Improving the accuracy of pose prediction by incorporating symmetry-related molecules

Abstract

Accurate prediction of biologically relevant binding poses is crucial for the success of computer-aided drug development. In this study, we describe a general strategy to enhance the precision of pose prediction in molecular docking by incorporating symmetry-related molecules (SRMs). Our objective was to demonstrate the significant impact of SRMs on the accuracy of pose prediction. To achieve this, we evaluated our method on high-quality protein-ligand complex structures, focusing on the presence and absence of SRMs during molecular docking studies. We have extracted the co-crystal ligands from the selected crystal structure and were redocked in presence and absence of SRM to assess their influence. Additionally, we calculated the free energy of the docked poses using the Molecular Mechanics Generalized Born Surface Area (MM-GBSA) method, comparing the results in the presence and absence of SRMs. The findings revealed that redocking performed in the presence of SRMs significantly improved the prediction of biologically significant/crystallographically relevant poses. Consequently, our proposed strategy offers a robust method for enhancing pose prediction in current molecular docking programs, potentially leading to more effective and reliable drug development processes.