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Updated: Jun 27, 2026

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Exploring the binding of HIV-1 integrase inhibitors by comparative residue interaction analysis (CoRIA)
Devendra K Dhaked1, Jitender Verma, Anil Saran
1Department of Pharmaceutical Chemistry, Bombay College of Pharmacy, Kalina, Santacruz (E), Mumbai, 400 098, India.
Abstract:
Since the recognition of HIV-1 integrase as a novel and rational target for HIV therapeutics, remarkable progress has been made in the development of integrase inhibitors. Computational techniques have played a critical role in accelerating research in this area. However, most previous computational studies were based solely on ligand information. In the present work, we describe the application of one of our recently developed receptor-based 3D-quantitative structure activity relationships (QSAR) methods, i.e. comparative residue interaction analysis (CoRIA), in exploring the events involved in ligand-integrase binding. In this methodology, the non-bonded interaction energies (van der Waals and Coulombic) of the inhibitors with individual active site residues of the integrase enzyme are calculated and, along with other thermodynamic descriptors, are correlated with biological activity using chemometric methods. Different combinations of descriptors were used to develop three types of QSAR models, all of which were found to be statistically significant by internal and external validation. This is the first report of such a dedicated receptor-based 3D-QSAR approach being applied to comprehend the integrase-inhibitor recognition process. In addition, the study was performed on 13-different series of inhibitors, thereby exploring the most structurally diverse data set ever used in understanding the inhibition of HIV-1 integrase. The major advantage of this technique is that it can quantitatively extract crucial residues and identify the nature of interactions between the ligand and receptor that modulate activity. The models suggest that Asp64, Thr66, Val77, Asp116, Glu152 and Lys159 are the key residues influencing the binding of ligands with the integrase enzyme, and the majority of these results are in line with earlier studies. The approach facilitates easy lead-to-hit conversion and design of novel inhibitors by optimisation of the interaction of ligands with these specific residues of the integrase enzyme.
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