Identification of binding sites and favorable ligand binding moieties by virtual screening and self-organizing map analysis.

ABSTRACT:

Background

Identifying druggable cavities on a protein surface is a crucial step in structure based drug design. The cavities have to present suitable size and shape, as well as appropriate chemical complementarity with ligands.

Results

We present a novel cavity prediction method that analyzes results of virtual screening of specific ligands or fragment libraries by means of Self-Organizing Maps. We demonstrate the method with two thoroughly studied proteins where it successfully identified their active sites (AS) and relevant secondary binding sites (BS). Moreover, known active ligands mapped the AS better than inactive ones. Interestingly, docking a naive fragment library brought even more insight. We then systematically applied the method to the 102 targets from the DUD-E

SUBMITTER: Harigua-Souiai E 

PROVIDER: S-EPMC4381396 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature