CAS OpenIR  > 中科院上海应用物理研究所2011-2019年
Building a Better Fragment Library for De Novo Protein Structure Prediction
de Oliveira, SHP; Shi, JY; Deane, CM
2015
Source PublicationPLOS ONE
Volume10Issue:4Pages:
Subtype期刊文献
AbstractFragment-based approaches are the current standard for de novo protein structure prediction. These approaches rely on accurate and reliable fragment libraries to generate good structural models. In this work, we describe a novel method for structure fragment library generation and its application in fragment-based de novo protein structure prediction. The importance of correct testing procedures in assessing the quality of fragment libraries is demonstrated. In particular, the exclusion of homologs to the target from the libraries to correctly simulate a de novo protein structure prediction scenario, something which surprisingly is not always done. We demonstrate that fragments presenting different predominant predicted secondary structures should be treated differently during the fragment library generation step and that exhaustive and random search strategies should both be used. This information was used to develop a novel method, Flib. On a validation set of 41 structurally diverse proteins, Flib libraries presents both a higher precision and coverage than two of the state-of-the-art methods, NNMake and HHFrag. Flib also achieves better precision and coverage on the set of 275 protein domains used in the two previous experiments of the the Critical Assessment of Structure Prediction (CASP9 and CASP10). We compared Flib libraries against NNMake libraries in a structure prediction context. Of the 13 cases in which a correct answer was generated, Flib models were more accurate than NNMake models for 10. "Flib is available for download at: http://www.stats.ox.ac.uk/research/proteins/resources".
KeywordSecondary Structure Prediction Families Database
Indexed BySCI
Language英语
Document Type期刊论文
Identifierhttp://ir.sinap.ac.cn/handle/331007/24406
Collection中科院上海应用物理研究所2011-2019年
Recommended Citation
GB/T 7714
de Oliveira, SHP,Shi, JY,Deane, CM. Building a Better Fragment Library for De Novo Protein Structure Prediction[J]. PLOS ONE,2015,10(4):—.
APA de Oliveira, SHP,Shi, JY,&Deane, CM.(2015).Building a Better Fragment Library for De Novo Protein Structure Prediction.PLOS ONE,10(4),—.
MLA de Oliveira, SHP,et al."Building a Better Fragment Library for De Novo Protein Structure Prediction".PLOS ONE 10.4(2015):—.
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