A residual level potential of mean force based approach to predict protein-protein interaction affinity

Xue Ling Li, Mei Ling Hou, Shu Lin Wang

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

4 Citations (Scopus)

Abstract

We develop a knowledge-based statistical energy function on residual level for quantitatively predicting the affinity of protein-protein complexes by using 20 residue types and a distance-free reference state. The correlation coefficients between experimentally measured protein-protein binding affinities (PPIA) and the predicted affinities by our approach are 0.74 for 82 protein-protein (peptide) complexes. Compared to the published results of two other volume corrected knowledge-based scoring functions on atomic level, the proposed approach not only is the simplest but also yields the comparable correlation between theoretical and experimental binding affinities of the test sets with the reported best methods.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages680-686
Number of pages7
Volume6215 LNCS
DOIs
StatePublished - 2010
Externally publishedYes
Event6th International Conference on Intelligent Computing, ICIC 2010 - Changsha, China
Duration: Aug 18 2010Aug 21 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6215 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other6th International Conference on Intelligent Computing, ICIC 2010
CountryChina
CityChangsha
Period8/18/108/21/10

Fingerprint

Protein-protein Interaction
Affine transformation
Proteins
Protein
Predict
Knowledge-based
Peptides
Test Set
Energy Function
Scoring
Correlation coefficient

Keywords

  • affinity
  • mean force of potential
  • protein complex
  • Protein-protein interaction
  • quaternary structure
  • residue level

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Li, X. L., Hou, M. L., & Wang, S. L. (2010). A residual level potential of mean force based approach to predict protein-protein interaction affinity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6215 LNCS, pp. 680-686). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6215 LNCS). https://doi.org/10.1007/978-3-642-14922-1_85

A residual level potential of mean force based approach to predict protein-protein interaction affinity. / Li, Xue Ling; Hou, Mei Ling; Wang, Shu Lin.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6215 LNCS 2010. p. 680-686 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6215 LNCS).

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

Li, XL, Hou, ML & Wang, SL 2010, A residual level potential of mean force based approach to predict protein-protein interaction affinity. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 6215 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6215 LNCS, pp. 680-686, 6th International Conference on Intelligent Computing, ICIC 2010, Changsha, China, 8/18/10. https://doi.org/10.1007/978-3-642-14922-1_85
Li XL, Hou ML, Wang SL. A residual level potential of mean force based approach to predict protein-protein interaction affinity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6215 LNCS. 2010. p. 680-686. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-14922-1_85
Li, Xue Ling ; Hou, Mei Ling ; Wang, Shu Lin. / A residual level potential of mean force based approach to predict protein-protein interaction affinity. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6215 LNCS 2010. pp. 680-686 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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