I want to find interactions between a pathogenic effector protein and the entire proteome of the host, to build a PPI (protein-protein interaction) network. What strategy/tool/software will be apt for this activity.
Many approaches, each will highlight only aspects: Sequence the whole transcriptome, do differential proteomics and analyze changes in signalling, e.g., phosphorylation, histone acetylation, etc.
One commonly used strategy for predicting protein-protein interactions (PPIs) is through computational methods that use protein sequence, structure, and other features to identify potential interacting partners. Here are a few tools and databases that may be useful for your project:
STRING: This is a database of known and predicted protein-protein interactions that covers a wide range of organisms, including many pathogenic species. You can input your effector protein sequence and retrieve a list of predicted interacting partners, along with confidence scores and information about the experimental evidence supporting each interaction.
HINT: This is a computational method for predicting PPIs based on features of the interacting proteins, including sequence, structure, and functional annotations. HINT has been shown to be effective at predicting PPIs for pathogenic proteins and can be run as a web server or downloaded as standalone software.
PrePPI: This is a database of predicted PPIs for human proteins based on a variety of features, including protein sequence, structure, and gene expression data. Although this database is specific to human proteins, it may be useful for identifying potential interacting partners that are relevant to your research.
NetworkX: This is a Python library for building and analyzing complex networks, including protein-protein interaction networks. You can use this library to build a PPI network based on the interactions predicted by the tools and databases mentioned above, and then analyze the network to identify key hub proteins or functional modules that may be relevant to your research.
It's worth noting that computational methods for predicting PPIs are not always accurate, and experimental validation is typically required to confirm the interactions identified by these methods. However, these tools and databases can be a useful starting point for identifying potential interacting partners and building a hypothesis about the interaction network between your pathogenic effector protein and the host proteome.