Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

The increasing incidence of HIV-1 drug resistance presents a challenge to the effectiveness of combination antiretroviral therapy, particularly in Southern Africa. The development of resistance to non-nucleotide reverse transcriptase inhibitors (NNRTIs) threatens the long-term success of antiretroviral therapy. In 2019, antimicrobial resistance directly accounted for an estimated 1.27 million deaths globally. This study employed an in-silico approach to investigate NNTRI drugs and their derivatives. Techniques used included density functional theory calculations, molecular docking, enumeration, quantitative structure-activity relationship (QSAR) analysis, molecular dynamics simulation (MDS), and molecular mechanics with generalized Born and surface area methods. The analysis focused on various pyrimidine derivatives and six NNRTI drugs, examining their interactions with the HIV-1 protein (PDB code 1HQU). A QSAR model was developed to predict the biological activity of the six NNRTIs under investigation. Using 94 pyrimidine derivatives, the QSAR model achieved an R<sup>2</sup> OF 0.822 and a Q<sup>2</sup> of 0.815, indicating a high level of predictive accuracy. MDS were conducted to assess the stability of various ligands and their newly developed alternatives, ensuring they remained bound to the protein's active site over a 200-nanosecond simulation timeframe. Etravirine exhibited root mean square deviation (RMSD) fluctuations of approximately 4.5 Å, while its enumerated derivatives showed RMSD fluctuations of 3.5 Å. Through molecular docking, MDS, and free energy computations, enumerated Etravirine demonstrated the best performance, with an activity value of 7.373 and a docking score of -10.517 kcal/mol. Furthermore, the calculated free energy of binding for enumerated Etravirine was -89.684 kcal/mol, outperforming other ligands under investigation. The significant improvement suggests that the modified Etravirine holds promising potential as a novel agent in antiretroviral therapy. The obtained lower RMSD value, the enhanced amino acid interactions, and the highest binding free energy indicate that enumerated Etravirine could serve as a viable alternative for HIV/AIDS treatment.

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Publication Details

Journal
Journal of Visualized Experiments
Published
2025-05-09
DOI
https://doi.org/10.3791/67457
Citations
3
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
4.51
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article

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Krishna Govender, Penny P. Govender, Ephraim Felix Marondedze, Vitalis Mbayo
3 citations
Journal of Visualized Experiments
Computational Drug Discovery Methods
4.51
article

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Krishna Govender, Penny P. Govender, Ephraim Felix Marondedze, Vitalis Mbayo
article en
3 citations

Abstract

The increasing incidence of HIV-1 drug resistance presents a challenge to the effectiveness of combination antiretroviral therapy, particularly in Southern Africa. The development of resistance to non-nucleotide reverse transcriptase inhibitors (NNRTIs) threatens the long-term success of antiretroviral therapy. In 2019, antimicrobial resistance directly accounted for an estimated 1.27 million deaths globally. This study employed an in-silico approach to investigate NNTRI drugs and their derivatives. Techniques used included density functional theory calculations, molecular docking, enumeration, quantitative structure-activity relationship (QSAR) analysis, molecular dynamics simulation (MDS), and molecular mechanics with generalized Born and surface area methods. The analysis focused on various pyrimidine derivatives and six NNRTI drugs, examining their interactions with the HIV-1 protein (PDB code 1HQU). A QSAR model was developed to predict the biological activity of the six NNRTIs under investigation. Using 94 pyrimidine derivatives, the QSAR model achieved an R<sup>2</sup> OF 0.822 and a Q<sup>2</sup> of 0.815, indicating a high level of predictive accuracy. MDS were conducted to assess the stability of various ligands and their newly developed alternatives, ensuring they remained bound to the protein's active site over a 200-nanosecond simulation timeframe. Etravirine exhibited root mean square deviation (RMSD) fluctuations of approximately 4.5 Å, while its enumerated derivatives showed RMSD fluctuations of 3.5 Å. Through molecular docking, MDS, and free energy computations, enumerated Etravirine demonstrated the best performance, with an activity value of 7.373 and a docking score of -10.517 kcal/mol. Furthermore, the calculated free energy of binding for enumerated Etravirine was -89.684 kcal/mol, outperforming other ligands under investigation. The significant improvement suggests that the modified Etravirine holds promising potential as a novel agent in antiretroviral therapy. The obtained lower RMSD value, the enhanced amino acid interactions, and the highest binding free energy indicate that enumerated Etravirine could serve as a viable alternative for HIV/AIDS treatment.

Journal of Visualized Experiments(219)
University of Johannesburg (ZA)
Zero hunger
Openalex Percentile: Top 6%
Computational Drug Discovery Methods
4.51
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