Fox Chase Cancer Center, Philadelphia PA, United States of America.
Department of Computer and Information Sciences, Temple University, Philadelphia PA, United States of America.
PLoS Comput Biol. 2019 Mar 7;15(3):e1006844. doi: 10.1371/journal.pcbi.1006844. eCollection 2019 Mar.
Protein loops connect regular secondary structures and contain 4-residue beta turns which represent 63% of the residues in loops. The commonly used classification of beta turns (Type I, I', II, II', VIa1, VIa2, VIb, and VIII) was developed in the 1970s and 1980s from analysis of a small number of proteins of average resolution, and represents only two thirds of beta turns observed in proteins (with a generic class Type IV representing the rest). We present a new clustering of beta-turn conformations from a set of 13,030 turns from 1074 ultra-high resolution protein structures (≤1.2 Å). Our clustering is derived from applying the DBSCAN and k-medoids algorithms to this data set with a metric commonly used in directional statistics applied to the set of dihedral angles from the second and third residues of each turn. We define 18 turn types compared to the 8 classical turn types in common use. We propose a new 2-letter nomenclature for all 18 beta-turn types using Ramachandran region names for the two central residues (e.g., 'A' and 'D' for alpha regions on the left side of the Ramachandran map and 'a' and 'd' for equivalent regions on the right-hand side; classical Type I turns are 'AD' turns and Type I' turns are 'ad'). We identify 11 new types of beta turn, 5 of which are sub-types of classical beta-turn types. Up-to-date statistics, probability densities of conformations, and sequence profiles of beta turns in loops were collected and analyzed. A library of turn types, BetaTurnLib18, and cross-platform software, BetaTurnTool18, which identifies turns in an input protein structure, are freely available and redistributable from dunbrack.fccc.edu/betaturn and github.com/sh-maxim/BetaTurn18. Given the ubiquitous nature of beta turns, this comprehensive study updates understanding of beta turns and should also provide useful tools for protein structure determination, refinement, and prediction programs.
蛋白质环连接规则的二级结构,并包含 4 残基β转角,占环中残基的 63%。常用的β转角分类(I 型、I'型、II 型、II'型、VIa1 型、VIa2 型、VIb 型和 VIII 型)是在 20 世纪 70 年代和 80 年代从少数平均分辨率的蛋白质分析中发展起来的,仅代表在蛋白质中观察到的β转角的三分之二(通用类 IV 型代表其余部分)。我们从 1074 个超高分辨率蛋白质结构(≤1.2Å)中的 13030 个转角的集合中提出了一种新的β转角构象聚类。我们的聚类是通过将 DBSCAN 和 k-medoids 算法应用于这个数据集,并使用通常应用于每个转角的第二和第三个残基的二面角集的定向统计中的度量来得到的。与常用的 8 种经典转角类型相比,我们定义了 18 种转角类型。我们提出了一种新的用于所有 18 种β转角类型的 2 字母命名法,使用两个中心残基的 Ramachandran 区域名称(例如,Ramachandran 图谱左侧的“α”区域的“A”和“D”和右侧等效区域的“a”和“d”;经典的 I 型转角是“AD”转角,而 I' 型转角是“ad”)。我们确定了 11 种新的β转角类型,其中 5 种是经典β转角类型的子类型。收集和分析了环中β转角的最新统计信息、构象概率密度和序列特征。转角类型库 BetaTurnLib18 和跨平台软件 BetaTurnTool18 可从 dunbrack.fccc.edu/betaturn 和 github.com/sh-maxim/BetaTurn18 免费获得和重新分发,用于识别输入蛋白质结构中的转角。鉴于β转角的普遍存在,这项全面的研究更新了对β转角的理解,也应该为蛋白质结构确定、精修和预测程序提供有用的工具。