Computational methods for the prediction of the structure and interactions of coiled-coil peptides

Gandhi, Neha S. & Mancera, Ricardo L. (2008) Computational methods for the prediction of the structure and interactions of coiled-coil peptides. Current Bioinformatics, 3(3), pp. 149-161.

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Abstract

The past several years have seen significant advances in the development of computational methods for the prediction of the structure and interactions of coiled-coil peptides. These methods are generally based on pairwise correlations of amino acids, helical propensity, thermal melts and the energetics of sidechain interactions, as well as statistical patterns based on Hidden Markov Model (HMM) and Support Vector Machine (SVM) techniques. These methods are complemented by a number of public databases that contain sequences, motifs, domains and other details of coiled-coil structures identified by various algorithms. Some of these computational methods have been developed to make predictions of coiled-coil structure on the basis of sequence information; however, structural predictions of the oligomerisation state of these peptides still remains largely an open question due to the dynamic behaviour of these molecules. This review focuses on existing in silico methods for the prediction of coiled-coil peptides of functional importance using sequence and/or three-dimensional structural data.

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ID Code: 93829
Item Type: Review
Refereed: Yes
Keywords: Coiled-coil peptides, hidden Markov model, oligomerisation, heptad, Crick's model, knobs-into-holes, Velcro hypothesis, leucine zipper
DOI: 10.2174/157489308785909205
ISSN: 2212-392X
Divisions: Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Deposited On: 04 Apr 2016 23:13
Last Modified: 04 Apr 2016 23:13

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