PHEVIR

PHEVIR predicts pathogen-associated human disease comorbidities by integrating putative mode of action (MOA) proteins and pathogen–human protein interactomes using the LeMeDISCO approach.

Key Features:

• Comprehensive Pathogen Database: Contains data for 312 viruses and 57 bacteria for pathogen-centered analyses.
• Predictive Capability: Predicts human disease comorbidities linked to specific viral or bacterial infections.
• Identification of MOA Proteins: Identifies putative driver pathogens and corresponding human MOA proteins implicated in disease complications.
• Application to Major Diseases: Applied to Type 2 diabetes, atherosclerosis, Alzheimer’s disease, inflammatory bowel disease, pathogen oncogenicity/oncolyticity, and heart disease–influenza relationships.
• Drug Target Identification: Facilitates prioritization of potential drug targets by elucidating molecular bases of pathogen-induced complications.

Scientific Applications:

• Disease Comorbidity Prediction: Predicts associations between infections and human disease comorbidities to map infection-driven disease risks.
• Mechanistic Hypothesis Generation: Links pathogen–human protein interactions to MOA proteins to generate molecular hypotheses about disease mechanisms.
• Therapeutic Target Prioritization: Supports identification and prioritization of drug targets for intervention in pathogen-associated disease complications.
• Disease-Specific Analyses: Enables focused analysis of pathogen contributions to conditions such as Type 2 diabetes, atherosclerosis, Alzheimer’s disease, inflammatory bowel disease, cancer-related effects, and influenza-related cardiovascular complications.

Methodology:

Integrates pathogen–human protein interaction data and putative MOA proteins via the LeMeDISCO approach to predict disease comorbidities by mapping molecular pathways.