Protein post-translational modifications (PTMs) play a pivotal role in numerous biological processes by modulating regulation of protein function. We have developed iPTMnet for PTM knowledge discovery, employing an integrative bioinformatics approach—combining text mining, data mining, and ontological representation to capture rich PTM information, including PTM enzyme-substrate-site relationships, PTM-specific protein-protein interactions (PPIs) and PTM conservation across species.
iPTMnet encompasses data from:
- Our PTM-focused text mining tools, RLIMS-P and eFIP, which extract phosphorylation information from full-scale mining of PubMed abstracts and full-length articles including phosphorylation dependent protein-protein interactions (PPIs)
- A set of curated databases with experimentally observed PTMs
- Biomuta to include variants affecting PTM sites to help in interp
- Protein Ontology (PRO) that organizes proteins and PTM proteoforms (observed protein forms derived from a single gene, including isoforms and combinations of PTMs), enabling their representation, annotation and comparison within and across species
Presently covering eight major PTM types (phosphorylation, ubiquitination, acetylation, methylation, glycosylation, S-nitrosylation, sumoylation and myristoylation).
iPTMnet has several unique features:
- PTM information integrated from the scientific literature and knowledge bases
- Representation of PTM proteins, PTM enzymes and their relations at the proteoform level
- Network visualization of PTM enzyme-substrate-site and PPI relations
- Sequence alignment visualization of singly-modified, multiply-modified and/or overlapping PTM forms/sites within and across species
- Variants affecting PTMs
iPTMnet connects PTM proteoforms with their modifying enzymes and multiple coordinated PTMs across taxa, thereby unifying fragmented PTM information into a biologically meaningful context for visual and systematic PTM knowledge discovery.
To see some examples, click on the poster icon below
