Protein Sequencing with an Adaptive Genetic Algorithm from Tandem Mass Spectrometry

TL;DR

This paper introduces an adaptive genetic algorithm that directly analyzes MS spectra to discover complete protein sequences, eliminating manual peak extraction and aiming to improve understanding of unknown proteins.

Contribution

It presents a novel genetic algorithm with a new evaluation function that works directly on MS spectra for de novo protein sequencing, bypassing traditional manual steps.

Findings

The approach successfully works with complete MS spectra.

It automates the peptide sequencing process.

It enhances the discovery of unknown protein sequences.

Abstract

In Proteomics, only the de novo peptide sequencing approach allows a partial amino acid sequence of a peptide to be found from a MS/MS spectrum. In this article a preliminary work is presented to discover a complete protein sequence from spectral data (MS and MS/MS spectra). For the moment, our approach only uses MS spectra. A Genetic Algorithm (GA) has been designed with a new evaluation function which works directly with a complete MS spectrum as input and not with a mass list like the other methods using this kind of data. Thus the mono isotopic peak extraction step which needs a human intervention is deleted. The goal of this approach is to discover the sequence of unknown proteins and to allow a better understanding of the differences between experimental proteins and proteins from databases.