Stringent DDI-based Prediction of H. sapiens-M. tuberculosis H37Rv Protein-Protein Interactions

摘要: Background: H. sapiens-M. tuberculosis H37Rv protein-protein interaction (PPI) data are very important information to illuminate the infection mechanism of M. H37Rv. But current PPI scarce. This seriously limits study between this pathogen and its host sapiens. Computational prediction PPIs is an strategy fill in gap. Domain-domain (DDI) based one frequently used computational approaches predicting both intra-species inter-species PPIs. However, performance DDI-based host-pathogen has been rather limited. Results: We develop a stringent approach with emphasis on (i) differences specific domain sequences annotated regions proteins under same ID (ii) calculation strength predicted interacting residues their interfaces. compare our conventional for gold standard coherent informative Gene Ontology terms assessment. The assessment results show that achieves much better than approach. Using approach, we have small set reliable which could be useful variety related studies. also analyze by using cellular compartment distribution analysis, functional category enrichment analysis pathway analysis. analyses support validity result. Also, network discovered some properties domains involved find tend more PPIs, these partners PPI. Conclusions: reported work provides It performs accurate