Harnessing SuperNatural database to identify VP35 inhibitors as anti-Ebola drug candidates: A multistage In silico study.
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| Title: | Harnessing SuperNatural database to identify VP35 inhibitors as anti-Ebola drug candidates: A multistage In silico study. |
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| Authors: | Hasb AAM; Computational Chemistry Laboratory, Chemistry Department, Faculty of Science, Minia University, Minia, Egypt., Mekhemer GAH; Computational Chemistry Laboratory, Chemistry Department, Faculty of Science, Minia University, Minia, Egypt., Sidhom PA; Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Tanta University, Tanta, Egypt., Rady A; Department of Zoology, College of Science, King Saud University, Riyadh, Saudi Arabia., Han Y; School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin, China., Ibrahim MAA; Computational Chemistry Laboratory, Chemistry Department, Faculty of Science, Minia University, Minia, Egypt.; School of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.; Department of Engineering, College of Engineering and Technology, University of Technology and Applied Sciences, Nizwa, Sultanate of Oman. |
| Source: | Antiviral therapy [Antivir Ther] 2025 Dec; Vol. 30 (6), pp. 13596535251405027. Date of Electronic Publication: 2025 Dec 23. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: SAGE Publications Country of Publication: England NLM ID: 9815705 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2040-2058 (Electronic) Linking ISSN: 13596535 NLM ISO Abbreviation: Antivir Ther Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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