Prediction and analysis of human-herpes simplex virus type 1 protein-protein interactions by integrating multiple methods

Background:Herpes simplex virus type 1(HSV-1)is a ubiquitous infectious pathogen that widely affects human health.To decipher the complicated human-HSV-1 interactions,a comprehensive protein-protein interaction(PPI)network between human and HSV-1 is highly demanded.Methods:To complement the experimental identification of human-HSV-1 PPIs,an integrative strategy to predict proteome-wide PPIs between human and HSV-1 was developed.For each human-HSV-1 protein pair,four popular PPI inference methods,including interolog mapping,the domain-domain interaction-based method,the domain-motif interaction-based method,and the machine learning-based method,were optimally implemented to generate four interaction probability scores,which were further integrated into a final probability score.Results:As a result,a comprehensive high-confidence PPI network between human and HSV-1 was established,covering 10,432 interactions between 4,546 human proteins and 72 HSV-1 proteins.Functional and network analyses of the HSV-1 targeting proteins in the context of human interactome can recapitulate the known knowledge regarding the HSV-1 replication cycle,supporting the overall reliability of the predicted PPI network.Considering that HSV-1 infections are implicated in encephalitis and neurodegenerative diseases,we focused on exploring the biological significance of the brain-specific human-HSV-1 PPIs.In particular,the predicted interactions between HSV-1 proteins and Alzheimer's-disease-related proteins were intensively investigated.Conclusion:The current work can provide testable hypotheses to assist in the mechanistic understanding of the human-HSV-1 relationship and the anti-HSV-1 pharmaceutical target discovery.To make the predicted PPI network and the datasets freely accessible to the scientific community,a user-friendly database browser was released at http://www.zzdlab.com/HintHSV/index.php.