Handschuh S, Wagener M, Gasteiger J
Computer-Chemie-Centrum, Institut für Organische Chemie, Universität Erlangen-Nürnberg, Germany.
J Chem Inf Comput Sci. 1998 Mar-Apr;38(2):220-32. doi: 10.1021/ci970438r.
The superposition of three-dimensional structures is the first task in the evaluation of the largest common three-dimensional substructure of a set of molecules. This is an important step in the identification of a pharmacophoric pattern for molecules that bind to the same receptor. The superposition method described here combines a genetic algorithm with a numerical optimization method. A major goal is to adequately address the conformational flexibility of ligand molecules. The genetic algorithm optimizes in a nondeterministic process the size and the geometric fit of the substructures. The geometric fit is further improved by changing torsional angles combining the genetic algorithm and the directed tweak method. This directed tweak method is based on a numerical quasi-Newton optimization method. Only one starting conformation per molecule is necessary. Molecules having several rotatable bonds and quite different initial conformations are modified to find large structural similarities. A set of angiotensin II antagonists is investigated to illustrate the performance of the method.
三维结构的叠加是评估一组分子最大公共三维子结构的首要任务。这是识别与同一受体结合的分子的药效团模式的重要一步。这里描述的叠加方法将遗传算法与数值优化方法相结合。一个主要目标是充分解决配体分子的构象灵活性问题。遗传算法在一个非确定性过程中优化子结构的大小和几何匹配度。通过结合遗传算法和定向微调方法改变扭转角,进一步改善几何匹配度。这种定向微调方法基于一种数值拟牛顿优化方法。每个分子只需要一个起始构象。对具有多个可旋转键且初始构象差异很大的分子进行修改,以发现较大的结构相似性。研究了一组血管紧张素II拮抗剂来说明该方法的性能。