Investigation of Protein-Ligand Interaction Using an Intermolecular Distance-Based Descriptor in Molecular Docking

Document Type : Original Article

Authors

School of Chemistry, Damghan University, Damghan, Iran

Abstract

Molecular docking is a key tool in structure-based drug design, extensively used to study biomolecular interactions and mechanisms. Molecular docking reliability is often evaluated using RMSD (Root Mean Square Deviation) compared to experimental structures, though such data is frequently unavailable in practice. Therefore, scoring functions can be used as an alternative to assess protein-ligand docking results. In this study, a simple computational scoring function for protein-ligand interaction was developed, based on calculating the sum of pairwise distances between ligand atoms bound in the active site and protein atoms. The distance matrix can be used to calculate a distance-based score (DB-Score). To better evaluate performance, we used experimentally determined values for IC_50 GRK6 (G protein-coupled receptor kinase 6) inhibitors to assess scoring and ranking accuracy compared to the AutoDock Vina program performances. Extensive experiments on this dataset demonstrate that the distance-based scoring function outperforms the conventional AutoDock Vina score in ranking and scoring. Pearson’s correlation coefficients for AutoDock Vina and our defined score against experimentally determined GRK6-pIC_50 were 0.09 and 0.76, respectively. Furthermore, the effectiveness of DB-Score was evaluated using the v2016-core subset of the PDBbind database. On the CASF-2016 benchmark, DB-Score achieved a Pearson’s r of 0.62, demonstrating surprisingly good performance.

Graphical Abstract

Investigation of Protein-Ligand Interaction Using an Intermolecular Distance-Based Descriptor in Molecular Docking

Keywords


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