UNLABELLED: XtalPred is a web server for prediction of protein crystallizability. The prediction is made by comparing several features of the protein with distributions of these features in TargetDB and combining the results into an overall probability of crystallization. XtalPred provides: (1) a detailed comparison of the protein's features to the corresponding distribution from TargetDB; (2) a summary of protein features and predictions that indicate problems that are likely to be encountered during protein crystallization; (3) prediction of ligands; and (4) (optional) lists of close homologs from complete microbial genomes that are more likely to crystallize. AVAILABILITY: The XtalPred web server is freely available for academic users on http://ffas.burnham.org/XtalPred

BACKGROUND: 3D-Jury, the structure prediction consensus method publicly available in the Meta Server http://meta.bioinfo.pl/, was evaluated using models gathered in the 7th round of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7). 3D-Jury is an automated expert process that generates protein structure meta-predictions from sets of models obtained from partner servers. RESULTS: The performance of 3D-Jury was analysed for three aspects. First, we examined the correlation between the 3D-Jury score and a model quality measure: the number of correctly predicted residues. The 3D-Jury score was shown to correlate significantly with the number of correctly predicted residues, the correlation is good enough to be used for prediction. 3D-Jury was also found to improve upon the competing servers' choice of the best structure model in most cases. The value of the 3D-Jury score as a generic reliability measure was also examined. We found that the 3D-Jury score separates bad models from good models better than the reliability score of the original server in 27 cases and falls short of it in only 5 cases out of a total of 38. We report the release of a new Meta Server feature: instant 3D-Jury scoring of uploaded user models. CONCLUSION: The 3D-Jury score continues to be a good indicator of structural model quality. It also provides a generic reliability score, especially important for models that were not assigned such by the original server. Individual structure modellers can also benefit from the 3D-Jury scoring system by testing their models in the new instant scoring feature http://meta.bioinfo.pl/compare_your_model_example.pl available in the Meta Server.

BACKGROUND: The number of protein structures from structural genomics centers dramatically increases in the Protein Data Bank (PDB). Many of these structures are functionally unannotated because they have no sequence similarity to proteins of known function. However, it is possible to successfully infer function using only structural similarity. RESULTS: Here we present the PDB-UF database, a web-accessible collection of predictions of enzymatic properties using structure-function relationship. The assignments were conducted for three-dimensional protein structures of unknown function that come from structural genomics initiatives. We show that 4 hypothetical proteins (with PDB accession codes: 1VH0, 1NS5, 1O6D, and 1TO0), for which standard BLAST tools such as PSI-BLAST or RPS-BLAST failed to assign any function, are probably methyltransferase enzymes. CONCLUSION: We suggest that the structure-based prediction of an EC number should be conducted having the different similarity score cutoff for different protein folds. Moreover, performing the annotation using two different algorithms can reduce the rate of false positive assignments. We believe, that the presented web-based repository will help to decrease the number of protein structures that have functions marked as "unknown" in the PDB file. AVAILABILITY: http://paradox.harvard.edu/PDB-UF and http://bioinfo.pl/PDB-UF.

UNLABELLED: The AutoMotif Server allows for identification of post-translational modification (PTM) sites in proteins based only on local sequence information. The local sequence preferences of short segments around PTM residues are described here as linear functional motifs (LFMs). Sequence models for all types of PTMs are trained by support vector machine on short-sequence fragments of proteins in the current release of Swiss-Prot database (phosphorylation by various protein kinases, sulfation, acetylation, methylation, amidation, etc.). The accuracy of the identification is estimated using the standard leave-one-out procedure. The sensitivities for all types of short LFMs are in the range of 70%. AVAILABILITY: The AutoMotif Server is available free for academic use at http://automotif.bioinfo.pl/

UNLABELLED: The PDB-Preview database is a dynamic web repository of in-silico predicted three-dimensional (3D) models of experimentally determined structures that are deposited into the PDB but are not yet publicly released, and are kept 'on-hold'. The PDB-Preview database is automatically generated on a weekly basis by the bioinfo.pl meta-server, which uses top-of-the-line fold-recognition methods. The PDB-Preview provides biologists with preliminary fold assignments well before the experimentally determined 3D structures are released. AVAILABILITY: http://bioinfo.pl/PDB-Preview/.

BACKGROUND: Defining blocks forming the global protein structure on the basis of local structural regularity is a very fruitful idea, extensively used in description, and prediction of structure from only sequence information. Over many years the secondary structure elements were used as available building blocks with great success. Specially prepared sets of possible structural motifs can be used to describe similarity between very distant, non-homologous proteins. The reason for utilizing the structural information in the description of proteins is straightforward. Structural comparison is able to detect approximately twice as many distant relationships as sequence comparison at the same error rate. RESULTS: Here we provide a new fragment library for Local Structure Segment (LSS) prediction called FRAGlib which is integrated with a previously described segment alignment algorithm SEA. A joined FRAGlib/SEA server provides easy access to both algorithms, allowing a one stop alignment service using a novel approach to protein sequence alignment based on a network matching approach. The FRAGlib used as secondary structure prediction achieves only 73% accuracy in Q3 measure, but when combined with the SEA alignment, it achieves a significant improvement in pairwise sequence alignment quality, as compared to previous SEA implementation and other public alignment algorithms. The FRAGlib algorithm takes approximately 2 min. to search over FRAGlib database for a typical query protein with 500 residues. The SEA service align two typical proteins within circa approximately 5 min. All supplementary materials (detailed results of all the benchmarks, the list of test proteins and the whole fragments library) are available for download on-line at http://ffas.ljcrf.edu/darman/results/. CONCLUSIONS: The joined FRAGlib/SEA server will be a valuable tool both for molecular biologists working on protein sequence analysis and for bioinformaticians developing computational methods of structure prediction and alignment of proteins.

MOTIVATION: Consensus structure prediction methods (meta-predictors) have higher accuracy than individual structure prediction algorithms (their components). The goal for the development of the 3D-Jury system is to create a simple but powerful procedure for generating meta-predictions using variable sets of models obtained from diverse sources. The resulting protocol should help to improve the quality of structural annotations of novel proteins. RESULTS: The 3D-Jury system generates meta-predictions from sets of models created using variable methods. It is not necessary to know prior characteristics of the methods. The system is able to utilize immediately new components (additional prediction providers). The accuracy of the system is comparable with other well-tuned prediction servers. The algorithm resembles methods of selecting models generated using ab initio folding simulations. It is simple and offers a portable solution to improve the accuracy of other protein structure prediction protocols. AVAILABILITY: The 3D-Jury system is available via the Structure Prediction Meta Server (http://BioInfo.PL/Meta/) to the academic community. SUPPLEMENTARY INFORMATION: 3D-Jury is coupled to the continuous online server evaluation program, LiveBench (http://BioInfo.PL/LiveBench/)

MOTIVATION: The Ligand-Info system is based on the assumption that small molecules with similar structure have similar functional (binding) properties. The developed system enables a fast and sensitive index based search for similar compounds in large databases. Index profiles, constructed by averaging indexes of related molecules are used to increase the specificity of the search. The utilization of index profiles helps to focus on frequent, common features of a family of compounds. RESULTS: A Java-based tool for clustering and scanning of small molecules has been created. The tool can interactively cluster sets of molecules and create index profiles on the user side and automatically download similar molecules from a databases of 250 000 compounds. The results of the application of index profiles demonstrate that the profile based search strategy can increase the quality of the selection process. AVAILABILITY: The system is available at http://Ligand.Info. The application requires the Java Runtime Environment 1.4, which can be automatically installed during the first use on desktop systems, which support it. A standalone version of the program is available from the authors upon request.

Abstract * To whom correspondence should be addressed [email protected]

BACKGROUND: Escherichia coli guanine-N2 (m2G) methyltransferases (MTases) RsmC and RsmD modify nucleosides G1207 and G966 of 16S rRNA. They possess a common MTase domain in the C-terminus and a variable region in the N-terminus. Their C-terminal domain is related to the YbiN family of hypothetical MTases, but nothing is known about the structure or function of the N-terminal domain. RESULTS: Using a combination of sequence database searches and fold recognition methods it has been demonstrated that the N-termini of RsmC and RsmD are related to each other and that they represent a "degenerated" version of the C-terminal MTase domain. Novel members of the YbiN family from Archaea and Eukaryota were also indentified. It is inferred that YbiN and both domains of RsmC and RsmD are closely related to a family of putative MTases from Gram-positive bacteria and Archaea, typified by the Mj0882 protein from M. jannaschii (1dus in PDB). Based on the results of sequence analysis and structure prediction, the residues involved in cofactor binding, target recognition and catalysis were identified, and the mechanism of the guanine-N2 methyltransfer reaction was proposed. CONCLUSIONS: Using the known Mj0882 structure, a comprehensive analysis of sequence-structure-function relationships in the family of genuine and putative m2G MTases was performed. The results provide novel insight into the mechanism of m2G methylation and will serve as a platform for experimental analysis of numerous uncharacterized N-MTases.

UNLABELLED: The Structure Prediction Meta Server offers a convenient way for biologists to utilize various high quality structure prediction servers available worldwide. The meta server translates the results obtained from remote services into uniform format, which are consequently used to request a jury prediction from a remote consensus server Pcons. AVAILABILITY: The structure prediction meta server is freely available at http://BioInfo.PL/meta/, some remote servers have however restrictions for non-academic users, which are respected by the meta server. SUPPLEMENTARY INFORMATION: Results of several sessions of the CAFASP and LiveBench programs for assessment of performance of fold-recognition servers carried out via the meta server are available at http://BioInfo.PL/services.html.

UNLABELLED: The ToolShop server offers a possibility to compare a protein tertiary structure prediction server with other popular servers before releasing it to the public. The comparison is conducted on a set of 203 proteins and the collected models are compared with over 20 other programs using various assessment procedures. The evaluation lasts circa one week. AVAILABILITY: The ToolShop server is available at http://BioInfo.PL/ToolShop/. The administrator should be contacted to couple the tested server to the evaluation suite. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: The evaluation procedures are similar to those implemented in the continuous online server evaluation program, LiveBench. Additional information is available from its homepage (http://BioInfo.PL/LiveBench/).

BACKGROUND: The 5'-terminal cap structure plays an important role in many aspects of mRNA metabolism. Capping enzymes encoded by viruses and pathogenic fungi are attractive targets for specific inhibitors. There is a large body of experimental data on viral and cellular methyltransferases (MTases) that carry out guanine-N7 (cap 0) methylation, including results of extensive mutagenesis. However, a crystal structure is not available and cap 0 MTases are too diverged from other MTases of known structure to allow straightforward homology-based interpretation of these data. RESULTS: We report a 3D model of cap 0 MTase, developed using sequence-to-structure threading and comparative modeling based on coordinates of the glycine N-methyltransferase. Analysis of the predicted structural features in the phylogenetic context of the cap 0 MTase family allows us to rationalize most of the experimental data available and to propose potential binding sites. We identified a case of correlated mutations in the cofactor-binding site of viral MTases that may be important for the rational drug design. Furthermore, database searches and phylogenetic analysis revealed a novel subfamily of hypothetical MTases from plants, distinct from "orthodox" cap 0 MTases. CONCLUSIONS: Computational methods were used to infer the evolutionary relationships and predict the structure of Eukaryotic cap MTase. Identification of novel cap MTase homologs suggests candidates for cloning and biochemical characterization, while the structural model will be useful in designing new experiments to better understand the molecular function of cap MTases.

BACKGROUND: Prediction of protein structures is one of the fundamental challenges in biology today. To fully understand how well different prediction methods perform, it is necessary to use measures that evaluate their performance. Every two years, starting in 1994, the CASP (Critical Assessment of protein Structure Prediction) process has been organized to evaluate the ability of different predictors to blindly predict the structure of proteins. To capture different features of the models, several measures have been developed during the CASP processes. However, these measures have not been examined in detail before. In an attempt to develop fully automatic measures that can be used in CASP, as well as in other type of benchmarking experiments, we have compared twenty-one measures. These measures include the measures used in CASP3 and CASP2 as well as have measures introduced later. We have studied their ability to distinguish between the better and worse models submitted to CASP3 and the correlation between them. RESULTS: Using a small set of 1340 models for 23 different targets we show that most methods correlate with each other. Most pairs of measures show a correlation coefficient of about 0.5. The correlation is slightly higher for measures of similar types. We found that a significant problem when developing automatic measures is how to deal with proteins of different length. Also the comparisons between different measures is complicated as many measures are dependent on the size of the target. We show that the manual assessment can be reproduced to about 70% using automatic measures. Alignment independent measures, detects slightly more of the models with the correct fold, while alignment dependent measures agree better when selecting the best models for each target. Finally we show that using automatic measures would, to a large extent, reproduce the assessors ranking of the predictors at CASP3. CONCLUSIONS: We show that given a sufficient number of targets the manual and automatic measures would have given almost identical results at CASP3. If the intent is to reproduce the type of scoring done by the manual assessor in in CASP3, the best approach might be to use a combination of alignment independent and alignment dependent measures, as used in several recent studies.

Abstract Motivation: Evaluating the accuracy of predicted models is critical for assessing structure prediction methods. Because this problem is not trivial, a large number of different assessment measures have been proposed by various authors, and it has already become an active subfield of research (Moult et al. (1999) Critical assessment of methods of protein structure prediction (CASP): round III. Proteins , Suppl32–6). The CASP (Moult et al. (1997) Critical assessment of methods of proteins structure prediction (CASP): round II. Proteins , Suppl3, Dedicated Issue, Moult et al. (1999) Critical assessment of methods of protein structure prediction (CASP): round III. Proteins , Suppl32–6) and CAFASP (Fischer et al. (1999) CAFASP-1: critical assessment of fully automated structure prediction methods. Proteins , Suppl3, 209–217) prediction experiments have demonstrated that it has been difficult to choose one single, ‘best’ method to be used in the evaluation. Consequently, the CASP3 evaluation was carried out using an extensive set of especially developed numerical measures, coupled with human-expert intervention. As part of our efforts towards a higher level of automation in the structure prediction field, here we investigate the suitability of a fully automated, simple, objective, quantitative and reproducible method that can be used in the automatic assessment of models in the upcoming CAFASP2 experiment. Such a method should (a) produce one single number that measures the quality of a predicted model and (b) perform similarly to human-expert evaluations. Results: MaxSub is a new and independently developed method that further builds and extends some of the evaluation methods introduced at CASP3. MaxSub aims at identifying the largest subset of \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \(C_{{\alpha}}\) \end{document}atoms of a model that superimpose ‘well’ over the experimental structure, and produces a single normalized score that represents the quality of the model. Because there exists no evaluation method for assessment measures of predicted models, it is not easy to evaluate how good our new measure is. Even though an exact comparison of MaxSub and the CASP3 assessment is not straightforward, here we use a test-bed extracted from the CASP3 fold-recognition models. A rough qualitative comparison of the performance of MaxSub vis-a-vis the human-expert assessment carried out at CASP3 shows that there is a good agreement for the more accurate models and for the better predicting groups. As expected, some differences were observed among the medium to poor models and groups. Overall, the top six predicting groups ranked using the fully automated MaxSub are also the top six groups ranked at CASP3. We conclude that MaxSub is a suitable method for the automatic evaluation of models. Availability: MaxSub is available at: http://www.cs.bgu.ac.il/~dfischer/MaxSub/MaxSub.html Contact: {nomsiew,dfischer}@cs.bgu.ac.il; [email protected]; [email protected] Supplementary Information: Full tables are available at: http://www.cs.bgu.ac.il/\batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \({\sim}\) \end{document}dfischer/MaxSub/MaxSub.html CASP web site: http://PredictionCenter.llnl.gov/casp3/CAFASP web site: http://www.cs.bgu.ac.il/~dfischer/CAFASP2 To whom correspondence should be addressed.