Ligand binding free energy landscapes at the tubulin colchicine site from coarse-grained metadynamics

Abstract

Accessing deeply buried binding sites remains a major challenge in structure-based drug discovery, where accurate description of both protein dynamics and ligand binding pathways is required. All-atom funnel metadynamics (AA-FMD) enables simulation of complete binding processes but is computationally demanding. By adopting the Martini 3 force field, coarse-grained funnel metadynamics (CG-FMD) substantially reduces computational requirements while retaining enhanced sampling capabilities. In this work, we assess the capability of CG-FMD to model ligand recognition at the deeply buried colchicinoids site of the tubulin αβ-heterodimer, a multisite protein of strategic importance. We investigated the binding of colchicine, podophyllotoxin and combretastatin-A4, recovering free energy profiles with improved statistical convergence compared to AA-FMD. These results suggest that CG-FMD is an efficient, physics-based approach for probing ligand binding to the deeply buried colchicine site of tubulin, motivating future studies on other challenging binding sites. Accessing deeply buried binding sites is a significant challenge in structure-based drug discovery, requiring precise modeling of protein dynamics and ligand pathways. Here, the authors demonstrate that coarse-grained funnel metadynamics (CG-FMD) effectively models ligand binding at the colchicine site of tubulin, offering improved computational efficiency and statistical convergence.