Molecular modeling studies of HIV-1 non-nucleoside reverse transcriptase inhibitors using 3D-QSAR, virtual screening, and docking simulations

Jian-Bo Tong, Shang-Shang Qin, Shan Lei, Yang Wang

Abstract


Acquired Immunodeficiency Syndrome (AIDS) is a significant human health threat around the world, therefore, the study of anti-HIV drug design has become an important task for today’s society. In this paper, a three-dimensional quantitative structure-activity relationships study (3D-QSAR) was conducted on 72 HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs) using Topomer comparative molecular field analysis (Topomer CoMFA). The multiple correlation coefficients of fitting, cross-validation, and external validation were 0.899, 0.788, and 0.942, respectively. The results indicated that the model obtained had both favorable estimation stability and good prediction capability. Topomer Search was used to search appropriate R groups from ZINC database, 14 new compounds were designed thereby, and 12 of the new compounds were predicted to be more active than the template molecule. These results strongly suggest that the Topomer Search is effective in screening and can be a useful guide in the design of new HIV-1 drugs. Ligands of the template molecule and new designed compounds were used for molecular docking to study the interaction of these compounds with the protein receptor. The results show that the ligands would form hydrogen-bonding interactions with the residues Ala28, Asp 29, Gly49 and Ile50 of the protein receptor generally, thereby providing additional insights for the designing of even more effective drugs.


Keywords


3D-QSAR; NNRTIs; Topomer CoMFA; Topomer Search; New drug design; Molecular docking

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DOI: https://doi.org/10.2298/JSC180904098T

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