Swain M T, Kemp G J
Department of Computing Science, King's College, University of Aberdeen, Aberdeen, Scotland AB24 3UE, UK.
Comput Chem. 2001 Dec;26(1):85-95. doi: 10.1016/s0097-8485(01)00103-6.
Side-chain placement is an important sub-task in protein modelling. Selecting conformations for side-chains is a difficult problem because of the large search space to be explored. This problem can be addressed using constraint logic programming (CLP), which is an artificial intelligence technique developed to solve large combinatorial search problems. The side-chain placement problem can be expressed as a CLP program in which rotamer conformations are used as values for finite domain variables, and bad steric contacts involving rotamers are represented as constraints. This paper introduces the concept of null rotamers, and shows how these can be used in implementing a novel iterative approach. We present results that compare the accuracy of models constructed using different rotamer libraries and different domain variable enumeration heuristics. The results obtained using this CLP-based approach compare favourably with those obtained by other methods.
侧链放置是蛋白质建模中的一个重要子任务。由于需要探索的搜索空间很大,为侧链选择构象是一个难题。这个问题可以使用约束逻辑编程(CLP)来解决,CLP是一种为解决大型组合搜索问题而开发的人工智能技术。侧链放置问题可以表示为一个CLP程序,其中旋转异构体构象用作有限域变量的值,涉及旋转异构体的不良空间接触表示为约束。本文介绍了空旋转异构体的概念,并展示了如何将其用于实现一种新颖的迭代方法。我们给出了使用不同旋转异构体库和不同域变量枚举启发式方法构建的模型准确性比较结果。使用这种基于CLP的方法获得的结果与其他方法获得的结果相比具有优势。