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Surface‐histogram: A new shape descriptor for protein‐protein docking
Author(s) -
Gu Shengyin,
Koehl Patrice,
Hass Joel,
Amenta Nina
Publication year - 2012
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.23192
Subject(s) - docking (animal) , macromolecular docking , histogram , surface protein , protein structure , computer science , protein–ligand docking , algorithm , biological system , artificial intelligence , mathematics , chemistry , biology , virtual screening , computational chemistry , biochemistry , molecular dynamics , medicine , nursing , virology , image (mathematics)
Determining the structure of protein–protein complexes remains a difficult and lengthy process, either by NMR or by X‐ray crystallography. Several computational methods based on docking have been developed to support and even serve as possible alternatives to these experimental methods. In this article, we introduce a new protein–protein docking algorithm, shDock, based on shape complementarity. We characterize the local geometry on each protein surface with a new shape descriptor, the surface‐histogram. We measure the complementarity between two surface‐histograms, one on each protein, using a modified Manhattan distance. When a match is found between two local protein surfaces, a model is generated for the protein complex, which is then scored by checking for collision between the two proteins. We have tested our algorithm on Version 3 of the ZDOCK protein–protein docking benchmark. We found that for 110 out of the 124 test cases of bound docking in the benchmark, our algorithm was able to generate a model in the top 3600 candidates for the protein complex within an root‐mean‐square deviation of 2.5 Å from its native structure. For unbound docking predictions, we found a model within 2.5 Å in the top 3600 models in 54 out of 124 test cases. A comparison with other shape‐based docking algorithms demonstrates that our approach gives significantly improved performance for both bound and unbound docking test cases. Proteins 2012; © 2011 Wiley Periodicals, Inc.