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Potential of mean force for protein–protein interaction studies
Author(s) -
Jiang Lin,
Gao Ying,
Mao Fenglou,
Liu Zhijie,
Lai Luhua
Publication year - 2001
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.10031
Subject(s) - hydrogen bond , binding energy , protein data bank (rcsb pdb) , chemistry , protein–protein interaction , interaction energy , protein data bank , force field (fiction) , statistical potential , protein structure , crystallography , bioinformatics , computational chemistry , physics , protein structure prediction , atomic physics , biology , molecule , biochemistry , quantum mechanics , organic chemistry
Calculating protein–protein interaction energies is crucial for understanding protein–protein associations. On the basis of the methodology of mean‐field potential, we have developed an empirical approach to estimate binding free energy for protein–protein interactions. This knowledge‐based approach has been used to derive distance‐dependent free energies of protein complexes from a nonredundant training set in the Protein Data Bank (PDB), with a careful treatment of homology. We calculate atom pair potentials for 16 pair interactions, which can reflect the importance of hydrophobic interactions and specific hydrogen‐bonding interactions. The derived potentials for hydrogen‐bonding interactions show a valley of favorable interactions at a distance of ≈3 Å, corresponding to that of an established hydrogen bond. For the test set of 28 protein complexes, the calculated energies have a correlation coefficient of 0.75 compared with experimental binding free energies. The performance of the method in ranking the binding energies of different protein–protein complexes shows that the energy estimation can be applied to value binding free energies for protein–protein associations. Proteins 2002;46:190–196. © 2001 Wiley‐Liss, Inc.