Prediction and classification of alpha-turn types

Tight turns play an important role in globular proteins from both the structural and functional points of view. Of tight turns, beta-turns and gamma-turns have been extensively studied, but alpha-turns were little investigated. Recently, a systematic search for alpha-turns was conducted by V. Pavone et al. [(1996) Biopolymers, Vol. 38, pp. 705-721] from 190 proteins (221 protein chains). They found 356 alpha-turns that were classified into nine different types according to their backbone trajectory features. In view of this new discovery, a sequence-coupled model based on Markov chain theory is proposed for predicting the alpha-turn types in proteins. The high rates of correct prediction by resubstitution test and jackknife test imply that that the formation of different alpha-turn types is evidently correlated with the sequence of a pentapeptide, and hence can be approximately predicted based on the sequence information of the pentapeptide alone, although the role of its interaction with the other part of a protein cannot be completely ignored. The algorithm presented here can also be used to conduct the prediction in which a distinction between alpha-turns and non-alpha-turns is also required.