An information-theoretic classification of amino acids for the assessment of interfaces in protein-protein docking

Beitrag in einer Fachzeitschrift


Details zur Publikation

Autorinnen und Autoren: Jardin C, Stefani A, Eberhardt M, Huber J, Sticht H
Zeitschrift: Journal of Molecular Modeling
Verlag: Springer Verlag (Germany)
Jahr der Veröffentlichung: 2013
Band: 19
Heftnummer: 9
Seitenbereich: 3901-10
ISSN: 1610-2940


Abstract

Docking represents a versatile and powerful method to predict the geometry of protein-protein complexes. However, despite significant methodical advances, the identification of good docking solutions among a large number of false solutions still remains a difficult task. We have previously demonstrated that the formalism of mutual information (MI) from information theory can be adapted to protein docking, and we have now extended this approach to enhance its robustness and applicability. A large dataset consisting of 22,934 docking decoys derived from 203 different protein-protein complexes was used for an MI-based optimization of reduced amino acid alphabets representing the protein-protein interfaces. This optimization relied on a clustering analysis that allows one to estimate the mutual information of whole amino acid alphabets by considering all structural features simultaneously, rather than by treating them individually. This clustering approach is fast and can be applied in a similar fashion to the generation of reduced alphabets for other biological problems like fold recognition, sequence data mining, or secondary structure prediction. The reduced alphabets derived from the present work were converted into a scoring function for the evaluation of docking solutions, which is available for public use via the web service score-MI: http://score-MI.biochem.uni-erlangen.de.


FAU-Autorinnen und Autoren / FAU-Herausgeberinnen und Herausgeber

Eberhardt, Martin
Lehrstuhl für Biochemie und Molekulare Medizin
Huber, Johannes Prof. Dr.-Ing.
Lehrstuhl für Informationsübertragung
Jardin, Christophe PD Dr.
Professur für Bioinformatik
Stefani, Arno
Lehrstuhl für Informationsübertragung
Sticht, Heinrich Prof. Dr.
Professur für Bioinformatik


Zitierweisen

APA:
Jardin, C., Stefani, A., Eberhardt, M., Huber, J., & Sticht, H. (2013). An information-theoretic classification of amino acids for the assessment of interfaces in protein-protein docking. Journal of Molecular Modeling, 19(9), 3901-10. https://dx.doi.org/10.1007/s00894-013-1916-7

MLA:
Jardin, Christophe, et al. "An information-theoretic classification of amino acids for the assessment of interfaces in protein-protein docking." Journal of Molecular Modeling 19.9 (2013): 3901-10.

BibTeX: 

Zuletzt aktualisiert 2018-05-10 um 02:28