Machine learning-driven docking of diverse DDAs as promising cysteine protease inhibitors targeting Mpox virus.
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| Title: | Machine learning-driven docking of diverse DDAs as promising cysteine protease inhibitors targeting Mpox virus. |
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| Authors: | Alotaibi BS; Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Shaqra University, Al- Quwayiyah, Riyadh Saudi Arabia., Ahmad I; Central Labs, Al-Qura'a, King Khalid University, P.O. Box 960, Abha, Saudi Arabia.; Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia., Almutairy B; Department of Pharmacology, College of Pharmacy, Shaqra University, Shaqra, 11961 Saudi Arabia., Alkhammash A; Department of Pharmacology, College of Pharmacy, Shaqra University, Shaqra, 11961 Saudi Arabia., Alsaiari AA; College of Applied Medical Science, Clinical Laboratories Science Department, Taif University, Taif, Saudi Arabia., Khan K; Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, 75270 Pakistan., Burki S; Department of Pharmacology, Jinnah Sindh Medical University, Rafiqui H.J Shaheed Road, Karachi, Pakistan. |
| Source: | In silico pharmacology [In Silico Pharmacol] 2025 Jun 09; Vol. 13 (2), pp. 85. Date of Electronic Publication: 2025 Jun 09 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer-Verlag, GmbH Country of Publication: Germany NLM ID: 101623954 Publication Model: eCollection Cited Medium: Print ISSN: 2193-9616 (Print) Linking ISSN: 21939616 NLM ISO Abbreviation: In Silico Pharmacol Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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