Hot-Spots-Guided Receptor-Based Pharmacophores (HS-Pharm): A Knowledge-Based Approach to Identify Ligand-Anchoring Atoms in Protein Cavities and Prioritize Structure-Based Pharmacophores

publication · 8 years ago
by Didier Rognan, Gilles Marcou, Caterina Barillari (Université de Strasbourg)
The design of biologically active compounds from ligand-free protein structures using a structure-based approach is still a major challenge. In this paper, we present a fast knowledge-based approach (HS-Pharm) that allows the prioritization of cavity atoms that should be targeted for ligand binding, by training machine learning algorithms with atom-based fingerprints of known ligand-binding pockets. The knowledge of hot spots for ligand binding is here used for focusing structure-based pharmacophore models. Three targets of pharmacological interest (neuraminidase, ß2 adrenergic receptor, and cyclooxygenase-2) were used to test the evaluated methodology, and the derived structure-based pharmacophores were used in retrospective virtual screening studies. The current study shows that structure-based pharmacophore screening is a powerful technique for the fast identification of potential hits in a chemical library, and that it is a valid alternative to virtual screening by molecular docking.
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