PERCEPTRON-PTMKB: A Web Server for Residue-Based Post-Translational Modification Analysis and Propensity Scoring.

Area of Science:

• Biochemistry
• Bioinformatics
• Computational Biology

Background:

• Post-translational modifications (PTMs) are crucial for protein function and cellular processes.
• Existing PTM databases lack integration with protein search tools, hindering analysis.
• There's a need for tools evaluating protein residues within their local context for PTMs.

Purpose of the Study:

• To introduce PERCEPTRON-PTMKB, a web server for analyzing and evaluating PTM sites.
• To provide a quantitative, residue-specific PTM evaluation using empirical data.
• To enable seamless integration of PTM analysis into existing bioinformatics workflows via a RESTful API.

Main Methods:

• Development of the PERCEPTRON-PTMKB web server.
• Implementation of a propensity scoring algorithm for quantitative PTM site evaluation.
• Creation of a secure RESTful API for search and propensity calculation pipelines.

Main Results:

• PERCEPTRON-PTMKB offers a novel approach to PTM site analysis.
• The server provides quantitative, per-residue propensity scores for PTMs.
• The RESTful API facilitates integration with protein sequence search engines.

Conclusions:

• PERCEPTRON-PTMKB enhances the study of protein post-translational modifications.
• The tool addresses the gap in integrated PTM analysis and evaluation.
• It empowers researchers to decipher PTMs more effectively in biological samples.