遇见数据集

Capturing Protein–Ligand Recognition Pathways in Coarse-Grained Simulation

收藏
Figshare2020-06-10 更新2026-04-28 收录
官方服务:

资源简介:

Protein–ligand recognition is dynamic and complex. A key approach in deciphering the mechanism underlying the recognition process is to capture the kinetic process of the ligand in its act of binding to its designated protein cavity. Toward this end, ultralong all-atom molecular dynamics simulation has recently emerged as a popular method of choice because of its ability to record these events at high spatial and temporal resolution. However, success via this route comes at an exorbitant computational cost. Herein, we demonstrate that coarse-grained models of the protein, when systematically optimized to maintain its tertiary fold, can capture the complete process of spontaneous protein–ligand binding from bulk media to the cavity at crystallographic precision and within wall clock time that is orders of magnitude shorter than that of all-atom simulations. The exhaustive sampling of ligand exploration in protein and solvent, harnessed by coarse-grained simulation, leads to elucidation of new ligand recognition pathways and discovery of non-native binding poses.

创建时间:
2020-06-10
二维码
社区交流群
二维码
科研交流群
商业服务