HseSUMO: Sumoylation site prediction using half-sphere exposures of amino acids residues.
BMC Genomics
; 19(Suppl 9): 982, 2019 Apr 18.
Article
em En
| MEDLINE
| ID: mdl-30999862
ABSTRACT
BACKGROUND:
Post-translational modifications are viewed as an important mechanism for controlling protein function and are believed to be involved in multiple important diseases. However, their profiling using laboratory-based techniques remain challenging. Therefore, making the development of accurate computational methods to predict post-translational modifications is particularly important for making progress in this area of research.RESULTS:
This work explores the use of four half-sphere exposure-based features for computational prediction of sumoylation sites. Unlike most of the previously proposed approaches, which focused on patterns of amino acid co-occurrence, we were able to demonstrate that protein structural based features could be sufficiently informative to achieve good predictive performance. The evaluation of our method has demonstrated high sensitivity (0.9), accuracy (0.89) and Matthew's correlation coefficient (0.78-0.79). We have compared these results to the recently released pSumo-CD method and were able to demonstrate better performance of our method on the same evaluation dataset.CONCLUSIONS:
The proposed predictor HseSUMO uses half-sphere exposures of amino acids to predict sumoylation sites. It has shown promising results on a benchmark dataset when compared with the state-of-the-art method. The extracted data of this study can be accessed at https//github.com/YosvanyLopez/HseSUMO .
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Proteínas
/
Biologia Computacional
/
Sumoilação
/
Aminoácidos
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
BMC Genomics
Assunto da revista:
GENETICA
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
Austrália