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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/8102| AI-Guided Discovery of Novel SARS-CoV-2 PLpro Inhibitors: Accelerating Antiviral Drug Development in the Fight Against COVID-19 | |
| Will Spagnoli Wayne Danter | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| https://doi.org/10.1101/2023.04.05.535700 | |
| https://www.biorxiv.org/content/10.1101/2023.04.05.535700v1 | |
| Abstract The global pandemic caused by SARS-CoV-2 has highlighted the urgent need for effective antiviral drugs. The papain-like protease (PLpro) is a key viral enzyme involved in the replication and immune evasion of SARS-CoV-2, making it a promising target for antiviral drug development. In this study, we employed an artificial intelligence (AI)-driven drug discovery platform, LIME, to generate novel inhibitors of the SARS-CoV-2 PLpro. LIME is based on generative language models that can generate diverse, valid, and synthetically accessible compounds. The LIME software was used to identify potential inhibitors with strong binding affinity and specificity to the target protein. The top 13 hit compounds were tested in vitro, and the top 5 inhibitors with strong binding affinity and specificity were selected for further analysis. A top candidate molecule, CSEMRS-1376, exhibited similar binding energies and structural similarities to the known SARS-CoV-2 PLpro inhibitor, XR8-89. Computational analysis of the absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles of the hit compounds and XR8-89 showed that both CSEMRS-1376 and XR8-89 demonstrated favorable ADMET profiles. Overall, the LIME software successfully identified several novel molecules, including CSEMRS-1376, with strong potential as a therapeutic agent against SARS-CoV-2. The study highlights the potential of AI-driven drug discovery platforms, such as LIME, to accelerate the drug development process and pave the way for more efficient and effective therapeutics. | |
| bioRxiv | |
| 05-04-2023 | |
| Preimpreso | |
| Inglés | |
| Público en general | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Materiales de Consulta y Comunicados Técnicos |
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| AI-Guided Discovery of Novel SARS-CoV-2 PLpro Inhibitors.pdf | 484.85 kB | Adobe PDF | Visualizar/Abrir |