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Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction.


ABSTRACT:

Motivation

Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of fragments are searched to find suitable conformations and ab initio, where conformations are generated computationally. Existing knowledge-based methods only use fragments that are the same length as the target, even though loops of slightly different lengths may adopt similar conformations. Here, we present a novel method, Sphinx, which combines ab initio techniques with the potential extra structural information contained within loops of a different length to improve structure prediction.

Results

We show that Sphinx is able to generate high-accuracy predictions and decoy sets enriched with near-native loop conformations, performing better than the ab initio algorithm on which it is based. In addition, it is able to provide predictions for every target, unlike some knowledge-based methods. Sphinx can be used successfully for the difficult problem of antibody H3 prediction, outperforming RosettaAntibody, one of the leading H3-specific ab initio methods, both in accuracy and speed.

Availability and implementation

Sphinx is available at http://opig.stats.ox.ac.uk/webapps/sphinx.

Contact

deane@stats.ox.ac.uk.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Marks C 

PROVIDER: S-EPMC5408792 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction.

Marks Claire C   Nowak Jaroslaw J   Klostermann Stefan S   Georges Guy G   Dunbar James J   Shi Jiye J   Kelm Sebastian S   Deane Charlotte M CM  

Bioinformatics (Oxford, England) 20170501 9


<h4>Motivation</h4>Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of fragments are searched to find suitable conformations and ab initio, where conformations are generated computationally. Existing knowledge-based methods only use fragments that are the same length as the target, even though loops of slightly diffe  ...[more]

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