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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
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]