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HseSUMO: Sumoylation site prediction using half - sphere exposures of amino acids residues

Sharma, Alokanand and Lysenko, Artem and Lopez, Yosvany and Dehzangi, Abdollah and Sharma, Ronesh and Reddy, Hamendra M. and Sattar, Abdul and Tsunoda, Tatsuhiko (2019) HseSUMO: Sumoylation site prediction using half - sphere exposures of amino acids residues. BMC Genomics, 19 (9). pp. 1-7. ISSN 1471-2164

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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.

Item Type: Journal Article
Subjects: Q Science > Q Science (General)
T Technology > T Technology (General)
Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
Depositing User: Alokanand Sharma
Date Deposited: 02 Aug 2019 03:47
Last Modified: 01 Oct 2020 02:22

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