Computational drug discovery under RNA times.
Autor: | Bernetti M; Computational and Chemical Biology, Italian Institute of Technology, 16152 Genova, Italy.; Department of Pharmacy and Biotechnology, Alma Mater Studiorum-University of Bologna, 40126 Bologna, Italy., Aguti R; Computational and Chemical Biology, Italian Institute of Technology, 16152 Genova, Italy.; Department of Pharmacy and Biotechnology, Alma Mater Studiorum-University of Bologna, 40126 Bologna, Italy., Bosio S; Computational and Chemical Biology, Italian Institute of Technology, 16152 Genova, Italy.; Department of Pharmacy and Biotechnology, Alma Mater Studiorum-University of Bologna, 40126 Bologna, Italy., Recanatini M; Department of Pharmacy and Biotechnology, Alma Mater Studiorum-University of Bologna, 40126 Bologna, Italy., Masetti M; Department of Pharmacy and Biotechnology, Alma Mater Studiorum-University of Bologna, 40126 Bologna, Italy., Cavalli A; Computational and Chemical Biology, Italian Institute of Technology, 16152 Genova, Italy.; Department of Pharmacy and Biotechnology, Alma Mater Studiorum-University of Bologna, 40126 Bologna, Italy. |
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Jazyk: | angličtina |
Zdroj: | QRB discovery [QRB Discov] 2022 Nov 14; Vol. 3, pp. e22. Date of Electronic Publication: 2022 Nov 14 (Print Publication: 2022). |
DOI: | 10.1017/qrd.2022.20 |
Abstrakt: | RNA molecules play many functional and regulatory roles in cells, and hence, have gained considerable traction in recent times as therapeutic interventions. Within drug discovery, structure-based approaches have successfully identified potent and selective small-molecule modulators of pharmaceutically relevant protein targets. Here, we embrace the perspective of computational chemists who use these traditional approaches, and we discuss the challenges of extending these methods to target RNA molecules. In particular, we focus on recognition between RNA and small-molecule binders, on selectivity, and on the expected properties of RNA ligands. (© The Author(s) 2022.) |
Databáze: | MEDLINE |
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