Structure prediction algorithm for protein complexes based on gene ontology
https://doi.org/10.29235/1561-8323-2020-64-2-150-158
Abstract
We propose an algorithm for comparing protein-protein complexes based on their functional properties in terms of Gene Ontology. The proposed measure of a functional similarity between complexes is combined with a structural measure to find templates for the template-based docking of protein complexes. We present the results on the modeling of protein complexes based on this algorithm.
About the Authors
A. Yu. HadarovichBelarus
Hadarovich Anna Yu. – Researcher.
6, Surganov Str., 220012, Minsk
I. V. Anishchenko
United States
Anishchanka Ivan V. – Ph. D. (Engineering), Researcher.
Seattle
P. Kundrotas
United States
Kundrotas Petras – Assistant research professor.
66045, 2030 Becker Drive, Lawrence, Kansas
I. Vakser
United States
Vakser Ilya – Professor, Director. Center for Computational Biology.
66045, 2030 Becker Drive, Lawrence, Kansas
A. V. Tuzikov
Belarus
Tuzikov Alexander V. – Corresponding Member, D. Sc. (Physics and Mathematics), Professor, General director.
6, Surganov Str., 220012, Minsk
References
1. The Gene Ontology Consortium. Gene Ontology Consortium: going forward. Nucleic Acids Research, 2015, vol. 43, pp. D1049–D1056. https://doi.org/10.1093/nar/gku1179
2. Pesquita C., Faria D., Bastos H., Ferreira A. E. N., Falcão A. O., Couto F. M. Metrics for GO based protein semantic similarity: a systematic evaluation. BMC Bioinformatics, 2008, vol. 9, pp. S4. https://doi.org/10.1186/1471-2105-9-s5-s4
3. Resnik P. Using Information Content to Evaluate Semantic Similarity in a Taxonomy. Proceedings of the 14th International Joint Conference on Artificial Intelligence, 1995, vol. 1, pp. 448–453.
4. Schlicker A., Domingues F. S., Rahnenführer J., Lengauer T. A new measure for functional similarity of gene products based on Gene Ontology. BMC Bioinformatics, 2006, vol. 7, no. 1, art. 302. https://doi.org/10.1186/1471-2105-7-302
5. Couto F. M., Silva M. J., Coutinho P. M. Measuring semantic similarity between Gene Ontology terms. Data & Knowledge Engineering, 2007, vol. 61, no. 1, pp. 137–152. https://doi.org/10.1016/j.datak.2006.05.003
6. Zhang Y., Skolnick J. Scoring Function for Automated Assessment of Protein Structure Template Quality. Proteins: Structure, Function, and Bioinformatics, 2004, vol. 57, no. 4, pp. 702–710. https://doi.org/10.1002/prot.20264
7. Zhang Y., Skolnick J. TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Research, 2005, vol. 33, no. 7, pp. 2302–2309. https://doi.org/10.1093/nar/gki524
8. Negroni J., Mosca R., Aloy P. Assessing the Applicability of Template-Based Protein Docking in the Twilight Zone. Structure, 2014, vol. 22, no. 9, pp. 1356–1362. https://doi.org/10.1016/j.str.2014.07.009
9. Douguet D., Chen H. C., Tovchigrechko A., Vakser I. A. DOCKGROUND resource for studying protein-protein interfaces. Bioinformatics, 2006, vol. 22, no. 21, pp. 2612–2618. https://doi.org/10.1093/bioinformatics/btl447
10. Kundrotas P. J., Anishchenko I., Dauzhenka T., Kotthoff I., Mnevets D., Copeland M. M., Vakser I. A. DOCKGROUND: A comprehensive data resource for modeling of protein complexes. Protein Science, 2018, vol. 27, no. 1, pp. 172–181. https://doi.org/10.1002/pro.3295
11. Berman H. M., Westbrook J., Feng Z., Gilliland G., Bhat T. N., Weissig H., Shindyalov I. N., Bourne P. E. The Protein Data Bank. Nucleic Acids Research, 2000, vol. 28, no. 1, pp. 235–242. https://doi.org/10.1093/nar/28.1.235
12. Anishchenko I., Kundrotas P. J., Tuzikov A. V., Vakser I. A. Structural templates for comparative protein docking. Proteins: Structure, Function, and Bioinformatics, 2014, vol. 83, no. 9, pp. 1563–1570. https://doi.org/10.1002/prot.24736
13. Das S., Abraham A., Konar A. Particle Swarm Optimization and Differential Evolution Algorithms: Technical Analysis, Applications and Hybridization Perspectives. Advances of Computational Intelligence in Industrial Systems, 2008, vol. 116, pp. 1–38. https://doi.org/10.1007/978-3-540-78297-1_1
14. Sinha R., Kundrotas P. J., Vakser I. A. Docking by structural similarity at protein-protein interfaces. Proteins: Structure, Function, and Bioinformatics, 2010, vol. 78, no. 15, pp. 3235–3241. https://doi.org/10.1002/prot.22812
15. Hadarovich A., Anishchenko I., Kundrotas P. J., Tuzikov A. V., Vakser I. A. Gene ontology improves template selection in comparative protein docking. Proteins: Structure, Function, Bioinformatics, 2019, vol. 87, no. 3, pp. 245–253. https://doi.org/10.1002/prot.25645