A new clustering and nomenclature for beta turns derived from high-resolution protein structures

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.

蛋白质环连接规则二级结构，其中包含4残基β转角（beta turn），这类结构占环中残基的63%。当前通用的β转角分类（I型、I’型、II型、II’型、VIa1型、VIa2型、VIb型以及VIII型）于20世纪70至80年代，通过对少量中等分辨率蛋白质的分析建立，仅涵盖了蛋白质中观测到的三分之二β转角，剩余类别由通用的IV型囊括。本研究基于1074个超高分辨率（≤1.2埃）蛋白质结构中的13030个转角数据，对β转角构象进行了全新聚类。我们采用方向统计学中常用的度量标准，针对每个转角第二、第三位残基的二面角（dihedral angle）集合进行计算，并将该度量应用于本数据集的DBSCAN与k-medoids聚类算法，以此完成聚类分析。相较于当前通用的8类经典转角类型，本研究定义了18种转角类型。我们针对全部18种β转角类型提出了全新的双字母命名法，以两个中心残基所在的拉马钱德兰区域（Ramachandran region）名称进行命名。例如，拉马钱德兰图（Ramachandran map）左侧的α区域对应‘A’与‘D’，右侧等效区域对应‘a’与‘d’；经典I型转角为‘AD’型转角，I’型转角则为‘ad’型转角。本研究共鉴定出11种新型β转角类型，其中5种为经典β转角类型的亚型。研究团队收集并分析了环区β转角的最新统计数据、构象概率密度以及序列特征谱。包含所有转角类型的数据库BetaTurnLib18，以及可识别输入蛋白质结构中转角的跨平台软件BetaTurnTool18，可从dunbrack.fccc.edu/betaturn与github.com/sh-maxim/BetaTurn18免费获取并重新分发。鉴于β转角广泛存在于蛋白质结构中，这项全面的研究更新了学界对β转角的认知，同时可为蛋白质结构测定、精修与预测程序提供实用工具。