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Automatic identification and representation of protein binding sites for molecular docking

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 t...

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Bibliographic Details
Published in:Protein science 1997-03, Vol.6 (3), p.524-533
Main Authors: Ruppert, Jim, Welch, Will, Jain, Ajay N.
Format: Article
Language:English
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Summary: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.
ISSN:0961-8368
1469-896X
DOI:10.1002/pro.5560060302