ArticleComputational and structural biotechnology journal2022
Potential drug discovery for COVID-19 treatment targeting Cathepsin L using a deep learning-based strategy.
Article in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 26 citations in OpenAlex.
- AI-guided identification of natural CTSL inhibitors with therapeutic potential for renal injury.PLoS computational biology · 2026Article
- Discovering novel Cathepsin L inhibitors from natural products using artificial intelligence.Computational and structural biotechnology journal · 2024Article
- Structural Elucidation and Antiviral Activity of Covalent Cathepsin L Inhibitors.Journal of medicinal chemistry · 2024Article
- Calpeptin is a potent cathepsin inhibitor and drug candidate for SARS-CoV-2 infections.Communications biology · 2023Article
- Revolutionizing Medicinal Chemistry: The Application of Artificial Intelligence (AI) in Early Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2023Review
- Structure-based lead optimization of peptide-based vinyl methyl ketones as SARS-CoV-2 main protease inhibitors.European journal of medicinal chemistry · 2023Article
- Navigating with chemometrics and machine learning in chemistry.Artificial intelligence review · 2023Article
- Children with type 1 diabetes in COVID-19 pandemic: Difficulties and solutions.World journal of clinical pediatrics · 2022Review
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cathepsin L (CTSL), a cysteine protease that can cleave and activate the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein, could be a promising therapeutic target for coronavirus disease 2019 (COVID-19). However, there is still no clinically available CTSL inhibitor that can be used. Here, we applied Chemprop, a newly trained directed-message passing deep neural network approach, to identify small molecules and FDA-approved drugs that can block CTSL activity to expand the discovery of CTSL inhibitors for drug development and repurposing for COVID-19. We found 5 molecules (Mg-132, Z-FA-FMK, leupeptin hemisulfate, Mg-101 and calpeptin) that were able to significantly inhibit the activity of CTSL in the nanomolar range and inhibit the infection of both pseudotype and live SARS-CoV-2. Notably, we discovered that daptomycin, an FDA-approved antibiotic, has a prominent CTSL inhibitory effect and can inhibit SARS-CoV-2 pseudovirus infection. Further, molecular docking calculation showed stable and robust binding of these compounds with CTSL. In conclusion, this study suggested for the first time that Chemprop is ideally suited to predict additional inhibitors of enzymes and revealed the noteworthy strategy for screening novel molecules and drugs for the treatment of COVID-19 and other diseases with unmet needs.
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