Potential novel HIV-1 reverse transcriptase inhibitors: a modeling and evaluation approach

Human immunodeficiency viru (HIV) is the causative agent of acquired immunodeficiency syndrome (AIDS), a disease that severely weakens the immune system and makes patients more susceptible to infections. Although there is no definitive cure for HIV, advances in drug development offer promising prospects. In this study, we targeted HIV-1 reverse transcriptase by performing virtual screening (VS) to identify novel candidate compounds. From a database of compounds similar to the inhibitor thymidine-5'-triphosphate (TTP), three compounds (CID441663, CID123650073, and CID123789980) were selected for their docking scores, which outperformed those of the reference compound TTP (-6.2302 kcal/mol). These compounds were then subjected to ADMET, PASS, and DFT analyses. Interestingly, all three ligands showed a broad spectrum of predicted antiviral activity, including targets related to human herpes virus and HIV. Specifically, while TTP primarily targets HIV-1 reverse transcriptase, the top three ligands were predicted to target HIV-1 integrase, with CID441663 and CID123789980 displaying higher confidence in this target compared to CID123650073. These findings suggest that the candidate ligands should undergo further in vitro validation to determine their precise roles as inhibitors or antagonists, and to confirm their selective targeting of HIV-related proteins.

• HIV-1 reverse transcriptase inhibitors
• HIV-1 integrase inhibitors
• virtual screening
• molecular docking
• ADMET prediction
• PASS prediction
• DFT calculations
• antiviral activity prediction
• drug repurposing

• 3 — Bonne santé et bien-être

• Computational Drug Discovery Methods
• HIV/AIDS drug development and treatment
• Synthesis and Characterization of Heterocyclic Compounds
• HIV-1 reverse transcriptase inhibitors
• HIV-1 integrase inhibitors
• virtual screening
• molecular docking
• ADMET prediction
• PASS prediction
• DFT calculations
• antiviral activity prediction
• Computational Theory and Mathematics
• Infectious Diseases
• Organic Chemistry
• Computer Science
• Medicine
• Chemistry