Receptor pharmacophore ensemble (REPHARMBLE): a probabilistic pharmacophore modeling approach using multiple protein-ligand complexes

Kumar, Sivakumar Prasanth (2018) Receptor pharmacophore ensemble (REPHARMBLE): a probabilistic pharmacophore modeling approach using multiple protein-ligand complexes. In: JOURNAL OF MOLECULAR MODELING, 24 (10).

PDF Jou_Mol_Mod_24-10_282_2018.pdf - Published Version Restricted to Registered users only Download (5MB) | Request a copy

Abstract

Ensemble methods are gaining more importance in structure-based approaches as single protein-ligand complexes strongly influence the outcomes of virtual screening. Structure-based pharmacophore modeling based on a single protein-ligand complex with complex feature combinations is often limited to certain chemical classes. The REPHARMBLE (receptor pharmacophore ensemble) approach presented here examines the ability of an ensemble of selected protein-ligand complexes to populate pharmacophore space in the ligand binding site, rigorously assesses the importance of pharmacophore features using Poisson statistic and information theory-based entropy calculations, and generates pharmacophore models with high probabilities. In addition, an ensemble scoring function that combines all the resultant high-scoring pharmacophore models to score molecules is derived. The REPHARMBLE approach was evaluated on ten DUD-E benchmark datasets and afforded good screening performance, as measured by receiver operating characteristic, enrichment factor and Guner-Henry score. Although one of the high-scoring models achieved superior statistical results in each dataset, the ensemble scoring function balanced the shortcomings of each model and passed with close performance measures. This approach offers a reliable way of choosing the best-scoring features to build four-feature pharmacophore queries and customize a target-biased pharmacophore ensemble' scoring function for subsequent virtual screening.

Item Type:	Journal Article
Publication:	JOURNAL OF MOLECULAR MODELING
Publisher:	SPRINGER
Additional Information:	Copy right for this article belong to SPRINGER
Keywords:	Ensemble; Structure-based pharmacophore; Probabilistic model; Protein-ligand complex; Virtual screening; Entropy
Department/Centre:	Division of Biological Sciences > Molecular Biophysics Unit
Date Deposited:	09 Oct 2018 15:43
Last Modified:	09 Oct 2018 15:43
URI:	http://eprints.iisc.ac.in/id/eprint/60843

Actions (login required)

View Item