volume 2 issue 1 publication number 3

Computational analysis of new generation TSPO ligands

Publication typeJournal Article
Publication date2025-02-03
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ISSN30049350
Abstract
Molecular docking, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity), and QSAR (Quantitative Structural Activity Relationships) profiling are integral components of drug discovery and development. In this study, we have utilized SeeSAR™ modules, BioSolveIT (FlexX docking) to evaluate the binding affinity of a series of 33 potential ligands for 18 kDa translocator protein (TSPO). Additionally, ADMET prediction tools, including SwissADME, ADMETlab 2.0, and ADMEai, were used to investigate the pharmacokinetic properties. Regression analysis tools were used to predict the structural activity relationships of these ligands. Out of 33 compounds, eleven molecules exhibited strong binding affinity toward TSPO (PDB ID: 4RYI), with binding free energies ranging from -65 to -50 kcal/mol. The key residues responsible for their binding were TRP A:51, GLN A:94, MET A: 3, SER A:22, PHE A:12, LYS B:37, ARG A:29, GLY A:44, LYS B:32 in the active site primarily through van der Waals forces. Other important hydrophobic interactions involving residues LEU B:60, PHE A:12, PHE A:11, PHE B:11, TYR A:15, TYR B:15, VAL B:53, LEU B:57, ILE A:8, ILE B:8. ADMET properties like logBB and Log S indicated favourable blood brain barrier permeability and appropriate aqueous solubility profiles. QSAR studies showed a good correlation between Caco 2 and BBB. In summary this study identified several promising ligands with strong binding affinity toward TSPO with favourable molecular properties, and potential for good bioavailability. Further research and experimentation are required to validate the efficacy and safety of these compounds as viable pharmaceutical candidates in drug development and exploration.
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Singh V. K. et al. Computational analysis of new generation TSPO ligands // Discover Molecules. 2025. Vol. 2. No. 1. 3
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Singh V. K., Azad P., Tiwari A. K. Computational analysis of new generation TSPO ligands // Discover Molecules. 2025. Vol. 2. No. 1. 3
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TY - JOUR
DO - 10.1007/s44345-025-00009-9
UR - https://link.springer.com/10.1007/s44345-025-00009-9
TI - Computational analysis of new generation TSPO ligands
T2 - Discover Molecules
AU - Singh, Vijay Kumar
AU - Azad, Pragati
AU - Tiwari, Anjani Kumar
PY - 2025
DA - 2025/02/03
PB - Springer Nature
IS - 1
VL - 2
SN - 3004-9350
ER -
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@article{2025_Singh,
author = {Vijay Kumar Singh and Pragati Azad and Anjani Kumar Tiwari},
title = {Computational analysis of new generation TSPO ligands},
journal = {Discover Molecules},
year = {2025},
volume = {2},
publisher = {Springer Nature},
month = {feb},
url = {https://link.springer.com/10.1007/s44345-025-00009-9},
number = {1},
pages = {3},
doi = {10.1007/s44345-025-00009-9}
}