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Updated: May 15, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Homology modeling, molecular docking and MD simulations study of 6,7-dimethoxy-1,2,3,4-tetrahydroisoquinoline
Vishakha Chaudhary1,2, Shubhra Chaturvedi2, Anju Wadhwa3
1Kirori Mal College, University of Delhi, North Campus, University Enclave, Delhi, India.
Abstract:
The sigma-2 receptor has gathered attention as a promising target for cancer diagnosis and therapy since biochemical studies have evidenced the presence of the receptor in highly proliferating tumor cells. Computational drug design can help create targeted ligands against sigma-2, but a three-dimensional receptor structure is required as input. This study aims to develop a homology model of the human sigma-2 receptor. The template protein bovine sigma-2 (7m93) was aligned with the query sequence (Q5BJF2) to generate five models. These models were screened using potential energy parameters and molecular dynamics, with the model having the lowest energy and maximum stability being validated using stereo chemical parameters. The accepted model had 95.9% residues in allowed regions of the Ramachandran plot and an overall quality factor of 87.2611%. The model was tested using correlation analysis (R2= 0.744) of docking score and literature values of pKi. In addition, the model is used to understand the binding pattern of emerging selective 6,7-dimethoxy-1,2,3,4-tetrahydroisoquinoline scaffold-based derivatives for designing ligands. The molecular dynamics studies of the model and ligand-bound model were performed for 100 ns to study the stability of the complexes, and the interactions compared with the known antagonist of sigma 2.
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