Abstract

When designing new medications targeting HIV-1, drug designers concentrate on reverse transcriptase (RT), the central enzyme of their concern. This is due to its vital role in converting single-stranded RNA into double-stranded DNA throughout the life cycle of HIV-1. In recent reports, a series of newly discovered pyridone derivatives with biphenyl substitutions have emerged as highly potent HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs), displaying impressive antiviral activity. To analyse the three-dimensional quantitative structure-activity relationship (3D-QSAR) of pyridone inhibitors with biphenyl substitutions, we employed CoMFA and CoMSIA methods in this study. The dataset comprises a total of 51 compounds. The findings of this research demonstrate that both the CoMFA (q2=0.688, r2=0.976, rpred2=0.831) and CoMSIA/SHE (q2=0.758, r2=0.968, rpred2=0.828) models exhibit excellent predictive capability and reliable estimation stability. According to the findings of the model, we designed a collection of eleven molecules that exhibit the potential for significantly improved predictive activity. We proceeded to investigate the binding patterns of these compounds to receptor proteins utilizing the molecular docking technique. To ensure the reliability of the docking results, we went on to validate them by conducting molecular dynamics simulations and performing accurate calculations of the binding free energy. Moreover, based on initial ADMET predictions, the results consistently indicate that the newly created molecule possesses favourable pharmacokinetic properties. This study will help to facilitate the development of efficient novel inhibitors that specifically target HIV-1's non-nucleoside reverse transcriptase (NNRTIs).Communicated by Ramaswamy H. Sarma.

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