BetaTPred: prediction of β-TURNS in a protein using statistical algorithms

摘要

Motivation: β-turns play an important role from a structural and functional point of view. β-turns are the most common type of non-repetitive structures in proteins and comprise on average, 25% of the residues. In the past numerous methods have been developed to predict β-turns in a protein. Most of these prediction methods are based on statistical approaches. In order to utilize the full potential of these methods, there is a need to develop a web server. Results: This paper describes a web server called BetaTPred, developed for predicting β-TURNS in a protein from its amino acid sequence. BetaTPred allows the user to predict turns in a protein using existing statistical algorithms. It also allows to predict different types of β-TURNS e.g. type I, I', II, II', VI, VIII and non-specific. This server assists the users in predicting the consensus β-TURNS in a protein.