Brown W Michael, Vander Jagt David L
Department of Computational Biology, Sandia National Laboratories, Albuquerque, New Mexico 87123, USA.
J Chem Inf Comput Sci. 2004 Jul-Aug;44(4):1412-22. doi: 10.1021/ci049853r.
Traditionally, algorithms for binding site characterization or identification focus on the problem of identifying atoms within a macromolecule that might be responsible for ligand binding. In this manuscript, we focus on the binding pocket problem from a different perspective as a challenge of calculating an artificial binding pocket boundary that is sufficient to isolate binding pocket volume. The approach involves the calculation of a macromolecule encapsulating surface (MES) that separates binding pocket volume from outside space. We show that the MES can be used to increase the efficiency of flexible docking as implemented in AutoDock 3.0. The most significant improvement in docking efficiency is seen when the entire protein is searched and results show additional support for the use of AutoDock, in and of itself, as a feasible tool for binding-site identification for cases in which a protein ligand is known.
传统上,用于结合位点表征或识别的算法专注于识别大分子中可能负责配体结合的原子的问题。在本论文中,我们从不同的角度关注结合口袋问题,将其视为计算足以隔离结合口袋体积的人工结合口袋边界的挑战。该方法涉及计算将结合口袋体积与外部空间分隔开的大分子包封表面(MES)。我们表明,MES可用于提高AutoDock 3.0中实现的柔性对接效率。当搜索整个蛋白质时,对接效率有最显著的提高,结果显示进一步支持将AutoDock本身用作已知蛋白质配体情况下结合位点识别的可行工具。