ArticleScientific reports2018
SUMOgo: Prediction of sumoylation sites on lysines by motif screening models and the effects of various post-translational modifications.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Artificial intelligence in plant salt stress research: from predictive models to multi-omics integration.Journal of experimental botany · 2026Review
- Recent advances in proteomic workflows to interrogate the SUMOylome in plants.The New phytologist · 2025Review
- A GATA factor radiation inbioRxiv : the preprint server for biology · 2025Article
- Insight into Protein Engineering: FromCurrent pharmaceutical design · 2025Review
- Sitetack: a deep learning model that improves PTM prediction by using known PTMs.Bioinformatics (Oxford, England) · 2024Article
- Topotecan and Ginkgolic Acid Inhibit the Expression and Transport Activity of Human Organic Anion Transporter 3 by Suppressing SUMOylation of the Transporter.Pharmaceutics · 2024Article
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- Exploring the Role of Unconventional Post-Translational Modifications in Cancer Diagnostics and Therapy.Current protein & peptide science · 2024Review
- Humanization reveals pervasive incompatibility of yeast and human kinetochore components.G3 (Bethesda, Md.) · 2023Article
- Identification genetic variations in some heat shock protein genes of Tali goat breed and study their structural and functional effects on relevant proteins.Veterinary medicine and science · 2023Article
- Pancreatic Hormone Insulin Modulates Organic Anion Transporter 1 in the Kidney: Regulation via Remote Sensing and Signaling Network.The AAPS journal · 2023Article
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- Thirty years of molecular dynamics simulations on posttranslational modifications of proteins.Physical chemistry chemical physics : PCCP · 2022Review
- Review
- Article
- First report of computational protein-ligand docking to evaluate susceptibility to HIV integrase inhibitors in HIV-infected Iranian patients.Biochemistry and biophysics reports · 2022Article
- Article
- Understanding and Exploiting Post-Translational Modifications for Plant Disease Resistance.Biomolecules · 2021Review
- SUMOylation of α-tubulin is a novel modification regulating microtubule dynamics.Journal of molecular cell biology · 2021Article
- Peptide Hormone Insulin Regulates Function, Expression, and SUMOylation of Organic Anion Transporter 3.The AAPS journal · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Most modern tools used to predict sites of small ubiquitin-like modifier (SUMO) binding (referred to as SUMOylation) use algorithms, chemical features of the protein, and consensus motifs. However, these tools rarely consider the influence of post-translational modification (PTM) information for other sites within the same protein on the accuracy of prediction results. This study applied the Random Forest machine learning method, as well as motif screening models and a feature selection combination mechanism, to develop a SUMOylation prediction system, referred to as SUMOgo. With regard to prediction method, PTM sites were coded as new functional features in addition to structural features, such as sequence-based binary coding, encoded chemical features of proteins, and encoded secondary structure information that is important for PTM. Twenty cycles of prediction were conducted with a 1:1 combination of positive test data and random negative data. Matthew's correlation coefficient of SUMOgo reached 0.511, which is higher than that of current commonly used tools. This study further verified the important role of PTM in SUMOgo and includes a case study on CREB binding protein (CREBBP). The website for the final tool is http://predictor.nchu.edu.tw/SUMOgo .
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