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
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI