Multi‐Objective Molecular De Novo Design by Adaptive Fragment Prioritization |
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| Authors: | Michael Reutlinger Dr. Tiago Rodrigues Dr. Petra Schneider Prof. Dr. Gisbert Schneider |
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| Affiliation: | 1. Eidgen?ssische Technische Hochschule (ETH), Departement Chemie und Angewandte Biowissenschaften, Vladimir‐Prelog‐Weg 4, 8093 Zürich (Switzerland);2. inSili.com GmbH, Segantinisteig 3, 8049 Zürich (Switzerland) |
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| Abstract: | We present the development and application of a computational molecular de novo design method for obtaining bioactive compounds with desired on‐ and off‐target binding. The approach translates the nature‐inspired concept of ant colony optimization to combinatorial building block selection. By relying on publicly available structure–activity data, we developed a predictive quantitative polypharmacology model for 640 human drug targets. By taking reductive amination as an example of a privileged reaction, we obtained novel subtype‐selective and multitarget‐modulating dopamine D4 antagonists, as well as ligands selective for the sigma‐1 receptor with accurately predicted affinities. The nanomolar potencies of the hits obtained, their high ligand efficiencies, and an overall success rate of 90 % demonstrate that this ligand‐based computer‐aided molecular design method may guide target‐focused combinatorial chemistry. |
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| Keywords: | computer‐assisted drug design GPCR machine learning polypharmacology reductive amination |
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