NDLI: A comparison of different functions for predicted protein model quality assessment

Content Provider	Springer Nature Link
Author	Li, Juan Fang, Huisheng
Copyright Year	2016
Abstract	In protein structure prediction, a considerable number of models are usually produced by either the Template-Based Method (TBM) or the ab initio prediction. The purpose of this study is to find the critical parameter in assessing the quality of the predicted models. A non-redundant template library was developed and 138 target sequences were modeled. The target sequences were all distant from the proteins in the template library and were aligned with template library proteins on the basis of the transformation matrix. The quality of each model was first assessed with QMEAN and its six parameters, which are C_β interaction energy (C_beta), all-atom pairwise energy (PE), solvation energy (SE), torsion angle energy (TAE), secondary structure agreement (SSA), and solvent accessibility agreement (SAE). Finally, the alignment score (score) was also used to assess the quality of model. Hence, a total of eight parameters (i.e., QMEAN, C_beta, PE, SE, TAE, SSA, SAE, score) were independently used to assess the quality of each model. The results indicate that SSA is the best parameter to estimate the quality of the model.
Starting Page	553
Ending Page	558
Page Count	6
File Format	PDF
ISSN	0920654X
Journal	Journal of Computer-Aided Molecular Design
Volume Number	30
Issue Number	7
e-ISSN	15734951
Language	English
Publisher	Springer International Publishing
Publisher Date	2016-08-03
Publisher Place	Cham
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Protein structure prediction QMEAN structure agreement Physical Chemistry Computer Applications in Chemistry Animal Anatomy / Morphology / Histology
Content Type	Text
Resource Type	Article
Subject	Drug Discovery Physical and Theoretical Chemistry Computer Science Applications

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