De novo generation of dual-target ligands for the treatment of SARS-CoV-2 using deep learning, virtual screening, and molecular dynamic simulations.

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Title: De novo generation of dual-target ligands for the treatment of SARS-CoV-2 using deep learning, virtual screening, and molecular dynamic simulations.
Authors: Humayun F; Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, PR China.; State Key Laboratory of Microbial Metabolism and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, PR China., Khan F; National Institute of Health, Islamabad, Pakistan., Khan A; Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, PR China.; State Key Laboratory of Microbial Metabolism and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, PR China., Alshammari A; Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia., Ji J; Henan Provincial Engineering and Technology Center of Health Products for Livestock and Poultry, Henan Provincial Engineering and Technology Center of Animal Disease Diagnosis and Integrated Control, Nanyang Normal University, Nanyang, PR China., Farhan A; Department of Chemistry, Chung Yuan Christian University, Taoyuan, Taiwan., Fawad N; Poultry Research Institute, Rawalpindi, Pakistan., Alam W; National Institute of Health, Islamabad, Pakistan., Ali A; Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, PR China.; State Key Laboratory of Microbial Metabolism and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, PR China., Wei DQ; Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, PR China.; State Key Laboratory of Microbial Metabolism and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, PR China.; Centre for Research in Molecular Modeling, Concordia University, Québec, Canada.
Source: Journal of biomolecular structure & dynamics [J Biomol Struct Dyn] 2024 Apr; Vol. 42 (6), pp. 3019-3029. Date of Electronic Publication: 2023 Jul 14.
Publication Type: Journal Article
Journal Info: Publisher: Taylor & Francis Country of Publication: England NLM ID: 8404176 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1538-0254 (Electronic) Linking ISSN: 07391102 NLM ISO Abbreviation: J Biomol Struct Dyn Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:1538-0254
DOI:10.1080/07391102.2023.2234481