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Journal of Structural and Functional Genomics

, Volume 12, Issue 4, pp 191–197 | Cite as

Prediction of metalloproteinase family based on the concept of Chou’s pseudo amino acid composition using a machine learning approach

  • Majid Mohammad Beigi
  • Mohaddeseh BehjatiEmail author
  • Hassan Mohabatkar
Article

Abstract

Matrix metalloproteinase (MMPs) and disintegrin and metalloprotease (ADAMs) belong to the zinc-dependent metalloproteinase family of proteins. These proteins participate in various physiological and pathological states. Thus, prediction of these proteins using amino acid sequence would be helpful. We have developed a method to predict these proteins based on the features derived from Chou’s pseudo amino acid composition (PseAAC) server and support vector machine (SVM) as a powerful machine learning approach. With this method, for ADAMs and MMPs families, an overall accuracy and Matthew’s correlation coefficient (MCC) of 95.89 and 0.90% were achieved respectively. Furthermore, the method is able to predict two major subclasses of MMP family; Furin-activated secreted MMPs and Type II trans-membrane; with MCC of 0.89 and 0.91%, respectively. The overall accuracy for Furin-activated secreted MMPs and Type II trans-membrane was 98.18 and 99.07, respectively. Our data demonstrates an effective classification of Metalloproteinase family based on the concept of PseAAC and SVM.

Keywords

Matrix metalloproteinases A disintegrin and metalloprotease Bioinformatics Chou’s pseudo amino acid composition Support vector machine 

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Majid Mohammad Beigi
    • 1
  • Mohaddeseh Behjati
    • 2
    Email author
  • Hassan Mohabatkar
    • 3
    • 4
  1. 1.Department of Biomedical Engineering, Faculty of EngineeringUniversity of IsfahanIsfahanIran
  2. 2.Isfahan University of Medical SciencesIsfahanIran
  3. 3.Department of Biotechnology, Faculty of Advanced Sciences and TechnologiesUniversity of IsfahanIsfahanIran
  4. 4.Department of BiologyCollege of Sciences, Shiraz UniversityShirazIran

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