title: Predictions of Protein-Protein Interfaces within Membrane Protein Complexes.
abstract: BACKGROUND
  Prediction of interaction sites within the membrane protein complexes using the sequence data is of a great importance, because it would find applications in modification of molecules transport through membrane, signaling pathways and drug targets of many diseases. Nevertheless, it has gained little attention from the protein structural bioinformatics community.
  
  
  METHODS
  In this study, a wide variety of prediction and classification tools were applied to distinguish the residues at the interfaces of membrane proteins from those not in the interfaces.
  
  
  RESULTS
  The tuned SVM model achieved the high accuracy of 86.95% and the AUC of 0.812 which outperforms the results of the only previous similar study. Nevertheless, prediction performances obtained using most employed models cannot be used in applied fields and needs more effort to improve.
  
  
  CONCLUSIONS
  Considering the variety of the applied tools in this study, the present investigation could be a good starting point to develop more efficient tools to predict the membrane protein interaction site residues.
authors.affiliation: Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran.
authors.forename: Ebrahim Barzegari
authors.initials: EB
authors.lastname: Asadabadi
authors.forename: Parviz
authors.initials: P
authors.lastname: Abdolmaleki
keywords: Interaction sites; Membrane proteins; Support vector machines
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