Wang C E
Artificial Intelligence Lab, MIT, 545 Technology Square, Cambridge, MA 02139-3539, USA.
Acta Crystallogr D Biol Crystallogr. 2000 Dec;56(Pt 12):1591-611. doi: 10.1107/s0907444900011859.
Building a protein model from the initial three-dimensional electron-density distribution (density map) is an important task in X-ray crystallography. This problem is computationally challenging because proteins are extremely flexible. The algorithm ConfMatch is a global real-space fitting procedure in torsion-angle space. It solves this 'map-interpretation' problem by matching a detailed conformation of the molecule to the density map (conformational matching). This 'best-match' structure is defined as one which maximizes the sum of the density at atom positions. ConfMatch is a practical systematic algorithm based on a branch-and-bound search. The most important idea of ConfMatch is an efficient method for computing accurate bounds. ConfMatch relaxes the conformational matching problem, a problem which can only be solved in exponential time, into one which can be solved in polynomial time. The solution to the relaxed problem is a guaranteed upper bound for the conformational matching problem. In most empirical cases, these bounds are accurate enough to prune the search space dramatically, enabling ConfMatch to solve structures with more than 100 free dihedral angles. Experiments have shown that ConfMatch may be able to automate the interpretation of density maps of small proteins.
根据初始三维电子密度分布(密度图)构建蛋白质模型是X射线晶体学中的一项重要任务。由于蛋白质具有极高的灵活性,这个问题在计算上具有挑战性。ConfMatch算法是一种在扭转角空间中的全局实空间拟合程序。它通过将分子的详细构象与密度图进行匹配(构象匹配)来解决这个“图谱解释”问题。这种“最佳匹配”结构被定义为使原子位置处的密度总和最大化的结构。ConfMatch是一种基于分支定界搜索的实用系统算法。ConfMatch最重要的思想是一种计算精确边界的有效方法。ConfMatch将构象匹配问题(一个只能在指数时间内解决的问题)放宽为一个可以在多项式时间内解决的问题。放宽问题的解决方案是构象匹配问题的一个有保证的上限。在大多数实际情况下,这些边界足够精确,可以大幅削减搜索空间,使ConfMatch能够解决具有100多个自由二面角的结构。实验表明,ConfMatch或许能够自动解释小蛋白质的密度图。