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CCBuilder: an interactive web-based tool for building, designing and assessing coiled-coil protein assemblies.


ABSTRACT: The ability to accurately model protein structures at the atomistic level underpins efforts to understand protein folding, to engineer natural proteins predictably and to design proteins de novo. Homology-based methods are well established and produce impressive results. However, these are limited to structures presented by and resolved for natural proteins. Addressing this problem more widely and deriving truly ab initio models requires mathematical descriptions for protein folds; the means to decorate these with natural, engineered or de novo sequences; and methods to score the resulting models.We present CCBuilder, a web-based application that tackles the problem for a defined but large class of protein structure, the ?-helical coiled coils. CCBuilder generates coiled-coil backbones, builds side chains onto these frameworks and provides a range of metrics to measure the quality of the models. Its straightforward graphical user interface provides broad functionality that allows users to build and assess models, in which helix geometry, coiled-coil architecture and topology and protein sequence can be varied rapidly. We demonstrate the utility of CCBuilder by assembling models for 653 coiled-coil structures from the PDB, which cover >96% of the known coiled-coil types, and by generating models for rarer and de novo coiled-coil structures.CCBuilder is freely available, without registration, at http://coiledcoils.chm.bris.ac.uk/app/cc_builder/.

SUBMITTER: Wood CW 

PROVIDER: S-EPMC4201159 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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CCBuilder: an interactive web-based tool for building, designing and assessing coiled-coil protein assemblies.

Wood Christopher W CW   Bruning Marc M   Ibarra Amaurys Á AÁ   Bartlett Gail J GJ   Thomson Andrew R AR   Sessions Richard B RB   Brady R Leo RL   Woolfson Derek N DN  

Bioinformatics (Oxford, England) 20140726 21


<h4>Motivation</h4>The ability to accurately model protein structures at the atomistic level underpins efforts to understand protein folding, to engineer natural proteins predictably and to design proteins de novo. Homology-based methods are well established and produce impressive results. However, these are limited to structures presented by and resolved for natural proteins. Addressing this problem more widely and deriving truly ab initio models requires mathematical descriptions for protein f  ...[more]

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