Prediction of enzyme inhibition (IC50) using a combination of protein–ligand docking and semiempirical quantum mechanics

A set of 77 ligands was constructed for which experimentally determined IC<sub>50</sub> values were available. For each of the ligands, prediction of the protein-ligand interaction energy was carried out in two distinct stages. In the first stage, the Protein-Ligand docking program GOLD was used to generate several distinct conformations of the ligand bound to a protein. The geometries of these systems were then optimised using the MOPAC program. A comparison of the relative binding energies of the ligands with the reported IC<sub>50</sub> values showed a very poor predictive power. By partitioning the ligand set into two subsets, and eliminating six ligands that were inconsistent with the experimental results, a large increase in accuracy was obtained.

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Publication Details

Journal
Journal of Molecular Modeling
Published
2025-07-12
DOI
https://doi.org/10.1007/s00894-025-06423-7
Citations
3
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
4.51
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article

Prediction of enzyme inhibition (IC50) using a combination of protein–ligand docking and semiempirical quantum mechanics

Jason C. Cole, Robert C. Glen, James J. P. Stewart
3 citations
Journal of Molecular Modeling
Computational Drug Discovery Methods
4.51
article

Prediction of enzyme inhibition (IC50) using a combination of protein–ligand docking and semiempirical quantum mechanics

Jason C. Cole, Robert C. Glen, James J. P. Stewart
article en
3 citations

Abstract

A set of 77 ligands was constructed for which experimentally determined IC<sub>50</sub> values were available. For each of the ligands, prediction of the protein-ligand interaction energy was carried out in two distinct stages. In the first stage, the Protein-Ligand docking program GOLD was used to generate several distinct conformations of the ligand bound to a protein. The geometries of these systems were then optimised using the MOPAC program. A comparison of the relative binding energies of the ligands with the reported IC<sub>50</sub> values showed a very poor predictive power. By partitioning the ligand set into two subsets, and eliminating six ligands that were inconsistent with the experimental results, a large increase in accuracy was obtained.

Journal of Molecular ModelingVol. 31(8)
University of Cambridge (GB), Hammersmith Hospital (GB), Cambridge Crystallographic Data Centre (GB), St Mary's Hospital (AU)
Zero hunger
Openalex Percentile: Top 5%
Computational Drug Discovery Methods
4.51
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