Prediction of enzyme inhibition (IC50) using a combination of protein-ligand docking and semiempirical quantum mechanics
Abstract
CONTEXT: The ability to predict the relative binding energies of ligands to a biological receptor would be of great value in drug discovery. However, accurately calculating the predicted binding energies is limited by the high accuracy required, by the presence of multiple minima on the potential energy surface, and by issues specific to the intrinsic properties of the binding site, such as details of the geometry of the ligand-protein complex. To address these issues, a systematic analysis of potential sources of error was carried out which resulted in a few relatively small changes being made to the MOPAC program.
METHODS: A set of 77 ligands was constructed for which experimentally determined IC50 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 IC50 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.
How strong is the evidence?
Evidence Hub reads this as a experimental / empirical study, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
Read the paper
Related studies
- Chaos and quantum thermalization
- The Dalton quantum chemistry program system
- Quantum dots: synthesis, bioapplications, and toxicity
- Cord Blood Leptin and Adiponectin as Predictors of Adiposity in Children at 3 Years of Age: A Prospective Cohort Study
- A Guide to In Silico Drug Design
- Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.