Offman Marc N, Fitzjohn Paul W, Bates Paul A
Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, Lincoln's Inn Fields Laboratories London, WC2A 3PX, UK.
Bioinformatics. 2006 Aug 1;22(15):1838-45. doi: 10.1093/bioinformatics/btl192. Epub 2006 May 16.
A wide variety of methods for the construction of an atomic model for a given amino acid sequence are known, the more accurate being those that use experimentally determined structures as templates. However, far fewer methods are aimed at refining these models. The approach presented here carefully blends models created by several different means, in an attempt to combine the good quality regions from each into a final, more refined, model.
We describe here a number of refinement operators (collectively, 'move-set') that enable a relatively large region of conformational space to be searched. This is used within a genetic algorithm that reshuffles and repacks structural components. The utility of the move-set is demonstrated by introducing a cost function, containing both physical and other components guiding the input structures towards the target structure. We show that our move-set has the potential to improve the conformation of models and that this improvement can be beyond even the best template for some comparative modelling targets.
The populus software package and the source code are available at http://bmm.cancerresearchuk.org/~offman01/populus.html.
已知有多种方法可用于为给定的氨基酸序列构建原子模型，其中更精确的方法是使用实验确定的结构作为模板。然而，旨在优化这些模型的方法要少得多。本文提出的方法精心融合了通过几种不同方式创建的模型，试图将每个模型的高质量区域组合成一个最终的、更精细的模型。
我们在此描述了一些优化算子（统称为“移动集”），这些算子能够搜索相对较大的构象空间区域。这在一种遗传算法中使用，该算法对结构组件进行重新排列和重新包装。通过引入一个成本函数来证明移动集的效用，该成本函数包含引导输入结构趋向目标结构的物理和其他组件。我们表明，我们的移动集有潜力改善模型的构象，并且对于某些比较建模目标，这种改善甚至可能超过最佳模板。
populus软件包和源代码可在http://bmm.cancerresearchuk.org/~offman01/populus.html获得。
