Comprehensive Evaluation of End-Point Free Energy Methods in DNA–Ligand Interaction Predictions

终点 DNA 能量(信号处理) 点(几何) 配体(生物化学) 化学 生物系统 计算生物学 计算机科学 生物 数学 统计 生物化学 几何学 实时计算 受体
作者
Cuiyu Li,Hongyan Du,Chengwei Zhang,Wanying Huang,Xujun Zhang,Tianyue Wang,Dejun Jiang,Tingjun Hou,Ercheng Wang
出处
期刊:Journal of Chemical Information and Modeling [American Chemical Society]
卷期号:65 (4): 2014-2025 被引量:4
标识
DOI:10.1021/acs.jcim.4c01947
摘要

Deoxyribonucleic acid (DNA) serves as a repository of genetic information in cells and is a critical molecular target for various antibiotics and anticancer drugs. A profound understanding of small molecule interaction with DNA is crucial for the rational design of DNA-targeted therapies. While the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) approaches have been well established for predicting protein-ligand binding, their application to DNA-ligand interactions has been less explored. In this study, we systematically investigated the binding of 13 diverse small molecules to DNA, evaluating the accuracy of DNA-ligand interaction predictions across different solvation approaches, interior dielectric constants (εin), and molecular force fields. Our results demonstrate that MM/PBSA, using energy-minimized structures (the bsc1 force field and εin = 20), provides the best correlation (Rp = -0.742) with experimental binding affinities, surpassing the performance of rDock scoring functions (best Rp = -0.481). Notably, the interior dielectric constant was found to significantly impact DNA-ligand binding free energy predictions, especially for MM/PBSA. Moreover, both MM/PBSA and MM/GBSA predictions (εin = 16 or 20) exhibited superior performance in distinguishing native-like binding modes within the top-10 poses from decoys, compared to the molecular docking tools used in this study. However, the popular docking software PLANTS demonstrates notable efficacy in predicting the top-1 binding pose. Given the considerably higher computational cost of MM/PBSA, MM/GBSA rescoring with higher εin = 16 or 20 is more efficient for recognizing the native-like binding poses for DNA-ligand systems. This study presents the first detailed exploration of end-point free energy calculations in the context of DNA-ligand interactions and offers valuable insights for the application of the MM/PB(GB)SA methods in this domain.
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