title: Amino-acid residue association models for large scale protein-protein interaction prediction.
abstract: The computational prediction of protein-protein interactions (PPI) is an essential complement to direct experimental evidence. Traditional approaches rely on less available or computationally predicted surface properties, show database-specific performances and are computationally expensive for large-scale datasets. Several sensitivity and specificity issues remain. Here, we report a novel method based on 'Amino-acid Residue Associations' (ARA) among interacting proteins which utilizes the accurate and easily available primary sequence. Large scale PPI datasets for six model species (from E. coli to human) were studied. The ARA method shows up to 73%sensitivity and 78% specificity. Furthermore, the method performs remarkably well in terms of stability and generalizability. The performance of ARA method benchmarked against existing prediction techniques shows performance improvement upto 25%. Ability of ARA method to predict PPI across species and across databases is also demonstrated. Overall, the ARA method provides a significant improvement over existing ones in correctly identifying large scale protein-protein interactions,irrespective of the data resource, network size or organism.
  
  
  BACKGROUND
  The MATLAB code for ARA approach will be made available upon request.
authors.affiliation: Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore 117576, Singapore.
authors.forename: Raghuraj
authors.initials: R
authors.lastname: Rao
authors.forename: Kyaw
authors.initials: K
authors.lastname: Tun
authors.forename: Samavedham
authors.initials: S
authors.lastname: Lakshminarayanan
authors.forename: Pawan K
authors.initials: PK
authors.lastname: Dhar
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D000818:Animals; D019295:Computational Biology / Q000379:methods; D030562:Databases, Protein; D006801:Humans; D008969:Molecular Sequence Data; D025941:Protein Interaction Mapping / Q000379:methods*; D011506:Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D012372:ROC Curve; D012680:Sensitivity and Specificity
chemical_list: D000596:Amino Acids; D011506:Proteins