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SVM-BetaPred: Prediction of Right-Handed ß-Helix Fold from Protein Sequence Using SVM

  • Siddharth Singh
  • Krishnan Hajela
  • Ashwini Kumar Ramani
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4774)

Abstract

The right-handed single-stranded ß-helix proteins are characterized as virulence factors, allergens, toxins that are threat to human health. Identification of these proteins from amino acid sequence is of great importance as these proteins are potential targets for anti-bacterial and fungal agents. In this paper, support vector machine (SVM) has been used to predict the presence of ß-helix fold in protein sequences using dipeptide composition. An input vector of 400 dimensions for dipeptide compositions is used to search for the presence of putative rungs or coils, the conserved secondary structure, found in ß-helix proteins. An average accuracy of 89.2% with Matthew’s correlation coefficient of 0.75 is obtained in a 5-fold cross-validation technique. In addition, a PSSM was also used to score the query sequence of proteins identified as ß-helices by SVM. The method recognizes right-handed ß-helices with 100% sensitivity and 99.6% specificity on test set of known protein structures.

Keywords

ß-helix fold ß-sheet stacking pectate lyase fold recognition secondary structure Support Vector Machines SVM PSSM 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Siddharth Singh
    • 1
  • Krishnan Hajela
    • 2
  • Ashwini Kumar Ramani
    • 1
  1. 1.School of Computer Science 
  2. 2.School of Life Science, Devi Ahilya University, Khandwa Road, Indore-452001India

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