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• W2570772893 abstract "Despite its remarkable importance in the arena of drug design, serotonin 1A receptor (5-HT1A) has been elusive to the X-ray crystallography community. This lack of direct structural information not only hampers our knowledge regarding the binding modes of many popular ligands (including the endogenous neurotransmitter—serotonin), but also limits the search for more potent compounds. In this paper we shed new light on the 3D pharmacological properties of the 5-HT1A receptor by using a ligand-guided approach (ALiBERO) grounded in the Internal Coordinate Mechanics (ICM) docking platform. Starting from a homology template and set of known actives, the method introduces receptor flexibility via Normal Mode Analysis and Monte Carlo sampling, to generate a subset of pockets that display enriched discrimination of actives from inactives in retrospective docking. Here, we thoroughly investigated the repercussions of using different protein templates and the effect of compound selection on screening performance. Finally, the best resulting protein models were applied prospectively in a large virtual screening campaign, in which two new active compounds were identified that were chemically distinct from those described in the literature." @default.
• W2570772893 created "2017-01-13" @default.
• W2570772893 creator A5020144569 @default.
• W2570772893 creator A5023487324 @default.
• W2570772893 creator A5025399512 @default.
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• W2570772893 creator A5069966276 @default.
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• W2570772893 creator A5075834688 @default.
• W2570772893 creator A5079988920 @default.
• W2570772893 creator A5085355095 @default.
• W2570772893 creator A5088932825 @default.
• W2570772893 date "2017-01-18" @default.
• W2570772893 modified "2023-09-27" @default.
• W2570772893 title "From Homology Models to a Set of Predictive Binding Pockets–a 5-HT_1A Receptor Case Study" @default.
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