ArticlePloS one2016
Uncovering New Pathogen-Host Protein-Protein Interactions by Pairwise Structure Similarity.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Pooled it
- Comprehensive review and assessment of machine learning approaches for host-pathogen protein-protein interaction prediction.Briefings in bioinformatics · 2026Review
- Computational Analysis of Virus-Host Interactomes.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Identification of virulence-associated factors in Vibrio parahaemolyticus with special reference to moonlighting protein: a secretomics study.International microbiology : the official journal of the Spanish Society for Microbiology · 2024Article
- Article
- Computational Biology and Machine Learning Approaches to Understand Mechanistic Microbiome-Host Interactions.Frontiers in microbiology · 2021Review
- Structural proteomics, electron cryo-microscopy and structural modeling approaches in bacteria-human protein interactions.Medical microbiology and immunology · 2020Review
- Inter-Species/Host-Parasite Protein Interaction Predictions Reviewed.Current bioinformatics · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pathogens usually evade and manipulate host-immune pathways through pathogen-host protein-protein interactions (PPIs) to avoid being killed by the host immune system. Therefore, uncovering pathogen-host PPIs is critical for determining the mechanisms underlying pathogen infection and survival. In this study, we developed a computational method, which we named pairwise structure similarity (PSS)-PPI, to predict pathogen-host PPIs. First, a high-quality and non-redundant structure-structure interaction (SSI) template library was constructed by exhaustively exploring heteromeric protein complex structures in the PDB database. New interactions were then predicted by searching for PSS with complex structures in the SSI template library. A quantitative score named the PSS score, which integrated structure similarity and residue-residue contact-coverage information, was used to describe the overall similarity of each predicted interaction with the corresponding SSI template. Notably, PSS-PPI yielded experimentally confirmed pathogen-host PPIs of human immunodeficiency virus type 1 (HIV-1) with performance close to that of in vitro high-throughput screening approaches. Finally, a pathogen-host PPI network of human pathogen Mycobacterium tuberculosis, the causative agent of tuberculosis, was constructed using PSS-PPI and refined using filtration steps based on cellular localization information. Analysis of the resulting network indicated that secreted proteins of the STPK, ESX-1, and PE/PPE family in M. tuberculosis targeted human proteins involved in immune response and phagocytosis. M. tuberculosis also targeted host factors known to regulate HIV replication. Taken together, our findings provide insights into the survival mechanisms of M. tuberculosis in human hosts, as well as co-infection of tuberculosis and HIV. With the rapid pace of three-dimensional protein structure discovery, the SSI template library we constructed and the PSS-PPI method we devised can be used to uncover new pathogen-host PPIs in the future.
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