Flexi-pharma: a molecule-ranking strategy for virtual screening using pharmacophores from ligand-free conformational ens
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Flexi‑pharma: a molecule‑ranking strategy for virtual screening using pharmacophores from ligand‑free conformational ensembles Isaias Lans1 · Karen Palacio‑Rodríguez1 · Claudio N. Cavasotto2,3,4 · Pilar Cossio1,5 Received: 6 March 2020 / Accepted: 27 June 2020 © The Author(s) 2020
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. Keywords Ligand-free pharmacophore · Virtual screening · Dynamics · Drug discovery · Enrichment · Affinity map
Introduction Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10822-020-00329-7) contains supplementary material, which is available to authorized users. * Pilar Cossio [email protected] 1
Biophysics of Tropical Diseases Max Planck Tandem Group, University of Antioquia UdeA, Calle 70 No. 52‑21, Medellín, Colombia
2
Computational Drug Design and Biomedical Informatics Laboratory, Translational Medicine Research Institute (IIMT), CONICET-Universidad Austral, Pilar, Buenos Aires, Argentina
3
Facultad de Ciencias Biomédicas, and Facultad de Ingeniería, Universidad Austral, Pilar, Buenos Aires, Argentina
4
Austral Institute for Applied Artificial Intelligence, Universidad Austral, Pilar, Buenos Aires, Argentina
5
Department of Theoretical Biophysics, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany
During the past two decades
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