Department of Information Studies, University of Sheffield, Regent Court, 211 Portobello Street, Sheffield S1 4DP, United Kingdom.
J Chem Inf Model. 2009 Dec;49(12):2761-73. doi: 10.1021/ci9002816.
Two methods are described for biasing conformational search during pharmacophore elucidation using a multiobjective genetic algorithm (MOGA). The MOGA explores conformation on-the-fly while simultaneously aligning a set of molecules such that their pharmacophoric features are maximally overlaid. By using a clique detection method to generate overlays of precomputed conformations to initialize the population (rather than starting from random), the speed of the algorithm has been increased by 2 orders of magnitude. This increase in speed has enabled the program to be applied to greater numbers of molecules than was previously possible. Furthermore, it was found that biasing the conformations explored during search time to those found in the Cambridge Structural Database could also improve the quality of the results.
描述了两种方法，用于在使用多目标遗传算法（MOGA）进行药效团阐明时对构象搜索进行偏置。MOGA 在实时探索构象的同时，对一组分子进行对齐，以使它们的药效团特征最大限度地重叠。通过使用团块检测方法生成预计算构象的重叠来初始化种群（而不是从随机开始），算法的速度提高了 2 个数量级。这种速度的提高使程序能够应用于比以前更多的分子。此外，还发现偏置搜索过程中探索的构象使其偏向于剑桥结构数据库中的构象，也可以提高结果的质量。
