Premium
Modeling Complexes of Transmembrane Proteins: Systematic Analysis of ProteinProtein Docking Tools
Author(s) -
Kaczor Agnieszka A.,
Selent Jana,
Sanz Ferran,
Pastor Manuel
Publication year - 2013
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201200150
Subject(s) - docking (animal) , transmembrane protein , transmembrane domain , g protein coupled receptor , computational biology , membrane protein , rhodopsin , protein structure , protein–ligand docking , drug discovery , chemistry , computer science , biophysics , bioinformatics , virtual screening , biochemistry , biology , receptor , membrane , medicine , retinal , nursing
Proteinprotein docking methodology is frequently used to model complexes of transmembrane proteins, in particular oligomers of G protein‐coupled receptors (GPCRs), even if its applicability for these systems has never been fully validated. The aim of this work is to perform a systematic study on the suitability of some widely‐used proteinprotein docking software for modeling complexes of transmembrane proteins. In this study we tested the programs ZDOCK, ClusPro, HEX, GRAMM‐X, PatchDock, SymmDock, and HADDOCK, using a set of membrane protein oligomers for which the 3D structure has been obtained experimentally, including opsin dimer, the recently published chemokine CXCR4 and kappa opioid receptor dimers. The results show that the docking success depends on the applied docking algorithm and scoring functions, but also on inherent structural features of the transmembrane proteins. Thus, proteins with large interface surfaces, rich in surface cavities, high‐order symmetry, and small conformational change upon complex formation are well predicted more often than proteins without these features. The results of this systematic analysis provide guidelines that can be used for obtaining reliable models of transmembrane proteins, including GPCRs. Therefore they can be useful for the application of structure‐based methods in drug discovery projects involving these targets.