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Computational analysis of the stability of SCF ligases employing domain information

Published: 20 September 2014 Publication History

Abstract

Because of the unequivocally fundamental role of SCF ubiquitin ligase in many biological functions within a living cell including regulating DNA repair, cell cycle progression, and inflammation, we have analyzed the role of domain interactions in determining particular types of protein-protein interactions (PPIs) that are known or predicted to occur involving subunit components of the SCF-ligase complex. We focus on the prediction and analysis of obligate and non-obligate SCF-ligase complexes by using sequence domains from the Pfam database. After extracting different types of feature vectors, the prediction is performed via a support vector machine (SVM). The numerical results demonstrate that most of the interactions of SCF-ligase complexes are mediated by at least one domain. Moreover, domain-domain interactions dominate in obligate complexes whereas non-obligate complexes exhibit more domain-peptide chain interactions. Also, the computational results show that the best prediction accuracy of 80.46% is achieved using the combination of feature vectors of domain-domain type, domain-peptide chain type and no-domain interactions.

References

[1]
M. H. Dezfulian, D. M. Soulliere, R. K. Dhaliwal, M. Sareen, and W. L. Crosby, "The skp1--like gene family of arabidopsis exhibits a high degree of differential gene expression and gene product interaction during development," PLOS ONE, vol. 7, no. 11, 2012.
[2]
D. M. Duda, D. C. Scott, M. F. Calabrese, E. S. Zimmerman, N. Zheng, and B. A. Schulman, "Structural regulation of cullin-ring ubiquitin ligase complexes," Current Opinion in Structural Biology, vol. 21, no. 2, pp. 257--264, 2012.
[3]
L. Chen, R. Wang, and X. Zhang, Biomolecular Networks: Methods and Applications in Systems Biology. John Wiley and Sons, 2009.
[4]
M. Maleki, M. Hall, and L. Rueda, "Using desolvation energies of structural domains to predict stability of protein complexes," Journal of Network Modeling Analysis in Health Informatics and Bioinformatics (NetMahib), vol. 2, pp. 267--275, 2013.
[5]
M. Maleki, G. Vasudev, and L. Rueda, "The role of electrostatic energy in prediction of obligate protein-protein interactions," BMC Proteome Science, vol. 11, 2013.
[6]
S. A. Ozbabacan, H. Engin, A. Gursoy, and O. Keskin, "Transient protein-protein interactions," Protein EngăDes Sel., vol. 24, no. 9, pp. 635--48, 2011.

Cited By

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  • (2015)Classification via correlation-based feature grouping2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)10.1109/CIBCB.2015.7300293(1-6)Online publication date: Aug-2015
  • (2015)A Computational Domain-Based Feature Grouping Approach for Prediction of Stability of SCF LigasesBioinformatics and Biomedical Engineering10.1007/978-3-319-16483-0_61(630-640)Online publication date: 2015

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Published In

cover image ACM Conferences
BCB '14: Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics
September 2014
851 pages
ISBN:9781450328944
DOI:10.1145/2649387
  • General Chairs:
  • Pierre Baldi,
  • Wei Wang
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 September 2014

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Author Tags

  1. SCF-ligases
  2. complex type prediction
  3. pfam domains
  4. protein-protein interaction

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BCB '14
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BCB '14: ACM-BCB '14
September 20 - 23, 2014
California, Newport Beach

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Overall Acceptance Rate 254 of 885 submissions, 29%

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Cited By

View all
  • (2015)Classification via correlation-based feature grouping2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)10.1109/CIBCB.2015.7300293(1-6)Online publication date: Aug-2015
  • (2015)A Computational Domain-Based Feature Grouping Approach for Prediction of Stability of SCF LigasesBioinformatics and Biomedical Engineering10.1007/978-3-319-16483-0_61(630-640)Online publication date: 2015

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