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Automatic identification and representation of protein binding sites for molecular docking
Author(s) -
Ruppert Jim,
Welch Will,
Jain Ajay N.
Publication year - 1997
Publication title -
protein science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.353
H-Index - 175
eISSN - 1469-896X
pISSN - 0961-8368
DOI - 10.1002/pro.5560060302
Subject(s) - docking (animal) , protein–ligand docking , searching the conformational space for docking , target protein , binding site , chemistry , ligand (biochemistry) , small molecule , drug discovery , protein ligand , affinities , computational biology , plasma protein binding , biophysics , stereochemistry , virtual screening , biochemistry , biology , receptor , medicine , nursing , gene
Abstract Molecular (locking is a popular way to screen for novel drug compounds. The method involves aligning small molecules to a protein structure and estimating their binding affinity. To do this rapidly for tens of thousands of molecules requires an effective representation of the binding region of the target protein. This paper presents an algorithm for representing a protein's binding site in a way that is specifically suited to molecular docking applications. Initially, the protein's surface is coated with a collection of molecular fragments that could potentially interact with the protein. Each fragment, or probe, serves as a potential alignment point for atoms in a ligand, and is scored to represent that probe's affinity for the protein. Probes are then clustered by accumulating their affinities, where high affinity clusters are identified as being the “stickiest” portions of the protein surface. The stickiest cluster is used as a computational binding “pocket” for docking. This method of site identification was tested on a number of ligand‐protein complexes; in each case the pocket constructed by the algorithm coincided with the known ligand binding site. Successful docking experiments demonstrated the effectiveness of the probe representation.