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<p>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 <b>SeeSAR</b><sup><b>™</b></sup><b> modules, BioSolveIT (FlexX docking)</b> to evaluate the binding affinity of a series of 33 potential ligands for 18&#xa0;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&#xa0;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.</p>

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Computational analysis of new generation TSPO ligands

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月3日

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  • Vijay Kumar Singh,
  • Pragati Azad,
  • Anjani Kumar Tiwari

摘要

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.