfortunately,a“bruteforce”
approachremainsimpractical.Foldingofatypicalprotein(invivoorinvitro)takes
milliseconds to minutes, while the state-of-the-art all-atom molecular mechanics
simulations of protein systems can cover only a time period of nanoseconds to
microseconds. This is the reason for the enormous progress in the development
of various multiscale modeling techniques applied to protein structure prediction,
modeling of protein dynamics and folding pathways, in silico protein engineer-
ing,model-aidedinterpretationofexperimentaldata,modelingofmacromolecular
assemblies,and theoretical studies of protein thermodynamics. Coarse-graining of
the proteins’ conformational space is a common feature of all these approaches,
althoughthedetailsandtheunderlyingphysicalmodelsspanaverybroadspectrum.
This book contains comprehensive reviews of the most advanced multiscale
modelingmethodsinproteinstructureprediction,computationalstudiesofprotein
dynamics, folding mechanisms, and macromolecular interactions. The presented
approachesspanawiderangeofthelevelsofcoarse-grainedrepresentations,vari-
oussamplingtechniques,andavarietyofapplicationstobiomedicalandbiophysical
problems.Itwasourintentiontoprovideacollectionofcomprehensivereviewsthat
couldbeusedasareferencebookforthosewhojustarebeginningtheiradventure
with biomacromolecular modeling but also as a valuable source of more detailed
information for those who are already experts in the field of biomacromolecular
modelingandinrelatedareasofcomputationalbiologyorbiophysics.
Proteins are linear copolymers composed of amino acids. Important ideas
of polymer physics inspired the field of protein modeling. Chapter 1 explains
some basic concepts of polymer conformational statistics and dynamics of chain
molecules in context of simple lattice models. This chapter demonstrates how
v
vi Preface
these ideas could be employed in protein modeling. Chapter 2 describes applica-
tion of a lattice-based protein model to the very challenging problem of protein
docking. Chapter 3 provides a comprehensive overview of various coarse-grained
protein-like and protein models. This chapter describes (among other approaches)
probablythemostrigoroussystemofphysics-basedreducedmodelingofproteins.
Coarse-grained,multiscale,proteinmodelingrequiresspecificdesignsofinteraction
schemes.Chapters4–6providein-depthoverviewsofvariouslevelforce-fieldsfor
thereducedrepresentationsofproteinconformationalspace,includingknowledge-
basedstatisticalpotentials.Chapters7and8(butalso,inpart,Chapters3–5and12)
describeavarietyofapplicationsofreducedmodelsinthestudyofproteindynam-
ics,foldingpathways,molecularmechanismsofmechanicalunfolding,andprotein
interactions.Chapter9givesanoverviewofthemosteffectivesamplingstrategiesin
areduced,althoughunrestrictedconformationalspace.Chapters10and11present
a very efficient philosophy of a conformational search, where the target structures
areassembledfromfragmentsexcisedfromalreadyknownproteinstructures.These
strategiesproventobeveryeffectiveinthelarge-scale,automatedinsilicostructure
prediction. Chapter 12 describes a multiscale method, based on a high-resolution
lattice model, for modeling protein folding pathways. Chapters 13 and 14 discuss
themostimportantideasandtechniquesofcomparativemodeling–themosteffec-
tive and the most popular method for theoretical prediction of protein structures.
Thesechaptersprovidealsoreviewsofthemodel-qualityassessmentmethods.
The contributing authors are world-wide recognized experts. Some of them
(Bujnicki and Zhang) are leaders in the field of protein structure prediction, as
assessed by the recent (CASP6–CASP8) community-wide experiments in a blind
structure prediction. Others also developed very successful methods for the pro-
teinstructureprediction(Scheraga,Liwo,Feig,andKihara).Severaloftheauthors
ofthisbookdevelopedveryefficientcoarse-grainedinteractionschemesforprotein
modelsbasedoneitheranevolutionaryknowledgeapproach(JerniganandScheraga
have built theoretical foundations of this class of approaches, but others also con-
tributedsignificantly:FeigandMicheletti)oraphysics-basedapproach(Scheraga,
Liwo, Feig, and Irback). Among the authors are also the world top leaders of
comparative modeling (Bujnicki, Zhang, Tramontano, and Kihara) and automated
structure prediction (Zhang and Bujnicki) – the structure prediction server created
by Zhang is the best till date. The book presents also the state-of-the-art methods
ofevaluationofqualityofthetheoreticalproteinmodels(TramontanoandKihara).
Recently, a significant progress has been achieved in multiscale modeling of pro-
tein dynamics and folding mechanisms. The authors of the chapters dealing with
this class of problems are also world-class leaders (Scheraga, Liwo, Irback, Feig,
Cieplak,Jernigan,andMicheletti).Theconformationalsearchstrategiesarecrucial
inproteinmodeling.Developersofthemostefficientcomputationaltechniquesand
strategiesarealsoamongtheauthors(Hansmann,Scheraga,andothers).
Warsaw,Poland AndrzejKolinski
Contents
1 LatticePolymersandProteinModels . . . . . . . . . . . . . . . . 1
AndrzejKolinski
2 MultiscaleProteinandPeptideDocking. . . . . . . . . . . . . . . 21
MateuszKurcinski,MichałJamroz,andAndrzejKolinski
3 Coarse-GrainedModelsofProteins:
TheoryandApplications . . . . . . . . . . . . . . . . . . . . . . . 35
CezaryCzaplewski,AdamLiwo,MariuszMakowski,
StanisławOłdziej,andHaroldA.Scheraga
4 ConformationalSamplinginStructurePredictionand
RefinementwithAtomisticandCoarse-GrainedModels. . . . . . 85
MichaelFeig,SrinivasaM.Gopal,KanagasabaiVadivel,
andAndrewStumpff-Kane
5 EffectiveAll-AtomPotentialsforProteins. . . . . . . . . . . . . . 111
AndersIrbäckandSandipanMohanty
6 StatisticalContactPotentialsinProteinCoarse-Grained
Modeling:FromPairtoMulti-bodyPotentials . . . . . . . . . . . 127
SumuduP.Leelananda,YapingFeng,PawelGniewek,
AndrzejKloczkowski,andRobertL.Jernigan
7 BridgingtheAtomicandCoarse-GrainedDescriptionsof
CollectiveMotionsinProteins . . . . . . . . . . . . . . . . . . . . 159
VincenzoCarnevale,CristianMicheletti,
FrancescoPontiggia,andRaffaelloPotestio
8 Structure-BasedModelsofBiomolecules:Stretchingof
Proteins,DynamicsofKnots,HydrodynamicEffects,and
IndentationofVirusCapsids . . . . . . . . . . . . . . . . . . . . . 179
MarekCieplakandJoannaI.Sułkowska
9 SamplingProteinEnergyLandscapes–TheQuestfor
EfficientAlgorithms . . . . . . . . . . . . . . . . . . . . . . . . . . 209
UlrichH.E.Hansmann
vii
viii Contents
10 Protein Structure Prediction: From Recognition
of Matches with Known Structures
toRecombinationofFragments . . . . . . . . . . . . . . . . . . . 231
MichalJ.Gajda,MarcinPawlowski,andJanuszM.Bujnicki
11 Genome-WideProteinStructurePrediction . . . . . . . . . . . . 255
SrayantaMukherjee,AndrasSzilagyi,AmbrishRoy,
andYangZhang
12 MultiscaleApproachtoProteinFoldingDynamics . . . . . . . . . 281
SebastianKmiecik,MichałJamroz,andAndrzejKolinski
13 ErrorEstimationofTemplate-BasedProteinStructureModels . . 295
DaisukeKihara,YifengDavidYang,andHaoChen
14 Evaluation of Protein Structure Prediction Methods:
IssuesandStrategies . . . . . . . . . . . . . . . . . . . . . . . . . 315
AnnaTramontanoandDomenicoCozzetto
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341
Contributors
JanuszM.BujnickiLaboratoryofBioinformaticsandProteinEngineering,
InternationalInstituteofMolecularandCellBiology,Warsaw,Poland;Laboratory
ofBioinformatics,InstituteofMolecularBiologyandBiotechnology,Facultyof
Biology,AdamMickiewiczUniversity,Poznan,Poland,[email protected]
VincenzoCarnevaleInstituteforComputationalMolecularScience,Temple
University,Philadelphia,PA,USA,[email protected]
HaoChenDepartmentofBiologicalSciences,CollegeofScience,Purdue
University,WestLafayette,IN,USA,[email protected]
MarekCieplakInstituteofPhysics,PolishAcademyofSciences,Warsaw,
Poland,[email protected]
DomenicoCozzettoDepartmentofBiochemicalSciences,“Sapienza”University
ofRome,Rome,Italy,[email protected]
CezaryCzaplewskiFacultyofChemistry,UniversityofGdan´sk,Gdan´sk,
Poland;BakerLaboratoryofChemistryandChemicalBiology,CornellUniversity,
Ithaca,NY,USA,[email protected]
MichaelFeigDepartmentofBiochemistryandMolecularBiology,MichiganState
University,EastLansing,MI,USA;DepartmentofChemistry,MichiganState
University,EastLansing,MI,USA,[email protected]
YapingFengDepartmentofBiochemistry,Biophysics,andMolecularBiology,
IowaStateUniversity,Ames,IA,USA;L.H.BakerCenterforBioinformaticsand
BiologicalStatistics,IowaStateUniversity,Ames,IA,USA,[email protected]
MichalJ.GajdaEuropeanMolecularBiologyLaboratories,HamburgOutstation,
Hamburg,Germany,[email protected]
PawelGniewekL.H.BakerCenterforBioinformaticsandBiologicalStatistics,
IowaStateUniversity,Ames,IA,USA;LaboratoryofTheoryofBiopolymers,
FacultyofChemistry,UniversityofWarsaw,Warsaw,Poland,
[email protected]
ix
x Contributors
SrinivasaM.GopalDepartmentofBiochemistryandMolecularBiology,
MichiganStateUniversity,EastLansing,MI,USA,[email protected]
UlrichH.E.HansmannDepartmentofPhysics,MichiganTechnological
University,Houghton,MI,USA,[email protected]
AndersIrbäckComputationalBiology&BiologicalPhysics,Departmentof
TheoreticalPhysics,LundUniversity,Lund,Sweden,[email protected]
MichałJamrozFacultyofChemistry,UniversityofWarsaw,Warsaw,Poland,
[email protected]
RobertL.JerniganDepartmentofBiochemistry,Biophysics,andMolecular
Biology,IowaStateUniversity,Ames,IA,USA;L.H.BakerCenterfor
BioinformaticsandBiologicalStatistics,IowaStateUniversity,Ames,IA,USA,
[email protected]
DaisukeKiharaDepartmentofBiologicalSciences,CollegeofScience;
DepartmentofComputerScience,CollegeofScience;MarkeyCenterfor
StructuralBiology,PurdueUniversity,WestLafayette,IN,USA,
[email protected]
AndrzejKloczkowskiDepartmentofBiochemistry,Biophysics,andMolecular
Biology,IowaStateUniversity,Ames,IA,USA;L.H.BakerCenterfor
BioinformaticsandBiologicalStatistics,IowaStateUniversity,Ames,IA,USA,
[email protected]
SebastianKmiecikFacultyofChemistry,UniversityofWarsaw,Warsaw,Poland,
[email protected]
AndrzejKolinskiFacultyofChemistry,UniversityofWarsaw,Warsaw,Poland,
[email protected]
MateuszKurcinskiFacultyofChemistry,UniversityofWarsaw,Warsaw,Poland,
[email protected]
SumuduP.LeelanandaDepartmentofBiochemistry,Biophysics,andMolecular
Biology,IowaStateUniversity,Ames,IA,USA;L.H.BakerCenterfor
BioinformaticsandBiologicalStatistics,IowaStateUniversity,Ames,IA,USA,
[email protected]
AdamLiwoFacultyofChemistry,UniversityofGdan´sk,Gdan´sk,Poland;Baker
LaboratoryofChemistryandChemicalBiology,CornellUniversity,Ithaca,NY,
USA,[email protected]
MariuszMakowskiFacultyofChemistry,UniversityofGdan´sk,Gdan´sk,
Poland;BakerLaboratoryofChemistryandChemicalBiology,CornellUniversity,
Ithaca,NY,USA,[email protected]
Contributors xi
CristianMichelettiScuolaInternazionaleSuperiorediStudiAvanzati,Trieste,
Italy;DemocritosCNR-IOMandItalianInstituteofTechnology(SISSAUnit),
Trieste,Italy,[email protected]
SandipanMohantyJülichSupercomputingCentre,ForschungszentrumJülich
GmbH,Jülich,Germany,[email protected]
SrayantaMukherjeeCenterforComputationalMedicineandBioinformatics,
UniversityofMichigan,AnnArbor,MI,USA;CenterforBioinformatics,
UniversityofKansas,Lawrence,KS,USA,[email protected]
StanisławOłdziejBakerLaboratoryofChemistryandChemicalBiology,Cornell
University,Ithaca,NY,USA;LaboratoryofBiopolymerStructure,Intercollegiate
FacultyofBiotechnology,UniversityofGdan´skandMedicalUniversityof
Gdan´sk,Gdan´sk,Poland,[email protected]
MarcinPawlowskiLaboratoryofBioinformaticsandProteinEngineering,
InternationalInstituteofMolecularandCellBiology,Warsaw,Poland,
[email protected]
FrancescoPontiggiaDepartmentofBiochemistry,BrandeisUniversity,Waltham,
MA,USA,[email protected]
RaffaelloPotestioScuolaInternazionaleSuperiorediStudiAvanzati,Trieste,
Italy,[email protected]
AmbrishRoyCenterforComputationalMedicineandBioinformatics,University
ofMichigan,AnnArbor,MI,USA;CenterforBioinformatics,Universityof
Kansas,Lawrence,KS,USA,[email protected]
HaroldA.ScheragaBakerLaboratoryofChemistryandChemicalBiology,
CornellUniversity,Ithaca,NY,USA,[email protected]
AndrewStumpff-KaneDepartmentofBiochemistryandMolecularBiology,
MichiganStateUniversity,Michigan,USA,[email protected]
JoannaI.SułkowskaInstituteofPhysics,PolishAcademyofSciences,Warsaw,
Poland;CTBP,UniversityofCalifornia,GilmanDrive9500,LaJolla,SanDiego,
CA,USA,[email protected]
AndrasSzilagyiCenterforBioinformatics,UniversityofKansas,Lawrence,KS,
USA;InstituteofEnzymology,BRC,HungarianAcademyofSciences,Budapest,
Hungary,[email protected]
AnnaTramontanoDepartmentofBiochemicalSciences,“Sapienza”University
ofRome,Rome,Italy;IstitutoPasteur–FondazioneCenciBolognetti,“Sapienza”
UniversityofRome,Rome,Italy,[email protected]
KanagasabaiVadivelDepartmentofBiochemistryandMolecularBiology,
MichiganStateUniversity,EastLansing,MI,USA,[email protected]