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Reduced Fragment Diversity for Alpha and Alpha-Beta Protein Structure Prediction using Rosetta.

Identifieur interne : 000E46 ( PubMed/Curation ); précédent : 000E45; suivant : 000E47

Reduced Fragment Diversity for Alpha and Alpha-Beta Protein Structure Prediction using Rosetta.

Auteurs : Jad Abbass [Royaume-Uni] ; Jean-Christophe Nebel

Source :

Protein and peptide letters [ 1875-5305 ] ; 2017.

RBID : pubmed:27993124

Descripteurs français

KwdFr :
- Algorithmes, Biologie informatique (), Fragments peptidiques (), Logiciel, Modèles moléculaires, Motifs et domaines d'intéraction protéique, Pliage des protéines, Protéines (), Référenciation, Simulation numérique, Structure en brin bêta, Structure en hélice alpha.
MESH :
- Algorithmes, Biologie informatique, Fragments peptidiques, Logiciel, Modèles moléculaires, Motifs et domaines d'intéraction protéique, Pliage des protéines, Protéines, Référenciation, Simulation numérique, Structure en brin bêta, Structure en hélice alpha.

English descriptors

KwdEn :
- Algorithms, Benchmarking, Computational Biology (methods), Computer Simulation, Models, Molecular, Peptide Fragments (chemistry), Protein Conformation, alpha-Helical, Protein Conformation, beta-Strand, Protein Folding, Protein Interaction Domains and Motifs, Proteins (chemistry), Software.
MESH :
- chemical , chemistry : Peptide Fragments, Proteins.
- methods : Computational Biology.
- Algorithms, Benchmarking, Computer Simulation, Models, Molecular, Protein Conformation, alpha-Helical, Protein Conformation, beta-Strand, Protein Folding, Protein Interaction Domains and Motifs, Software.

Abstract

Protein structure prediction is considered a main challenge in computational biology. The biannual international competition, Critical Assessment of protein Structure Prediction (CASP), has shown in its eleventh experiment that free modelling target predictions are still beyond reliable accuracy, therefore, much effort should be made to improve ab initio methods. Arguably, Rosetta is considered as the most competitive method when it comes to targets with no homologues. Relying on fragments of length 9 and 3 from known structures, Rosetta creates putative structures by assembling candidate fragments. Generally, the structure with the lowest energy score, also known as first model, is chosen to be the "predicted one". A thorough study has been conducted on the role and diversity of 3-mers involved in Rosetta's model "refinement" phase. Usage of the standard number of 3-mers - i.e. 200 - has been shown to degrade alpha and alpha-beta protein conformations initially achieved by assembling 9-mers. Therefore, a new prediction pipeline is proposed for Rosetta where the "refinement" phase is customised according to a target's structural class prediction. Over 8% improvement in terms of first model structure accuracy is reported for alpha and alpha-beta classes when decreasing the number of 3- mers.

DOI: 10.2174/0929866523666161216124019
PubMed: 27993124

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Le document en format XML

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<front><div type="abstract" xml:lang="en">Protein structure prediction is considered a main challenge in computational biology. The biannual international competition, Critical Assessment of protein Structure Prediction (CASP), has shown in its eleventh experiment that free modelling target predictions are still beyond reliable accuracy, therefore, much effort should be made to improve ab initio methods. Arguably, Rosetta is considered as the most competitive method when it comes to targets with no homologues. Relying on fragments of length 9 and 3 from known structures, Rosetta creates putative structures by assembling candidate fragments. Generally, the structure with the lowest energy score, also known as first model, is chosen to be the "predicted one". A thorough study has been conducted on the role and diversity of 3-mers involved in Rosetta's model "refinement" phase. Usage of the standard number of 3-mers - i.e. 200 - has been shown to degrade alpha and alpha-beta protein conformations initially achieved by assembling 9-mers. Therefore, a new prediction pipeline is proposed for Rosetta where the "refinement" phase is customised according to a target's structural class prediction. Over 8% improvement in terms of first model structure accuracy is reported for alpha and alpha-beta classes when decreasing the number of 3- mers.</div>
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Reduced Fragment Diversity for Alpha and Alpha-Beta Protein Structure Prediction using Rosetta.

Reduced Fragment Diversity for Alpha and Alpha-Beta Protein Structure Prediction using Rosetta.

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

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Pour générer des pages wiki