Analyzing Cysteine Site Neighbors in Proteins to Reveal Dimethyl Fumarate Targets.
Proteomics
; 19(4): e1800301, 2019 02.
Article
em En
| MEDLINE
| ID: mdl-30633445
ABSTRACT
This work proposes a novel approach by which to consistently classify cysteine sites in proteins in terms of their reactivity toward dimethyl fumarate (DMF) and fumarate. Dimethyl fumarate-based drug products have been approved for use as oral treatments for psoriasis and relapsing-remitting multiple sclerosis. The adduction of DMF and its (re)active metabolites to certain cysteine residues in proteins is thought to underlie their effects. However, only a few receptors for these compounds have been discovered to date. Our approach takes advantage of the growing number of known DMF- and fumarate-sensitive proteins and sites to perform analyses by combining the concepts of network theory, for protein structure analyses, and machine-learning procedures. Wide-ranging and previously unforeseen variety is found in the analysis of the neighborhood composition (the first neighbors) of cysteine sites found in DMF- and fumarate-sensitive proteins. Furthermore, neighborhood composition has shown itself to be a network-type attribute that is endowed with remarkable predictive power when distinct classification algorithms are employed. In conclusion, when adopted in combination with other target identification/validation approaches, methods that are based on the analysis of cysteine site neighbors in proteins should provide useful information by which to decipher the mode of action of DMF-based drugs.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Proteínas
/
Cisteína
/
Fumarato de Dimetilo
Limite:
Humans
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article