Abstract
Human immunodeficiency virus type-1 reverse transcriptase (HIV-1 RT) plays a key in the life cycle of HIV-1. It is considered to be one of the promising targets for treating HIV/AIDS which contains two drug binding sites, a substrate binding site, and an allosteric site. Non-nucleoside reverse transcriptase inhibitors (NNRTIs) are a class of RT inhibitors that bind to allosteric sites on HIV-1 RT in a non-competitive manner and thereby disrupting the conformation of RT. Hence, they can act as potent inhibitors against HIV-1 RT. In present study, the key structural requirements for enhancing HIV-1 RT inhibitory activity were explored from combined docking and three-dimensional quantitative structure activity relationship (3D QSAR) protocols. Initially, multiple-receptor conformation docking (MRCD) was performed using a series of diaryl pyridine and pyrimidine derivatives into the active site of ten X-ray crystal structures and one NMR-resolved conformation of HIV-1 RT. Later, the dock poses obtained from docking were clustered and 3D QSAR models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) methods. Finally, a robust model was established using cross-validation techniques and the robustness of the model was confirmed through high accuracy of q2loo of 0.843 and 0.682, r2ncv of 0.977 and 0.949, and r2pred of 0.702 and 0.690, respectively, for CoMFA and CoMSIA. Based on the outcome of the results, new pyrimidine derivatives having potential inhibitory against HIV-1 RT were designed.
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Acknowledgements
We greatly acknowledge Tripos Inc., USA, and Schrödinger LLC, New York, for providing the software. The author Saikiran Reddy Peddi (IF150172) would like to acknowledge the financial support from DST for a research fellowship.
Funding
This research was made possible through grants from DST-SERB (SB/EMEQ-004/2013) New Delhi, India.
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Supplementary information consists of toxicity profile of dataset compounds calculated from pkCSM online server.
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Peddi, S.R., Mohammed, N.A., Hussein, A.A. et al. Multiple-receptor conformation docking, dock pose clustering, and 3D QSAR-driven approaches exploring new HIV-1 RT inhibitors. Struct Chem 29, 999–1012 (2018). https://doi.org/10.1007/s11224-018-1082-8
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DOI: https://doi.org/10.1007/s11224-018-1082-8