IFrag: A Protein–Protein Interface Prediction Server Based on Sequence Fragments. Issue 3 (3rd February 2017)

• Record Type: Journal Article
• Authors: Garcia-Garcia, Javier; Valls-Comamala, Victòria; Guney, Emre; Andreu, David; Muñoz, Francisco J.; Fernandez-Fuentes, Narcis; Oliva, Baldo
• Is Part Of: Journal of molecular biology. Volume 429:Issue 3(2017)
• Page Start: 382
• Page End: 389
• Publication Date: 2017-02-03
• Subjects: PPI protein–protein interaction -- PPV positive predictive value -- MCC Matthew's correlation coefficient -- AUC-ROC area under the ROC curve -- AUC-PR area under the precision-recall curve -- ThT Thioflavin T; binding site prediction -- protein interactions -- interface prediction -- β-amyloid aggregation; Molecular biology -- Periodicals; Biology -- Periodicals; Biochemistry -- Periodicals; Bacteriology -- Periodicals; Molecular Biology -- Periodicals; Biochemistry -- Periodicals; Biologie moléculaire -- Périodiques; Biologie -- Périodiques; Biochimie -- Périodiques; Moleculaire biologie; Biochemistry; Biology; Molecular biology; Periodicals; 572.805
• DOI: 10.1016/j.jmb.2016.11.034
• Languages: English
• ISSNs: 0022-2836

Abstract

Abstract: Protein–protein interactions (PPIs) are crucial in many biological processes. The first step towards the molecular characterisation of PPIs implies the charting of their interfaces, that is, the surfaces mediating the interaction. To this end, we present here iFrag, a sequence-based computational method that infers possible interacting regions between two proteins by searching minimal common sequence fragments of the interacting protein pairs. By utilising the sequences of two interacting proteins (queries), iFrag derives a two-dimensional matrix computing a score for each pair of residues that relates to the presence of similar regions in interolog protein pairs. The scoring matrix is represented as a heat map reflecting the potential interface regions in both query proteins. Unlike existing approaches, iFrag does not require three-dimensional structural information or multiple sequence alignments and can even predict small interaction sites consisting only of few residues. Thus, predicted interfaces range from short fragments composed of few residues to domains of proteins, depending on available information on PPIs, as we demonstrate in several examples. Moreover, as a proof of concept, we include the experimental validation on the successful prediction of a peptide competing with the aggregation of β-amyloid in Alzheimer's disease. iFrag is freely accessible athttp://sbi.imim.es/iFrag . Graphical Abstract: Highlights: iFrag is a new computational approach to infer the interface region of the interaction between two proteins, based only in sequence information and with a competitive performance compared to the state-of-the-art methodologies. Despite the low general accuracy of state-of-the-art approaches on the prediction of protein–protein interactions purely based on sequence information, iFraG predictions are 1.5-fold better than random predictions (when comparing to domain-binding predictions) and can reach 155-fold improvement over random predictions when comparing to homolog searches. Thus, iFraG predictions are useful complements to experimental efforts aiming at, for example, defining interface regions in proteins, selection of residues for site-directed mutagenesis, etc. The length of the sequence fragment involved in the interface varies between the size of a domain and the length of a peptide. Graphically, the predictions are presented in a bidimensional heat map, thus providing a convenient representation to help define and select protein interfaces for subsequent analyses. A proof of concept included the experimental validation of a predicted peptide that modulates the aggregation of β-amyloids, which is responsible for Alzheimer's disease, hence proving the potential and value of iFraG predictions in a real case situation.