Thermal Titration Molecular Dynamics (TTMD): Not Your Usual Post-Docking Refinement

Molecular docking is one of the most widely used computational approaches in the field of rational drug design, thanks to its favorable balance between the rapidity of execution and the accuracy of provided results. Although very efficient in exploring the conformational degrees of freedom available to the ligand, docking programs can sometimes suffer from inaccurate scoring and ranking of generated poses. To address this issue, several post-docking filters and refinement protocols have been proposed throughout the years, including pharmacophore models and molecular dynamics simulations. In this work, we present the first application of Thermal Titration Molecular Dynamics (TTMD), a recently developed method for the qualitative estimation of protein-ligand unbinding kinetics, to the refinement of docking results. TTMD evaluates the conservation of the native binding mode throughout a series of molecular dynamics simulations performed at progressively increasing temperatures with a scoring function based on protein-ligand interaction fingerprints. The protocol was successfully applied to retrieve the native-like binding pose among a set of decoy poses of drug-like ligands generated on four different pharmaceutically relevant biological targets, including casein kinase 1 delta, casein kinase 2, pyruvate dehydrogenase kinase 2, and SARS-CoV-2 main protease.

Automated summary

Molecular docking is commonly used in rational drug design due to its rapid execution and accurate results. However, docking programs can sometimes have inaccuracies in scoring and ranking generated poses. To address this, researchers have proposed post-docking filters and refinement protocols, including pharmacophore models and molecular dynamics simulations. This study presents the application of Thermal Titration Molecular Dynamics (TTMD) to refine docking results by evaluating protein-ligand unbinding kinetics.