Hanna, George S. and Benjamin, Menny M. and Choo, Yeun-Mun and De, Ramyani and Schinazi, Raymond F. and Nielson, Sarah E. and Hevel, Joan M. and Hamann, Mark T. (2024) Informatics and Computational Approaches for the Discovery and Optimization of Natural Product-Inspired Inhibitors of the SARS-CoV-2 2′-O-Methyltransferase. Journal of Natural Products, 87 (2). pp. 217-227. ISSN 0163-3864, DOI https://doi.org/10.1021/acs.jnatprod.3c00875.
Full text not available from this repository.Abstract
The urgent need for new classes of orally available, safe, and effective antivirals-covering a breadth of emerging viruses-is evidenced by the loss of life and economic challenges created by the HIV-1 and SARS-CoV-2 pandemics. As frontline interventions, small-molecule antivirals can be deployed prophylactically or postinfection to control the initial spread of outbreaks by reducing transmissibility and symptom severity. Natural products have an impressive track record of success as prototypic antivirals and continue to provide new drugs through synthesis, medicinal chemistry, and optimization decades after discovery. Here, we demonstrate an approach using computational analysis typically used for rational drug design to identify and develop natural product-inspired antivirals. This was done with the goal of identifying natural product prototypes to aid the effort of progressing toward safe, effective, and affordable broad-spectrum inhibitors of Betacoronavirus replication by targeting the highly conserved RNA 2'-O-methyltransferase (2'-O-MTase). Machaeriols RS-1 (7) and RS-2 (8) were identified using a previously outlined informatics approach to first screen for natural product prototypes, followed by in silico-guided synthesis. Both molecules are based on a rare natural product group. The machaeriols (3-6), isolated from the genus Machaerium, endemic to Amazonia, inhibited the SARS-CoV-2 2'-O-MTase more potently than the positive control, Sinefungin (2), and in silico modeling suggests distinct molecular interactions. This report highlights the potential of computationally driven screening to leverage natural product libraries and improve the efficiency of isolation or synthetic analog development.
| Item Type: | Article |
|---|---|
| Funders: | United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Center for Complementary & Alternative Medicine (NCCAM) (F31AT011158), United States Department of Health & Human Services National Institutes of Health (NIH) - USA (R01-AI-161570); (P30-AI-050409), United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of General Medical Sciences (NIGMS) (RO1 GM145845-01) |
| Uncontrolled Keywords: | Sponge; Analogs |
| Subjects: | Q Science > QD Chemistry |
| Divisions: | Faculty of Science > Department of Chemistry |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 12 Nov 2024 01:03 |
| Last Modified: | 12 Nov 2024 01:03 |
| URI: | http://eprints.um.edu.my/id/eprint/45763 |
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