Mining Natural Products for Macrocycles to Drug Difficult Targets
| Autor: | Peter Sjö, Vasanthanathan Poongavanam, Stefan Geschwindner, Fabio Begnini, Björn Over, Stefan Schiesser, Jan Kihlberg, Patrik Johansson, Lisa Wissler, Mohit Tyagi, Christian Tyrchan, Marie Castaldo |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Models
Molecular Databases Factual NF-E2-Related Factor 2 In silico Drug Evaluation Preclinical Computational biology 01 natural sciences Article 03 medical and health sciences Structure-Activity Relationship Drug Discovery Data Mining Humans Computer Simulation Polycyclic Compounds PROTEIN-PROTEIN INTERACTION SMALL MOLECULES KELCH DOMAIN PREDICTION DISCOVERY INHIBITORS FRAGMENTS PROGRAM BIND RULE 030304 developmental biology 0303 health sciences Biological Products Kelch-Like ECH-Associated Protein 1 Chemistry Läkemedelskemi 0104 chemical sciences Molecular Docking Simulation 010404 medicinal & biomolecular chemistry Solubility Docking (molecular) Microsomes Liver Molecular Medicine Medicinal Chemistry |
| Zdroj: | Journal of Medicinal Chemistry 'Journal of Medicinal Chemistry ', vol: 64, pages: 1054-1072 (2021) |
| ISSN: | 1520-4804 0022-2623 |
| Popis: | Lead generation for difficult-to-drug targets that have large, featureless, and highly lipophilic or highly polar and/or flexible binding sites is highly challenging. Here, we describe how cores of macrocyclic natural products can serve as a high-quality in silico screening library that provides leads for difficult-to-drug targets. Two iterative rounds of docking of a carefully selected set of natural-product-derived cores led to the discovery of an uncharged macrocyclic inhibitor of the Keap1-Nrf2 protein- protein interaction, a particularly challenging target due to its highly polar binding site. The inhibitor displays cellular efficacy and is well-positioned for further optimization based on the structure of its complex with Keapl and synthetic access. We believe that our work will spur interest in using macrocyclic cores for in silico-based lead generation and also inspire the design of future macrocycle screening collections. |
| Databáze: | OpenAIRE |
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