IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0022930.html
   My bibliography  Save this article

Prediction of Ubiquitination Sites by Using the Composition of k-Spaced Amino Acid Pairs

Author

Listed:
  • Zhen Chen
  • Yong-Zi Chen
  • Xiao-Feng Wang
  • Chuan Wang
  • Ren-Xiang Yan
  • Ziding Zhang

Abstract

As one of the most important reversible protein post-translation modifications, ubiquitination has been reported to be involved in lots of biological processes and closely implicated with various diseases. To fully decipher the molecular mechanisms of ubiquitination-related biological processes, an initial but crucial step is the recognition of ubiquitylated substrates and the corresponding ubiquitination sites. Here, a new bioinformatics tool named CKSAAP_UbSite was developed to predict ubiquitination sites from protein sequences. With the assistance of Support Vector Machine (SVM), the highlight of CKSAAP_UbSite is to employ the composition of k-spaced amino acid pairs surrounding a query site (i.e. any lysine in a query sequence) as input. When trained and tested in the dataset of yeast ubiquitination sites (Radivojac et al, Proteins, 2010, 78: 365–380), a 100-fold cross-validation on a 1∶1 ratio of positive and negative samples revealed that the accuracy and MCC of CKSAAP_UbSite reached 73.40% and 0.4694, respectively. The proposed CKSAAP_UbSite has also been intensively benchmarked to exhibit better performance than some existing predictors, suggesting that it can be served as a useful tool to the community. Currently, CKSAAP_UbSite is freely accessible at http://protein.cau.edu.cn/cksaap_ubsite/. Moreover, we also found that the sequence patterns around ubiquitination sites are not conserved across different species. To ensure a reasonable prediction performance, the application of the current CKSAAP_UbSite should be limited to the proteome of yeast.

Suggested Citation

  • Zhen Chen & Yong-Zi Chen & Xiao-Feng Wang & Chuan Wang & Ren-Xiang Yan & Ziding Zhang, 2011. "Prediction of Ubiquitination Sites by Using the Composition of k-Spaced Amino Acid Pairs," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-8, July.
  • Handle: RePEc:plo:pone00:0022930
    DOI: 10.1371/journal.pone.0022930
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0022930
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0022930&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0022930?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Md Mehedi Hasan & Yuan Zhou & Xiaotian Lu & Jinyan Li & Jiangning Song & Ziding Zhang, 2015. "Computational Identification of Protein Pupylation Sites by Using Profile-Based Composition of k-Spaced Amino Acid Pairs," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-20, June.
    2. Qiqige Wuyun & Wei Zheng & Yanping Zhang & Jishou Ruan & Gang Hu, 2016. "Improved Species-Specific Lysine Acetylation Site Prediction Based on a Large Variety of Features Set," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-21, May.
    3. Ting Hou & Guangyong Zheng & Pingyu Zhang & Jia Jia & Jing Li & Lu Xie & Chaochun Wei & Yixue Li, 2014. "LAceP: Lysine Acetylation Site Prediction Using Logistic Regression Classifiers," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-7, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0022930. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.