دورية أكاديمية
In silico assessment of a natural small molecule as an inhibitor of programmed death ligand 1 for cancer immunotherapy: a computational approach.
| العنوان: | In silico assessment of a natural small molecule as an inhibitor of programmed death ligand 1 for cancer immunotherapy: a computational approach. |
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| المؤلفون: | Alharthi NS; Department of Medical Laboratory. College of Applied Medical Sciences in Al-Kharj, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudia Arabia., Alwethaynani MS; Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, AlQuwayiyah, Shaqra University, Saudi Arabia., Alhazmi AY; Pharmaceutical Practices Department, College of Pharmacy, Umm Al-Qura University, Makkah, Saudi Arabia., Alawam AS; Department of Biology, College of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia., Alshehri FF; Department of Medical Laboratories, College of Applied Medical Sciences, Shaqra University, Saudi Arabia., Alotaibi F; Department of Pharmacy Practice, College of Pharmacy, Shaqra University, Saudi Arabia., Rehman ZU; Department of Pharmaceutical Chemistry, College of Pharmacy, Jazan University, Saudi Arabia., Alkhayl FFA; Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah, Saudi Arabia., Al-Bazi MM; Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia., Khan FR; Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, AlQuwayiyah, Shaqra University, Saudi Arabia. |
| المصدر: | Journal of biomolecular structure & dynamics [J Biomol Struct Dyn] 2024 Feb 22, pp. 1-21. Date of Electronic Publication: 2024 Feb 22. |
| 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: | Programmed cell death ligand 1 (PD-L1) is a crucial target for cancer therapy. Here, an in silico study investigates PD-L1 to inhibit its interaction with PD1, thereby promoting an immune response to eliminate cancer cells. The study employed machine learning (ML) -based QSAR to detect PDL1 inhibitors. Morgan's fingerprint with docking score showed a 0.83 correlation with the experimental IC50, enabling the screening of 3200 natural compounds. The top three compounds, considered 2819 , 2821 and 3188 , were selected from the ML-based QSAR and subjected to molecular docking and simulation. The binding scores for 2819 , 2821 and 3188 were -7.0, -9.0 and -8.9 kcal/mol, respectively. The stability of the ligands during a 100 ns simulation was assessed using RMSD, showing that 2819 and 2821 maintained stable patterns comparable to the control inhibitor. Notably, 2819 exhibited a consistent stable pattern throughout the simulation, while 2821 showed stability in the last 40 ns. The control compound showed the highest number of hydrogen bonds with proteins, whereas compounds 2819 and 2821 formed continuous H-bonds. 3188 was separated from the protein in later phases and is not regarded as a potential PD-L1-binding molecule. MMGBSA binding free energy for complexes was computed. Control had the lowest binding free energy, while 2819 and 2821 also had lower binding energies. In contrast, 3188 showed poor binding free energy, causing protein separation. Principal component analysis showed a loss of entropy and reduced protein conformational variation. Overall, 2819 and 2821 are potential binders for PD-L1 inhibition and immune response triggering.Communicated by Ramaswamy H. Sarma. |
| فهرسة مساهمة: | Keywords: QSAR; RMSD; docking; in silico; machine learning; programmed cell death ligand 1 |
| تواريخ الأحداث: | Date Created: 20240222 Latest Revision: 20240222 |
| رمز التحديث: | 20240222 |
| DOI: | 10.1080/07391102.2024.2317980 |
| PMID: | 38385444 |
| قاعدة البيانات: | MEDLINE |
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Full Text Finder | تدمد: | 1538-0254 |
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| DOI: | 10.1080/07391102.2024.2317980 |