Dataset Information

Highly accurate and high-resolution function prediction of RNA binding proteins by fold recognition and binding affinity prediction.

ABSTRACT: A full understanding of the mechanism of post- transcriptional regulation requires more than simple two- state prediction (binding or not binding) for RNA binding proteins. Here we report a sequence-based technique dedicated for predicting complex structures of protein and RNA by combining fold recognition with binding affinity prediction. The method not only provides a highly accurate complex structure prediction (77% of residues are within 4°A RMSD from native in average for the independent test set) but also achieves the best performing two-state binding or non-binding prediction with an accuracy of 98%, precision of 84%, and Mathews correlation coefficient (MCC) of 0.62. Moreover, it predicts binding residues with an accuracy of 84%, precision of 66% and MCC value of 0.51. In addition, it has a success rate of 77% in predicting RNA binding types (mRNA, tRNA or rRNA). We further demonstrate that it makes more than 10% improvement either in precision or sensitivity than PSI- BLAST, HHPRED and our previously developed structure- based technique. This method expects to be useful for highly accurate genome-scale, high-resolution prediction of RNA-binding proteins and their complex structures. A web server (SPOT) is freely available for academic users at http://sparks.informatics.iupui.edu.

SUBMITTER: Zhao H

PROVIDER: S-EPMC3360076 | biostudies-literature | 2011 Nov-Dec

REPOSITORIES: biostudies-literature

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Highly accurate and high-resolution function prediction of RNA binding proteins by fold recognition and binding affinity prediction.

Zhao Huiying H Yang Yuedong Y Zhou Yaoqi Y

RNA biology 20111101 6

A full understanding of the mechanism of post- transcriptional regulation requires more than simple two- state prediction (binding or not binding) for RNA binding proteins. Here we report a sequence-based technique dedicated for predicting complex structures of protein and RNA by combining fold recognition with binding affinity prediction. The method not only provides a highly accurate complex structure prediction (77% of residues are within 4°A RMSD from native in average for the independent te ...[more]

PMID: 21955494

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Project description:The expression of genes transcribed by the RNA polymerase with the alternative sigma factor sigma 54 (E sigma 54) is absolutely dependent on activator proteins that bind to enhancer-like sites, located far upstream from the promoter. These unique prokaryotic proteins, known as enhancer-binding proteins (EBP), mediate open promoter complex formation in a reaction dependent on NTP hydrolysis. The best characterized proteins of this family of regulators are NtrC and NifA, which activate genes required for ammonia assimilation and nitrogen fixation, respectively. In a recent IRBM course (@ontiers of protein structure prediction," IRBM, Pomezia, Italy, 1995; see web site http://www.mrc-cpe.cam.uk/irbm-course95/), one of us (J.O.) participated in the elaboration of the proposal that the Central domain of the EBPs might adopt the classical mononucleotide-binding fold. This suggestion was based on the results of a new protein fold recognition algorithm (Map) and in the mapping of correlated mutations calculated for the sequence family on the same mononucleotide-binding fold topology. In this work, we present new data that support the previous conclusion. The results from a number of different secondary structure prediction programs suggest that the Central domain could adopt an alpha/beta topology. The fold recognition programs ProFIT 0.9, 3D PROFILE combined with secondary structure prediction, and 123D suggest a mononucleotide-binding fold topology for the Central domain amino acid sequence. Finally, and most importantly, three of five reported residue alterations that impair the Central domain. ATPase activity of the E sigma 54 activators are mapped to polypeptide regions that might be playing equivalent roles as those involved in nucleotide-binding in the mononucleotide-binding proteins. Furthermore, the known residue substitution that alter the function of the E sigma 54 activators, leaving intact the Central domain ATPase activity, are mapped on region proposed to play an equivalent role as the effector region of the GTPase superfamily.

Dataset Information

Highly accurate and high-resolution function prediction of RNA binding proteins by fold recognition and binding affinity prediction.

Publications

Highly accurate and high-resolution function prediction of RNA binding proteins by fold recognition and binding affinity prediction.

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