|
| Titre : |
In silico prediction of protein flexibility with local structure approach |
| Type de document : |
document électronique |
| Auteurs : |
Tarun Narwani, Auteur ; Catherine Etchebest, Auteur ; Pierrick Craveur, Auteur |
| Editeur : |
Elsevier |
| Autre Editeur : |
arXiv |
| Importance : |
Volume 165, Pages 150-155 |
| Format : |
PDF |
| Langues : |
Anglais (eng) |
| Catégories : |
572 Biochimie
|
| Tags : |
'Amino acid Structural alphabet Long structural prototypes Protein folds Disorder Bioinformatics Structural bioinformatics Software Support vector machines Evolutionary information Protein data bank Quantitative Methods (q-bio.QM) Biomolecules (q-bio.BM)' |
| Index. décimale : |
572 |
| Résumé : |
Flexibility is an intrinsic essential feature of protein structures, directly linked to their functions. To this day, most of the prediction methods use the crystallographic data (namely B-factors) as the only indicator of protein's inner flexibility and predicts them as rigid or flexible.PredyFlexy stands differently from other approaches as it relies on the definition of protein flexibility (i) not only taken from crystallographic data, but also (ii) from Root Mean Square Fluctuation (RMSFs) observed in Molecular Dynamics simulations. It also uses a specific representation of protein structures, named Long Structural Prototypes (LSPs). From Position-Specific Scoring Matrix, the 120 LSPs are predicted with a good accuracy and directly used to predict (i) the protein flexibility in three categories (flexible, intermediate and rigid), (ii) the normalized B-factors, (iii) the normalized RMSFs, and (iv) a confidence index. Prediction accuracy among these three classes is equivalent to the best two class prediction methods, while the normalized B-factors and normalized RMSFs have a good correlation with experimental and in silico values. Thus, PredyFlexy is a unique approach, which is of major utility for the scientific community. It support parallelization features and can be run on a local cluster using multiple cores.The entire project is available under an open-source license at this http URL. |
| En ligne : |
https://arxiv.org/abs/1908.05120 |
| Format de la ressource électronique : |
PDF |
In silico prediction of protein flexibility with local structure approach [document électronique] / Tarun Narwani, Auteur ; Catherine Etchebest, Auteur ; Pierrick Craveur, Auteur . - Elsevier : arXiv, [s.d.] . - Volume 165, Pages 150-155 ; PDF. Langues : Anglais ( eng)
| Catégories : |
572 Biochimie
|
| Tags : |
'Amino acid Structural alphabet Long structural prototypes Protein folds Disorder Bioinformatics Structural bioinformatics Software Support vector machines Evolutionary information Protein data bank Quantitative Methods (q-bio.QM) Biomolecules (q-bio.BM)' |
| Index. décimale : |
572 |
| Résumé : |
Flexibility is an intrinsic essential feature of protein structures, directly linked to their functions. To this day, most of the prediction methods use the crystallographic data (namely B-factors) as the only indicator of protein's inner flexibility and predicts them as rigid or flexible.PredyFlexy stands differently from other approaches as it relies on the definition of protein flexibility (i) not only taken from crystallographic data, but also (ii) from Root Mean Square Fluctuation (RMSFs) observed in Molecular Dynamics simulations. It also uses a specific representation of protein structures, named Long Structural Prototypes (LSPs). From Position-Specific Scoring Matrix, the 120 LSPs are predicted with a good accuracy and directly used to predict (i) the protein flexibility in three categories (flexible, intermediate and rigid), (ii) the normalized B-factors, (iii) the normalized RMSFs, and (iv) a confidence index. Prediction accuracy among these three classes is equivalent to the best two class prediction methods, while the normalized B-factors and normalized RMSFs have a good correlation with experimental and in silico values. Thus, PredyFlexy is a unique approach, which is of major utility for the scientific community. It support parallelization features and can be run on a local cluster using multiple cores.The entire project is available under an open-source license at this http URL. |
| En ligne : |
https://arxiv.org/abs/1908.05120 |
| Format de la ressource électronique : |
PDF |
|
Faire une suggestion Affiner la recherche Interroger des sources externes
