A Dual-Target-Based Screening Strategy for Anti-SARS-CoV-2 Active Compounds Enabling the Identification of Macrocyclic Peptide Natural Products: Chloropeptins
Toward the development of innovative antiviral drugs, potential dual inhibitors were screened from the O̅mura natural compound library by the use of SARS-CoV-2 3CL<sup>pro</sup> enzyme activity and SARS-CoV-2 spike trimer-ACE2 ELISA assays. This screening identified macrocyclic peptide natural products, chloropeptins, as potential dual inhibitors. Further evaluation of their anti-SARS-CoV-2 activity against several variants demonstrated their strong potency (IC<sub>50</sub> = 2.96-4.36 μM). Pseudovirus and BlaM-Vpr assays utilizing SARS-CoV-2 spike pseudovirus confirmed that chloropeptin 1 effectively blocks viral entry. Additionally, molecular docking simulations revealed that chloropeptins form hydrogen bonds and van der Waals interactions with Lys353 and His34 of ACE2, implicating key roles involved in SARS-CoV-2 spike protein binding. These findings highlight chloropeptins as promising candidates for the development of novel anti-SARS-CoV-2 therapeutics.
Authors
- Terumasa Ikeda (ORCID: https://orcid.org/0000-0003-2869-9450)
- Kamrun Naher
- Otowa Takahashi
- Sota Honma
- Takayuki Uematsu (ORCID: https://orcid.org/0000-0002-3680-7231)
- Kazuhiko Katayama (ORCID: https://orcid.org/0000-0002-7692-1151)
- Kei Haga (ORCID: https://orcid.org/0000-0002-8524-1078)
- Teruki Honma (ORCID: https://orcid.org/0000-0003-3761-9504)
- Masako Honsho
- Yukihiro Asami (ORCID: https://orcid.org/0000-0003-1821-9169)
- Aoi Kimishima (ORCID: https://orcid.org/0000-0002-2625-1356)
- Chiduru Watanabe (ORCID: https://orcid.org/0000-0002-0742-3896)
- Toshiaki Sunazuka (ORCID: https://orcid.org/0000-0003-2538-9916)
- Reiko Takai‐Todaka
- Yukiko Ujie
Institutions
- Structure Based Design (United States) (US)
- Center for Human Genetics (US)
- Biology of Infection (FR)
- Kitasato University Medical Center (JP)
- United Biomedical (United States) (US)
- RIKEN Center for Integrative Medical Sciences (JP)
- Institute of Biomedical Science (GB)
- Memorial Health System (US)
- Kitasato University (JP)
- Kumamoto University (JP)
Publication Details
- Journal
- Journal of Natural Products
- Published
- 2025-09-25
- DOI
- https://doi.org/10.1021/acs.jnatprod.5c00634
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00