Inferring the microscopic surface energy of protein-protein interfaces from mutation data

被引:8
作者
Moal, Iain H. [1 ]
Dapkunas, Justas [2 ]
Fernandez-Recio, Juan [1 ]
机构
[1] BSC, Dept Life Sci, Joint BSC IRB Res Program Computat Biol, Barcelona 08034, Spain
[2] Vilnius Univ, Inst Biotechnol, LT-02241 Vilnius, Lithuania
关键词
protein-protein interactions; binding affinity; interaction energy; mutation; docking; hydrophobic effect; empirical modeling; CHAIN CONFORMATIONAL ENTROPY; COMPUTATIONAL DESIGN; BINDING-AFFINITY; HYDROPHOBIC PATCHES; DRIVING-FORCE; DOCKING; PREDICTION; SPECIFICITY; COMPLEX; PRINCIPLES;
D O I
10.1002/prot.24761
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Mutations at protein-protein recognition sites alter binding strength by altering the chemical nature of the interacting surfaces. We present a simple surface energy model, parameterized with empirical G values, yielding mean energies of -48 calmol(-1)angstrom(-2) for interactions between hydrophobic surfaces, -51 to -80 calmol(-1)angstrom(-2) for surfaces of complementary charge, and 66-83 calmol(-1)angstrom(-2) for electrostatically repelling surfaces, relative to the aqueous phase. This places the mean energy of hydrophobic surface burial at -24 calmol(-1)angstrom(-2). Despite neglecting configurational entropy and intramolecular changes, the model correlates with empirical binding free energies of a functionally diverse set of rigid-body interactions (r=0.66). When used to rerank docking poses, it can place near-native solutions in the top 10 for 37% of the complexes evaluated, and 82% in the top 100. The method shows that hydrophobic burial is the driving force for protein association, accounting for 50-95% of the cohesive energy. The model is available open-source from and via the CCharpPPI web server . Proteins 2015; 83:640-650. (c) 2015 Wiley Periodicals, Inc.
引用
收藏
页码:640 / 650
页数:11
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