LIBSA – A Method for the Determination of Ligand-Binding Preference to Allosteric Sites on Receptor Ensembles
Author(s) -
Harrison J. Hocker,
Nandini Rambahal,
Alemayehu A. Gorfe
Publication year - 2014
Publication title -
journal of chemical information and modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.24
H-Index - 160
eISSN - 1549-960X
pISSN - 1549-9596
DOI - 10.1021/ci400474u
Subject(s) - allosteric regulation , docking (animal) , binding site , chemistry , ligand (biochemistry) , drug discovery , computational biology , protein–ligand docking , ranking (information retrieval) , searching the conformational space for docking , binding pocket , computer science , virtual screening , receptor , artificial intelligence , biology , biochemistry , medicine , nursing
Incorporation of receptor flexibility into computational drug discovery through the relaxed complex scheme is well suited for screening against a single binding site. In the absence of a known pocket or if there are multiple potential binding sites, it may be necessary to do docking against the entire surface of the target (global docking). However no suitable and easy-to-use tool is currently available to rank global docking results based on the preference of a ligand for a given binding site. We have developed a protocol, termed LIBSA for LIgand Binding Specificity Analysis, that analyzes multiple docked poses against a single or ensemble of receptor conformations and returns a metric for the relative binding to a specific region of interest. By using novel filtering algorithms and the signal-to-noise ratio (SNR), the relative ligand-binding frequency at different pockets can be calculated and compared quantitatively. Ligands can then be triaged by their tendency to bind to a site instead of ranking by affinity alone. The method thus facilitates screening libraries of ligand cores against a large library of receptor conformations without prior knowledge of specific pockets, which is especially useful to search for hits that selectively target a particular site. We demonstrate the utility of LIBSA by showing that it correctly identifies known ligand binding sites and predicts the relative preference of a set of related ligands for different pockets on the same receptor.
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