Flexi-pharma: a molecule-ranking strategy for virtual screening using pharmacophores from ligand-free conformational ensembles

Isaias Lans,Pilar Cossio,Karen Palacio-Rodríguez,Claudio N Cavasotto

doi:10.1007/s10822-020-00329-7

Abstract

Computer-aided strategies are useful for reducing the costs and increasing the success-rate in drug discovery. Among these strategies, methods based on pharmacophores (an ensemble of electronic and steric features representing the target active site) are efficient to implement over large compound libraries. However, traditional pharmacophore-based methods require knowledge of active compounds or ligand–receptor structures, and only few ones account for target flexibility. Here, we developed a pharmacophore-based virtual screening protocol, Flexi-pharma, that overcomes these limitations. The protocol uses molecular dynamics (MD) simulations to explore receptor flexibility, and performs a pharmacophore-based virtual screening over a set of MD conformations without requiring prior knowledge about known ligands or ligand–receptor structures for building the pharmacophores. The results from the different receptor conformations are combined using a “voting” approach, where a vote is given to each molecule that matches at least one pharmacophore from each MD conformation. Contrarily to other approaches that reduce the pharmacophore ensemble to some representative models and score according to the matching models or molecule conformers, the Flexi-pharma approach takes directly into account the receptor flexibility by scoring in regards to the receptor conformations. We tested the method over twenty systems, finding an enrichment of the dataset for 19 of them. Flexi-pharma is computationally efficient allowing for the screening of thousands of compounds in minutes on a single CPU core. Moreover, the ranking of molecules by vote is a general strategy that can be applied with any pharmacophore-filtering program.

Highlights

During the past two decades, the implementation of computational tools in drug discovery has increased
The Flexi-pharma protocol consists on the following steps: (1) run an molecular dynamics (MD) simulation starting from a crystal structure; (2) select a set of MD conformations of the ligand-free receptor; (3) build a set of pharmacophores for each conformation; (4) use Pharmer [34] to screen a compound library finding the molecules that match any pharmacophore; (5) give a ‘vote’ to the molecules that match at least one pharmacophore for each conformation and (6) add the votes from the MD conformations
We present a protocol for virtual screening based on pharmacophores, Flexi-pharma, which uses multiple free ligand–receptor conformations

Summary

Introduction

During the past two decades, the implementation of computational tools in drug discovery has increased. Many pharmaceutical companies have included computational methods in their drug discovery pipelines [1, 2] These methods have been useful to decrease the costs of drug discovery by reducing the number of compounds to test in experimental assays [3]. Their implementation in drug-screening protocols increases the rate of success of finding active compounds and reduces the false negatives from high-throughput compound screening [1, 4,5,6,7,8,9,10].

Methods

Results

Conclusion