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Protein-Protein Interactions (PPIs) play a critical role in various biological processes, including cell signaling, enzyme regulation, and protein complex formation. Studying PPIs can provide valuable insights into the mechanisms of cellular functions and help in the discovery of new therapeutic targets. In recent years, computer-aided drug design (CADD) has emerged as a powerful tool to accelerate the drug discovery process and enhance our understanding of PPI networks. One of the essential components in CADD is the utilization of various databases, such as the UniProt, PDB, STRING, BioGRID, and GeneMANIA databases. This resource page aims to provide an overview of these databases and their applications in the context of PPI research.
| PPI Database | URL | Descriptions |
| UniProt Database | https://www.uniprot.org/ | The UniProt database is a comprehensive protein sequence and functional annotation database. It provides extensive information on protein sequences, structures, functions, and interactions, and serves as a valuable resource for PPI analysis. UniProt contains curated information from several sources, including Swiss-Prot, TrEMBL, and other external protein databases. Researchers can access UniProt to retrieve specific proteins or protein families of interest, analyze their functional annotations, view protein structures and domains, and obtain valuable insights into PPI networks. |
| Protein Data Bank (PDB) Database | https:// www.rcsb.org | The Protein Data Bank (PDB) is a worldwide repository that houses three-dimensional structures of proteins and nucleic acids. It provides a wealth of information on protein structures and their interactions with other molecules. The PDB contains experimentally determined structures of protein complexes, making it an indispensable resource for studying PPIs. Researchers can search the PDB database to retrieve protein structures involved in specific interactions, visualize the binding interfaces and residues, and gain insights into the structural basis of PPIs. Additionally, the PDB offers tools and resources for analyzing and comparing protein structures, aiding in the rational design of novel PPI inhibitors. |
| STRING Database | https://string-db.org/ | The STRING database stands for "Search Tool for the Retrieval of Interacting Genes/Proteins," and it serves as a comprehensive resource for protein-protein interaction networks. STRING integrates experimental data, computational predictions, and public databases to provide a high-confidence network of PPIs for multiple organisms. Researchers can utilize STRING to explore PPIs associated with specific proteins, visualize the interaction networks, and assess the functional associations and pathways implicated by these interactions. |
| BioGRID Database | https://thebiogrid.org/ | The BioGRID database is a curated repository of biological interactions, including PPIs, genetic interactions, and post-translational modifications. It collects data from high-throughput experiments, literature, and other databases, ensuring the integration of diverse interaction datasets. BioGRID enables researchers to search for specific PPIs, retrieve experimental evidence supporting these interactions, and analyze the functional implications of PPI networks. |
| GeneMANIA Database | http://www.genemania.org/ | The GeneMANIA database assists researchers in the interpretation of PPI data and the discovery of potential interaction partners. It integrates diverse functional genomics data, including PPIs, co-expression profiles, genetic interactions, and pathway data, to predict and prioritize genes or proteins that may be functionally related. |
Protein-Protein Interaction (PPI) databases, such as UniProt, PDB, STRING, BioGRID, and GeneMANIA, have become indispensable resources in computer-aided drug design (CADD) and PPI research. These databases provide valuable information on protein sequences, structures, functions, and interactions, enabling researchers to explore and analyze PPI networks in a systematic and efficient manner. By leveraging the data and tools available in these databases, researchers can accelerate the identification of novel PPI targets, predict and prioritize interacting partners, and design therapeutic interventions to modulate PPI networks. The integration of these databases with CADD approaches holds immense potential to accelerate drug discovery and improve our understanding of complex biological systems.