Molecular replacement by evolutionary search
Molecular replacement by evolutionary search
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DOI：
10.1107/s0907444901012458
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发表时间：
2001-10-01
影响因子：
2.2
通讯作者：
Bouzida, D
中科院分区：
文献类型：
--
作者：
Kissinger, CR;Gehlhaar, DK;Bouzida, D
随机搜索算法可以用来执行快速的六维分子替换搜索。已经开发出一种分子置换程序，该程序使用进化算法来同时优化搜索模型在单位细胞中的方向和位置。在这里，我们考察了该算法的性能及其对搜索模型质量和目标函数选择的依赖性。虽然进化搜索过程能够利用搜索模型找到仅代表目标分子总散射物质的一小部分的解，但搜索过程的效率高度依赖于搜索模型的质量。聚丙氨酸模型通常比全原子模型提供更好的搜索效率，即使在侧链位置已知的情况下也是如此。虽然搜索过程的成功并不高度依赖于用作目标函数的统计，但观测到的和计算的结构因子幅度之间的相关系数通常比R因子产生更好的搜索效率。另一种随机搜索过程，模拟退火法，提供了与进化搜索相似的整体性能。现在开始研究将进化搜索算法扩展到包括内部优化、搜索模型的选择和构建的方法。
Stochastic search algorithms can be used to perform rapid six-dimensional molecular-replacement searches. A molecular-replacement procedure has been developed that uses an evolutionary algorithm to simultaneously optimize the orientation and position of a search model in a unit cell. Here, the performance of this algorithm and its dependence on search model quality and choice of target function are examined. Although the evolutionary search procedure is capable of finding solutions with search models that represent only a small fraction of the total scattering matter of the target molecule, the efficiency of the search procedure is highly dependent on the quality of the search model. Polyalanine models frequently provide better search efficiency than all-atom models, even in cases where the side-chain positions are known with high accuracy. Although the success of the search procedure is not highly dependent on the statistic used as the target function, the correlation coefficient between observed and calculated structure-factor amplitudes generally results in better search efficiency than does the R factor. An alternative stochastic search procedure, simulated annealing, provides similar overall performance to evolutionary search. Methods of extending the evolutionary search algorithm to include internal optimization, selection and construction of the search model are now beginning to be investigated.