Molecular interactions form the basis of pathogenicity. Protein-protein interactions (PPIs) play a crucial role in causing the disease infection and generating subsequent defense responses against the disease. HPIpy is a Python-based tool designed to predict protein-protein interactions across diverse pathosystems such as human-virus, plant-pathogen, and others. Our tool leverages computational algorithms to predict accurate and reliable interactions between host and pathogen proteins, and support research in the field of infectious diseases and drug discovery. With a comprehensive documentation, HPIpy empowers researchers to accelerate their discoveries and gain deeper insights into complex biological systems.
Key Features
- Comprehensive host-pathogen systems coverage
- Network analysis and visualization
- Scalability to large datasets
- High efficiency
- Easy to install and use with clear documentation
- Open source and customizable
Advantages
- Accelerate research with precise interactions prediction
- Save time with advanced end-to-end, automated pipeline
- Enhance understanding of complex biological systems
Pathosystems
HPIpy supports multiple host-pathogen systems:
- Human-Virus: Human as host and all human-related viruses as pathogen
- Human-Bacteria: Potential host is human and all human-related bacterial species as pathogen
- Animal-Pathogen: Animals (such as rat, bovine, etc.) as host and their pathogens (bacteria, viruses, etc.) as pathogen
- Plant-Pathogen: Plants (cereals, legumes, etc.) as host and their pathogens (fungi, bacteria, etc.) as pathogen
Computational models
HPIpy implements diverse interaction models for interactions prediction:
- Interolog mapping
- Domain-based
- Phylogenetic profiling
- Gene ontology (GO) semantic similarity