Methods for protein complex prediction and their contributions towards understanding the organisation, function and dynamics of complexes

摘要

Complexesofphysicallyinteractingproteinsconstitutefundamentalfunctionalunitsresponsiblefordrivingbiologicalprocesseswithincells.Afaithfulreconstructionoftheentiresetofcomplexesisthereforeessentialtounderstandthefunctionalorganisationofcells.Inthisreview,wediscussthekeycontributionsofcomputationalmethodsdevelopedtilldate(approximatelybetween2003and2015)foridentifyingcomplexesfromthenetworkofinteractingproteins(PPInetwork).WeevaluateindepththeperformanceofthesemethodsonPPIdatasetsfromyeast,andhighlighttheirlimitationsandchallenges,inparticularatdetectingsparseandsmallorsub‐complexesanddiscerningoverlappingcomplexes.Wedescribemethodsforintegratingdiverseinformationincludingexpressionprofilesand3DstructuresofproteinswithPPInetworkstounderstandthedynamicsofcomplexformation,forinstance,oftime‐basedassemblyofcomplexsubunitsandformationoffuzzycomplexesfromintrinsicallydisorderedproteins.Finally,wediscussmethodsforidentifyingdysfunctionalcomplexesinhumandiseases,anapplicationthatisprovinginvaluabletounderstanddiseasemechanismsandtodiscovernoveltherapeutictargets.Wehopethisreviewaptlycommemoratesadecadeofresearchoncomputationalpredictionofcomplexesandconstitutesavaluablereferenceforfurtheradvancementsinthisexcitingarea...