SCIENCE@home

A comprehensive comparative review of protein sequence based computational prediction models of lysine succinylation sites.

Samme Amena Tasmia,M. Kibria,Md. Ariful Islam,M. S. Khatun,Md. Nurul Haque Mollah

Published 2022 in Current protein and peptide science

ABSTRACT

Lysine succinylation is a post-translational modification (PTM) of protein in which a succinyl group (-CO-CH2-CH2-CO2H) is added to a lysine residue of protein that reverses lysine's positive charge to a negative charge and leads to the significant changes in protein structure and function. It occurs on a wide range of proteins and plays an important role in various cellular and biological processes in both eukaryotes and prokaryotes. Beyond experimentally identified succinylation sites, there have been a lot of studies for developing sequence-based prediction using machine learning approaches, because it has the promise of being extremely time-saving, accurate, robust, and cost-effective. Despite of these benefits on computational prediction of lysine succinylation sites for different species, there are a number of issues that need to be addressed in the design and development of succinylation site predictors. In spite the fact that many studies used different statistical and machine learning computational tools, only a few studies have focused on these bioinformatics issues in depth. Therefore, in this comprehensive comparative review, an attempt is made to present the latest advances in the prediction models, datasets, and online resources, as well as the obstacles and limits, to provide an advantageous guideline for developing more suitable and effective succinylation site prediction tools.

PUBLICATION RECORD

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-90 of 90 references · Page 1 of 1

CITED BY

Showing 1-4 of 4 citing papers · Page 1 of 1