Prediction of E.coli Protein-Protein Interaction Sites Using Inter-Residue Distances and High-Quality-Index Features

  • Brijesh Kumar Sriwastava
  • Subhadip Basu
  • Ujjwal Maulik
  • Dariusz Plewczynski
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 132)


We propose computational method for identification of protein-protein interaction sites using sequence and structure information. The method is trained on database of interacting proteins (DIP) for E.coli. Proteins that are known to interact are first collected from experimental results. All interacting partners are mapped onto corresponding three-dimensional structures. The training dataset for support vector machine algorithm is trained using both sequence composition and structural conformations of selected structures, if and only if both partners are composing the same complex. Our computational method is able to predict interactions for E.coli with 0.93 AUC, 0.89 sensitivity and 0.98 specificity.


Protein Data Bank Accessible Surface Area Interface Residue Support Vector Machine Algorithm Protein Data Bank Entry 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Brijesh Kumar Sriwastava
    • 1
  • Subhadip Basu
    • 2
  • Ujjwal Maulik
    • 2
  • Dariusz Plewczynski
    • 3
  1. 1.Department of Computer Science and EngineeringGovernment College of Engineering and Leather TechnologyKolkataIndia
  2. 2.Department of Computer Science and EngineeringJadavpur UniversityKolkataIndia
  3. 3.Interdisciplinary Centre for Mathematical and Computational ModelingUniversity of WarsawWarsawPoland

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