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Updated: Nov 5, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
On the use of electronegativity and electron affinity based pseudo-molecular field descriptors in developing
Pushkar D Kunde1,2, Sudha Ramkumar3, Sanjay P Kamble1,2
1Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory (CSIR-NCL), Pune, India.
Abstract:
For quantitative structure-activity relationship (QSAR) modeling in ligand-based drug discovery programs, pseudo-molecular field (PMF) descriptors using intrinsic atomic properties, namely, electronegativity and electron affinity are studied. In combination with partial least squares analysis and Procrustes transformation, these PMF descriptors were employed successfully to develop correlations that predict the activities of target protein inhibitors involved in various diseases (cancer, neurodegenerative disorders, HIV, and malaria). The results show that the present QSAR approach is competitive to existing QSAR models. In order to demonstrate the use of this algorithm, we present results of screening naturally occurring molecules with unknown bioactivities. The pIC50 predictions can screen molecules that have desirable activity before assessment by docking studies.
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