Analysis and prediction of the different types of β-turn in proteins

C. M. Wilmot, J. M. Thornton

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β-Turns have been extracted from 59 non-identical proteins (resolution 2 Å) using the standard criterion that the distance between Cα(i) and Cα(i + 3) is less than 7 Å (1 Å = 0·1 nm). The β-turns have been classified, using φ, ψ angles, into seven conventional turn types (I, I′, II, II′, IV, VIa, VIb) and a new class of β-turn, designated type VIII, in which the central residues (i + 1, i + 2) adopt an αRβ conformation. Most β-turn types are found in various topological environments, with the exception of I′ and II′ β-turns, where 83% and 50%, respectively, are found in β-hairpins. Sufficient data have been gathered to enable, for the first time, the separate statistical analysis of type I and II β-turns. The two turn types have been shown to be strikingly different in their sequence preferences. Type I turns favour Asp, Asn, Ser and Cys at i; Asp, Ser, Thr and Pro at i + 1; Asp, Ser, Asn and Arg at i + 2; Gly, Trp and Met at i + 3, whilst type II turns prefer Pro at i + 1; Gly and Asn at i + 2; Gln and Arg at i + 3. These preferences have been explained by the specific side-chain interactions observed within the X-ray structures. The positional trends for type I and II β-turns have been incorporated into the simple empirical predictive algorithm originally developed by P. N. Lewis et al. The program has improved the positional prediction of β-turns, and has enhanced and extended the method by predicting the type of β-turn. Since the observed preferences reflect local interactions these predictions are applicable not only to proteins, but also to peptides, many of which are thought to contain β-turns.

Original languageEnglish (US)
Pages (from-to)221-232
Number of pages12
JournalJournal of Molecular Biology
Issue number1
StatePublished - Sep 5 1988

Bibliographical note

Funding Information:
We thank Dr Mike J. E. Sternberg, Dr Suhail Islam and the Protein Engineering Club for use and help with the Oracle Protein Structure Relational Database; Dr Mario Geyson, Malcolm McGregor and Mike Sutcliffe for useful discussions. C.W. is supported by a SERC studentship.

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