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An efficient mechanism for prediction of protein-ligand interactions based on analysis of protein tertiary substructures

机译:基于蛋白质三级亚结构分析的预测蛋白质-配体相互作用的有效机制

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Analysis of protein-ligand interactions is a fundamental issue in drug design. As the detailed and accurate analysis of protein-ligand interactions involves calculation of binding free energy based on thermodynamics and even quantum mechanics, which is highly expensive in terms of computing time, conformational and structural analysis of proteins and ligands has been widely employed as a screening process in computer-aided drug design. In this paper, an efficient mechanism for identifying possible protein-ligand interactions based on analysis of protein tertiary substructures is proposed. In one experiment reported in this paper, the proposed prediction mechanism has been exploited to obtain some clues about a hypothesis that the biochemists have been speculating. The main distinction in the design of the prediction mechanism is the filtering process incorporated to expedite the analysis. The filtering process extracts the residues located in a cave of the protein tertiary structure for analysis and operates with O(nlogn) time complexity, where n is the number of residues in the protein. In comparison, the /spl alpha/hull algorithm, which is a widely used algorithm in computer graphics for identifying those instances that are on the contour of a 3-dimensional object, features O(n/sup 2/) time complexity. Experimental results show that the filtering process presented in this paper is able to speed up the analysis by a factor ranging from 3.11 to 9.79 times.
机译:蛋白质-配体相互作用的分析是药物设计中的一个基本问题。由于对蛋白质-配体相互作用的详细而准确的分析涉及基于热力学甚至量子力学的结合自由能的计算,这在计算时间方面非常昂贵,因此蛋白质和配体的构象和结构分析已广泛用于筛选计算机辅助药物设计中的过程。本文提出了一种有效的机制,用于基于蛋白质三级亚结构的分析来识别可能的蛋白质-配体相互作用。在本文报道的一项实验中,已利用拟议的预测机制来获得有关生物化学家正在推测的假说的一些线索。预测机制设计中的主要区别是合并了过滤过程以加快分析速度。过滤过程会提取位于蛋白质三级结构洞穴中的残基以进行分析,并以O(nlogn)时间复杂度进行操作,其中n是蛋白质中的残基数。相比之下,/ spl alpha / hull算法是计算机图形学中用于识别3维对象轮廓上的那些实例的一种广泛使用的算法,具有O(n / sup 2 /)时间复杂度。实验结果表明,本文提出的过滤过程能够使分析速度提高3.11倍至9.79倍。

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