دورية أكاديمية
Structural and energetic analysis of NS5 protein inhibition by small molecules in Japanese encephalitis virus using machine learning and steered molecular dynamics approach.
العنوان: | Structural and energetic analysis of NS5 protein inhibition by small molecules in Japanese encephalitis virus using machine learning and steered molecular dynamics approach. |
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المؤلفون: | Alhazmi AY; Pharmaceutical Practices Department, College of Pharmacy, Umm Al-Qura University, Makkah, Saudi Arabia., Khan FR; Department of Clinical Laboratory Sciences, College of Applied Medical Sciences - AlQuwayiyah, Shaqra University, Saudi Arabia., Rehman ZU; Department of Pharmaceutical Chemistry, College of Pharmacy, Jazan University, Jazan, Saudi Arabia., Hazazi A; Department of Pathology and Laboratory Medicine, Security Forces Hospital Program, Riyadh, Saudi Arabia., Alotaibi BS; Department of Clinical Laboratory Sciences, College of Applied Medical Sciences - AlQuwayiyah, Shaqra University, Saudi Arabia., Alharthi NS; Department of Medical Laboratory. College of Applied Medical Sciences in Al-Kharj, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudia Arabia., Alhuthali HM; Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University, Taif, Saudi Arabia., Aba Alkhayl FF; Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah, Saudi Arabia., Alshehri FF; Department of Medical Laboratories, College of Applied Medical Sciences, Shaqra University, Shaqra, Saudi Arabia., Alkhoshaiban A; Unit of Scientific Research, Applied College, Qassim University, Buraydah, Saudi Arabia., Al-Otaibi F; Department of Pharmacy Practice, College of Pharmacy, Shaqra University, Saudi Arabia. |
المصدر: | Journal of biomolecular structure & dynamics [J Biomol Struct Dyn] 2024 Feb 26, pp. 1-18. Date of Electronic Publication: 2024 Feb 26. |
Publication Model: | Ahead of Print |
نوع المنشور: | Journal Article |
اللغة: | English |
بيانات الدورية: | 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 |
أسماء مطبوعة: | Publication: June 2012- : Oxon, UK : Taylor & Francis Original Publication: Guilderland, NY : Adenine Press, [c1983- |
مستخلص: | One of the viral diseases that affect millions of people around the world, particularly in developing countries, is Japanese encephalitis (JE). In this study, the conserved protein of this virus, that is, non-structural protein 5 (NS5), was used as a target protein for this study, and a compound library of 749 antiviral molecules was screened against NS5. The current study employed machine learning-based virtual screening combined with molecular docking. Here, three hits ( 24360 , 123519051 and 213039 ) had lower binding energies (< -8 kcal/mol) than the control, S-Adenosyl-L-homocysteine (SAH). All the compounds showed significant H-bond interactions with functional residues, which were also observed by the control. Molecular dynamics simulation, MM/GBSA for binding free energy analysis, principal component analysis and free energy landscape were also performed to study the stability of the complex formation. All three compounds had similar root mean square deviation trends, which were comparable to the control, SAH. Post-MD, the 123519051 -receptor complex had the highest number of H-bonds (4 to 5) after the control, out of which three exhibited the highest percentage occupancy (50%, 24% and 79%). Both docking and MD, 123519051 showed an H-bond with the residue Gly111, which was also found for the control-protein complex. 123519051 showed the lowest binding free energy with Δ G |
فهرسة مساهمة: | Keywords: Japanese encephalitis; machine learning; molecular docking; molecular dynamics simulation; non-structural protein 5 |
تواريخ الأحداث: | Date Created: 20240226 Latest Revision: 20240226 |
رمز التحديث: | 20240226 |
DOI: | 10.1080/07391102.2024.2316767 |
PMID: | 38407246 |
قاعدة البيانات: | MEDLINE |
تدمد: | 1538-0254 |
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DOI: | 10.1080/07391102.2024.2316767 |