构象异构
标杆管理
算法
稳健性(进化)
计算机科学
数学
化学
分子
基因
营销
有机化学
业务
生物化学
作者
Nils‐Ole Friedrich,Christina de Bruyn Kops,Florian Flachsenberg,Kai Sommer,Matthias Rarey,Johannes Kirchmair
标识
DOI:10.1021/acs.jcim.7b00505
摘要
2017, 57, 529-539). For commercial algorithms, the median minimum root-mean-square deviations measured between protein-bound ligand conformations and ensembles of a maximum of 250 conformers are between 0.46 and 0.61 Å. Commercial conformer ensemble generators are characterized by their high robustness, with at least 99% of all input molecules successfully processed and few or even no substantial geometrical errors detectable in their output conformations. The RDKit distance geometry algorithm (with minimization enabled) appears to be a good free alternative since its performance is comparable to that of the midranked commercial algorithms. Based on a statistical analysis, we elaborate on which algorithms to use and how to parametrize them for best performance in different application scenarios.
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