Open AccessPrediction and analysis of human‐herpes simplex virus type 1 protein‐protein interactions by integrating multiple methods
Author(s) -
Lian Xianyi,
Yang Xiaodi,
Shao Jiqi,
Hou Fujun,
Yang Shiping,
Pan Dongli,
Zhang Ziding
Publication year - 2020
Publication title -
quantitative biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.707
H-Index - 15
eISSN - 2095-4697
pISSN - 2095-4689
DOI - 10.1007/s40484-020-0222-5
Subject(s) - herpes simplex virus , computational biology , human proteome project , hsl and hsv , protein–protein interaction , context (archaeology) , interactome , decipher , biology , inference , computer science , bioinformatics , proteomics , virology , artificial intelligence , virus , genetics , gene , paleontology
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 .