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

Bioinformatics. 2002 Mar;18(3):498-9. doi: 10.1093/bioinformatics/18.3.498.

Abstract

Motivation: beta-turns play an important role from a structural and functional point of view. beta-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 beta-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 beta-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 beta-TURNS e.g. type I, I', II, II', VI, VIII and non-specific. This server assists the users in predicting the consensus beta-TURNS in a protein.

Availability: The server is accessible from http://imtech.res.in/raghava/betatpred/

MeSH terms

  • Algorithms*
  • Amino Acid Sequence
  • Computing Methodologies
  • Internet
  • Models, Molecular*
  • Models, Statistical*
  • Molecular Sequence Data
  • Protein Structure, Secondary
  • Proteins / chemistry*
  • Software*

Substances

  • Proteins