BioJava-ModFinder
BioJava-ModFinder identifies and annotates protein modifications in three-dimensional structures from the Protein Data Bank (PDB) to support structural analysis of modified residues, attachment modifications, and cross-links.
Key Features:
- Curated modification dataset: Contains over 400 types of protein modifications compiled from PDB, RESID, and PSI-MOD.
- Categorization of modifications: Classifies modifications into modified residues, attachment modifications, and cross-links.
- PDB-wide scanning: Scans all archived 3D structures in the PDB and has identified over 30,000 structures containing protein modifications.
- Detection and annotation algorithms: Implements algorithms that detect and annotate modification instances within PDB entries.
- Integration with RCSB PDB: Programmatic integration augments sequence diagrams and structure annotations within the RCSB PDB ecosystem.
Scientific Applications:
- Explore protein functionality: Maps protein modifications onto 3D structures to support analysis of their roles in protein behavior and interactions.
- Facilitate drug discovery: Identifies modification sites on proteins that can inform target selection and structure-based drug design.
- Advance structural annotation: Produces detailed modification annotations that enhance structural databases and downstream computational analyses.
Methodology:
Collects and curates modification data from PDB, RESID, and PSI-MOD. Categorizes modifications into predefined groups (modified residues, attachment modifications, cross-links). Implements algorithms that scan PDB entries to detect and annotate these modifications.
Topics
Details
- License:
- LGPL-2.1
- Tool Type:
- desktop application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Java
- Added:
- 6/5/2018
- Last Updated:
- 12/10/2018
Operations
Publications
Gao J, Prlić A, Bi C, Bluhm WF, Dimitropoulos D, Xu D, Bourne PE, Rose PW. BioJava-ModFinder: identification of protein modifications in 3D structures from the Protein Data Bank. Bioinformatics. 2017;33(13):2047-2049. doi:10.1093/bioinformatics/btx101. PMID:28334105. PMCID:PMC5870676.