Exploring the extremes of sequence/structure space with ensemble fold recognition in the program Phyre

Abstract

Structural and functional annotation of the large and growing database of genomic sequences is a major problem in modern biology. Protein structure prediction by detecting remote homology to known structures is a well-established and successful annotation technique. However, the broad spectrum of evolutionary change that accompanies the divergence of close homologues to become remote homologues cannot easily be captured with a single algorithm. Recent advances to tackle this problem have involved the use of multiple predictive algorithms available on the Internet. Here we demonstrate how such ensembles of predictors can be designed in-house under controlled conditions and permit significant improvements in recognition by using a concept taken from protein loop energetics and applying it to the general problem of 3D clustering. We have developed a stringent test that simulates the situation where a protein sequence of interest is submitted to multiple different algorithms and not one of these algorithms can make a confident (95%) correct assignment. A method of meta-server prediction (Phyre) that exploits the benefits of a controlled environment for the component methods was implemented. At 95% precision or higher, Phyre identified 64.0% of all correct homologous query-template relationships, and 84.0% of the individual test query proteins could be accurately annotated. In comparison to the improvement that the single best fold recognition algorithm (according to training) has over PSI-Blast, this represents a 29.6% increase in the number of correct homologous query-template relationships, and a 46.2% increase in the number of accurately annotated queries. It has been well recognised in fold prediction, other bioinformatics applications, and in many other areas, that ensemble predictions generally are superior in accuracy to any of the component individual methods. However there is a paucity of information as to why the ensemble methods are superior and indeed this has never been systematically addressed in fold recognition. Here we show that the source of ensemble power stems from noise reduction in filtering out false positive matches. The results indicate greater coverage of sequence space and improved model quality, which can consequently lead to a reduction in the experimental workload of structural genomics initiatives.

NrdI, a flavodoxin involved in maintenance of the diferric-tyrosyl radical cofactor in Escherichia coli class Ib ribonucleotide reductase

“…In Desulfovibrio vulgaris Fld, for example, seven acidic residues, without compensating positively charged residues, are within 13 Å of the FMN N(1). A homology model (25,26) of E. coli NrdI based on the structure of B. subtilis NrdI suggests a more neutral or positively charged environment in B. subtilis and E. coli NrdIs, respectively.…”

Alternative splicing converts STIM2 from an activator to an inhibitor of store-operated calcium channels

“…The CAD region is critical for binding and activating Orai1 (Park et al, 2009) as well as stabilizing STIM dimers and oligomers (Covington et al, 2010;Yang et al, 2012). We used homology modeling (Bennett-Lovsey et al, 2008) based on the STIM1-CAD crystal structure (Yang et al, 2012), as well as de novo structure prediction (Lupas et al, 1991), to predict the effect of the 2β insert on CAD structure. While the predicted structure of STIM2α-CAD is quite similar to that of STIM1-CAD, the 2β insert significantly disrupts the helical topology of STIM2β-CAD ( Fig.…”

The Essential Protein for Bacterial Flagella Formation FlgJ Functions as a β-N-Acetylglucosaminidase

“…BlastP searches of the NCBI database for FlgJ homologs were performed using the amino acid sequence of S. enterica FlgJ as the probe. Analyses of sequence data were performed using ClustalW2 software (32), whereas both secondary and tertiary structure predictions were made using Phyre2 (33,34). Nucleotide sequencing of PCR products as well as plasmids was performed by the Genomic Facility of the Advanced Analysis Center, University of Guelph.…”