JPred4:a protein secondary structure prediction server

JPred

Pairwise covariance adds little to secondary structure prediction but improves the prediction of non-canonical local structure

<p>Abstract</p> <p>Background</p> <p>Amino acid sequence probability distributions, or profiles, have been used successfully to predict secondary structure and local structure in proteins. Profile models assume the statistical independence of each position in the sequence, but the energetics of protein folding is better captured in a scoring function that is based on pairwise interactions, like a force field.</p> <p>Results</p> <p>I-sites motifs are short sequence/structure motifs that populate the protein structure database due to energy-driven convergent evolution. Here we show that a pairwise covariant sequence model does not predict alpha helix or beta strand significantly better overall than a profile-based model, but it does improve the prediction of certain loop motifs. The finding is best explained by considering secondary structure profiles as multivariant, all-or-none models, which subsume covariant models. Pairwise covariance is nonetheless present and energetically rational. Examples of negative design are present, where the covariances disfavor non-native structures.</p> <p>Conclusion</p> <p>Measured pairwise covariances are shown to be statistically robust in cross-validation tests, as long as the amino acid alphabet is reduced to nine classes. An updated I-sites local structure motif library that provides sequence covariance information for all types of local structure in globular proteins and a web server for local structure prediction are available at <url>http://www.bioinfo.rpi.edu/bystrc/hmmstr/server.php</url>.</p

: Protein Long Local Structure Prediction

International audienceA relevant and accurate description of three-dimensional (3D) protein structures can be achieved by characterizing recurrent local structures. In a previous study, we developed a library of 120 3D structural prototypes encompassing all known 11-residues long local protein structures and ensuring a good quality of structural approximation. A local structure prediction method was also proposed. Here, overlapping properties of local protein structures in global ones are taken into account to characterize frequent local networks. At the same time, we propose a new long local structure prediction strategy which involves the use of evolutionary information coupled with Support Vector Machines (SVMs). Our prediction is evaluated by a stringent geometrical assessment. Every local structure prediction with a Calpha RMSD less than 2.5 A from the true local structure is considered as correct. A global prediction rate of 63.1% is then reached, corresponding to an improvement of 7.7 points compared with the previous strategy. In the same way, the prediction of 88.33% of the 120 structural classes is improved with 8.65% mean gain. 85.33% of proteins have better prediction results with a 9.43% average gain. An analysis of prediction rate per local network also supports the global improvement and gives insights into the potential of our method for predicting super local structures. Moreover, a confidence index for the direct estimation of prediction quality is proposed. Finally, our method is proved to be very competitive with cutting-edge strategies encompassing three categories of local structure predictions. Proteins 2009. (c) 2009 Wiley-Liss, Inc

Scanning-Electron-Microscopy Study of Corrosion and Surface Features in Glass Microballoons

Gaseous acid treatment (HBr) of surface-hardened binary glass microballoons results in etching and the growth of salt nodules, tubes or whiskers, depending on moisture conditions. Temperatures from 400/sup 0/C to 625/sup 0/C for 24 h or more are required for the effects to be significant. Numerous imperfections, including craters, are documented on the unexposed interiors surfaces. The evident phase separation and nucleation sites suggest a need for better production controls and post-production annealing. 6 figures

Thermal Adaptation of Dihydrofolate Reductase from the Moderate ThermophileGeobacillus stearothermophilus

The thermal melting temperature of dihydrofolate reductase from Geobacillus stearothermophilus (BsDHFR) is 30 °C higher than that of its homologue from the psychrophile Moritella profunda. Additional proline residues in the loop regions of BsDHFR have been proposed to enhance the thermostability of BsDHFR, but site-directed mutagenesis studies reveal that these proline residues contribute only minimally. Instead, the high thermal stability of BsDHFR is partly due to removal of water-accessible thermolabile residues such as glutamine and methionine, which are prone to hydrolysis or oxidation at high temperatures. The extra thermostability of BsDHFR can be obtained by ligand binding, or in the presence of salts or cosolvents such as glycerol and sucrose. The sum of all these incremental factors allows BsDHFR to function efficiently in the natural habitat of G. stearothermophilus, which is characterized by temperatures that can reach 75 °C