Protein-protein interaction affinity prediction based on interface descriptors and machine learning

Xue Ling Li, Min Zhu, Xiao Lai Li, Hong Qiang Wang, Shulin Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Knowing the protein-protein interaction affinity is important for accurately inferring the time dimensionality of the dynamic protein-protein interaction networks from a viewpoint of systems biology. The accumulation of the determined protein complex structures with high resolution facilitates to realize this ambitious goal. Previous methods on protein-protein interaction affinity (PPIA) prediction have achieved great success. However, there is still a great space to improve prediction accuracy. Here, we develop a support vector regression method to infer highly heterogeneous protein-protein interaction affinities based on interface properties. This method takes full advantage of the labels of the interaction pairs and greatly reduces the dimensionality of the input features. Results show that the supervised machine leaning methods are effective with R=0.80 and SD=1.41 and perform well when applied to the prediction of highly heterogeneous or generic PPIA. Comparison of different types of interface properties shows that the global interface properties have a more stable performance while the smoothed PMF obtains the best prediction accuracy.

Original languageEnglish (US)
Title of host publicationIntelligent Computing Theories and Applications - 8th International Conference, ICIC 2012, Proceedings
Pages205-212
Number of pages8
DOIs
StatePublished - Aug 20 2012
Event8th International Conference on Intelligent Computing Theories and Applications, ICIC 2012 - Huangshan, China
Duration: Jul 25 2012Jul 29 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7390 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Conference on Intelligent Computing Theories and Applications, ICIC 2012
CountryChina
CityHuangshan
Period7/25/127/29/12

Keywords

  • Machine Learning
  • Potential of Mean Force
  • Protein-protein interaction affinity
  • protein complex interface descriptors
  • two-layer Support Vectors

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Li, X. L., Zhu, M., Li, X. L., Wang, H. Q., & Wang, S. (2012). Protein-protein interaction affinity prediction based on interface descriptors and machine learning. In Intelligent Computing Theories and Applications - 8th International Conference, ICIC 2012, Proceedings (pp. 205-212). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7390 LNAI). https://doi.org/10.1007/978-3-642-31576-3_27