Building shape-focused pharmacophore models for effective docking screening.

ABSTRACT: The performance of molecular docking can be improved by comparing the shape similarity of the flexibly sampled poses against the target proteins' inverted binding cavities. The effectiveness of these pseudo-ligands or negative image-based models in docking rescoring is boosted further by performing enrichment-driven optimization. Here, we introduce a novel shape-focused pharmacophore modeling algorithm O-LAP that generates a new class of cavity-filling models by clumping together overlapping atomic content via pairwise distance graph clustering. Top-ranked poses of flexibly docked active ligands were used as the modeling input and multiple alternative clustering settings were benchmark-tested thoroughly with five demanding drug targets using random training/test divisions. In docking resco

SUBMITTER: Moyano-Gomez P 

PROVIDER: S-EPMC11312248 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature