Anzai Risa, Asami Yoshiki, Inoue Waka, Ueno Hina, Yamada Koya, Okada Tetsuji
Department of Life Science, Gakushuin University, 1-5-1 Mejiro, Toshima-ku, Tokyo 171-8588, Japan.
Heliyon. 2018 Feb 1;4(1):e00510. doi: 10.1016/j.heliyon.2018.e00510. eCollection 2018 Jan.
Systematic analysis of the statistical and dynamical properties of proteins is critical to understanding cellular events. Extraction of biologically relevant information from a set of high-resolution structures is important because it can provide mechanistic details behind the functional properties of protein families, enabling rational comparison between families. Most of the current structural comparisons are pairwise-based, which hampers the global analysis of increasing contents in the Protein Data Bank. Additionally, pairing of protein structures introduces uncertainty with respect to reproducibility because it frequently accompanies other settings for superimposition. This study introduces intramolecular distance scoring for the global analysis of proteins, for each of which at least several high-resolution structures are available. As a pilot study, we have tested 300 human proteins and showed that the method is comprehensively used to overview advances in each protein and protein family at the atomic level. This method, together with the interpretation of the model calculations, provide new criteria for understanding specific structural variation in a protein, enabling global comparison of the variability in proteins from different species.
对蛋白质的统计和动力学特性进行系统分析对于理解细胞事件至关重要。从一组高分辨率结构中提取生物学相关信息很重要，因为它可以提供蛋白质家族功能特性背后的机制细节，从而实现家族之间的合理比较。当前大多数结构比较都是基于成对的，这阻碍了对蛋白质数据库中不断增加的内容进行全局分析。此外，蛋白质结构的配对在可重复性方面引入了不确定性，因为它经常伴随着其他叠加设置。本研究引入分子内距离评分用于蛋白质的全局分析，每种蛋白质至少有几个高分辨率结构可用。作为一项初步研究，我们测试了300种人类蛋白质，并表明该方法可全面用于在原子水平上概述每种蛋白质和蛋白质家族的进展。该方法与模型计算的解释一起，为理解蛋白质中的特定结构变异提供了新的标准，从而能够对来自不同物种的蛋白质的变异性进行全局比较。
