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


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 .

SUBMITTER: Sharma A 

PROVIDER: S-EPMC7402407 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Publications

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

Sharma Alok A   Lysenko Artem A   López Yosvany Y   Dehzangi Abdollah A   Sharma Ronesh R   Reddy Hamendra H   Sattar Abdul A   Tsunoda Tatsuhiko T  

BMC genomics 20190418 Suppl 9


<h4>Background</h4>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.<h4>Results</h4>This work explores the use of four h  ...[more]

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