A genetic algorithm for the ab initio phasing of icosahedral viruses.
A genetic algorithm for the ab initio phasing of icosahedral viruses.
复制标题
用于二十面体病毒从头开始定相的遗传算法。
DOI：
10.1107/s0907444995011620
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发表时间：
1996
期刊：
影响因子：
--
通讯作者：
Filman,DJ
中科院分区：
文献类型：
--
作者：
Miller,ST;Hogle,JM;Filman,DJ
遗传算法已被研究作为从头定相的低分辨率X射线衍射数据从二十面体病毒晶体的计算工具。在没有预先知道病毒的形状并且仅近似知道其大小的情况下，病毒可以被建模为近似四面体排列的晶格点的短列表的对称扩展，所述晶格点粗略但均匀地对二十面体唯一体积进行采样。格点的数量取决于在工作分辨率极限下对非冗余信息内容的估计。该参数化允许模型评估计算的简单矩阵公式化，从而导致对可能的模型的空间的高效调查。最初，每个参数一位就足够了，因为将1和0分配给格点会产生物理上合理的病毒低分辨率图像。通过调查确定的最佳候选解决方案进行了改进，以放松建模粗糙度所施加的约束，然后选择在所有分辨率范围内基于强度的统计数据相对较好的试验。这产生了一个可接受的起始点，为约一半的时间的直接相位扩展的基于时间的。将选择标准直接纳入遗传算法的适应度函数，以提高效率进行了讨论。
Genetic algorithms have been investigated as computational tools for the de novo phasing of low-resolution X-ray diffraction data from crystals of icosahedral viruses. Without advance knowledge of the shape of the virus and only approximate knowledge of its size, the virus can be modeled as the symmetry expansion of a short list of nearly tetrahedrally arranged lattice points which coarsely, but uniformly, sample the icosahedrally unique volume. The number of lattice points depends on an estimate of the non-redundant information content at the working resolution limit. This parameterization permits a simple matrix formulation of the model evaluation calculation, resulting in a highly efficient survey of the space of possible models. Initially, one bit per parameter is sufficient, since the assignment of ones and zeros to the lattice points yields a physically reasonable low-resolution image of the virus. The best candidate solutions identified by the survey are refined to relax the constraints imposed by the coarseness of the modeling, and then trials whose intensity-based statistics are comparatively good in all resolution ranges are chosen. This yields an acceptable starting point for symmetry-based direct phase extension about half the time. Improving efficiency by incorporating the selection criterion directly into the genetic algorithm's fitness function is discussed.