Zebra: a web server for bioinformatic analysis of diverse protein families

During evolution of proteins from a common ancestor, one functional property can be preserved while others can vary leading to functional diversity. A systematic study of the corresponding adaptive mutations provides a key to one of the most challenging problems of modern structural biology – understanding the impact of amino acid substitutions on protein function. The subfamily-specific positions (SSPs) are conserved within functional subfamilies but are different between them and, therefore, seem to be responsible for functional diversity in protein superfamilies. Consequently, a corresponding method to perform the bioinformatic analysis of sequence and structural data has to be implemented in the common laboratory practice to study the structure–function relationship in proteins and develop novel protein engineering strategies. This paper describes Zebra web server – a powerful remote platform that implements a novel bioinformatic analysis algorithm to study diverse protein families. It is the first application that provides specificity determinants at different levels of functional classification, therefore addressing complex functional diversity of large superfamilies. Statistical analysis is implemented to automatically select a set of highly significant SSPs to be used as hotspots for directed evolution or rational design experiments and analyzed studying the structure–function relationship. Zebra results are provided in two ways – (1) as a single all-in-one parsable text file and (2) as PyMol sessions with structural representation of SSPs. Zebra web server is available at http://biokinet.belozersky.msu.ru/zebra.     

The PredictProtein server

PredictProtein (PP, http://cubic.bioc.columbia.edu/pp/) is an internet service for sequence analysis and the prediction of aspects of protein structure and function. Users submit protein sequence or alignments; the server returns a multiple sequence alignment, PROSITE sequence motifs, low-complexity regions (SEG), ProDom domain assignments, nuclear localisation signals, regions lacking regular structure and predictions of secondary structure, solvent accessibility, globular regions, transmembrane helices, coiled-coil regions, structural switch regions and disulfide-bonds. Upon request, fold recognition by prediction-based threading is available. For all services, users can submit their query either by electronic mail or interactively from World Wide Web.     

The morph server: a standardized system for analyzing and visualizing macromolecular motions in a database framework

The number of solved structures of macromolecules that have the same fold and thus exhibit some degree of conformational variability is rapidly increasing. It is consequently advantageous to develop a standardized terminology for describing this variability and automated systems for processing protein structures in different conformations. We have developed such a system as a 'front-end' server to our database of macromolecular motions. Our system attempts to describe a protein motion as a rigid-body rotation of a small 'core' relative to a larger one, using a set of hinges. The motion is placed in a standardized coordinate system so that all statistics between any two motions are directly comparable. We find that while this model can accommodate most protein motions, it cannot accommodate all; the degree to which a motion can be accommodated provides an aid in classifying it. Furthermore, we perform an adiabatic mapping (a restrained interpolation) between every two conformations. This gives some indication of the extent of the energetic barriers that need to be surmounted in the motion, and as a by-product results in a 'morph movie'. We make these movies available over the Web to aid in visualization. Many instances of conformational variability occur between proteins with somewhat different sequences. We can accommodate these differences in a rough fashion, generating an 'evolutionary morph'. Users have already submitted hundreds of examples of protein motions to our server, producing a comprehensive set of statistics. So far the statistics show that the median submitted motion has a rotation of approximately 10 degrees and a maximum Calpha displacement of 17 A. Almost all involve at least one large torsion angle change of >140 degrees. The server is accessible at http://bioinfo.mbb.yale. edu/MolMovDB     

The BiSearch web server

Background  

A large number of PCR primer-design softwares are available online. However, only very few of them can be used for the design of primers to amplify bisulfite-treated DNA templates, necessary to determine genomic DNA methylation profiles. Indeed, the number of studies on bisulfite-treated templates exponentially increases as determining DNA methylation becomes more important in the diagnosis of cancers. Bisulfite-treated DNA is difficult to amplify since undesired PCR products are often amplified due to the increased sequence redundancy after the chemical conversion. In order to increase the efficiency of PCR primer-design, we have developed BiSearch web server, an online primer-design tool for both bisulfite-treated and native DNA templates.     

Reliability-oriented bioinformatic networks visualization

SUMMARY: We present our protein-protein interaction (PPI) network visualization system RobinViz (reliability-oriented bioinformatic networks visualization). Clustering the PPI network based on gene ontology (GO) annotations or biclustered gene expression data, providing a clustered visualization model based on a central/peripheral duality, computing layouts with algorithms specialized for interaction reliabilities represented as weights, completely automated data acquisition, processing are notable features of the system. AVAILABILITY: RobinViz is a free, open-source software protected under GPL. It is written in C++ and Python, and consists of almost 30 000 lines of code, excluding the employed libraries. Source code, user manual and other Supplementary Material are available for download at http://code.google.com/p/robinviz/.     

The PSIPRED protein structure prediction server

SUMMARY: The PSIPRED protein structure prediction server allows users to submit a protein sequence, perform a prediction of their choice and receive the results of the prediction both textually via e-mail and graphically via the web. The user may select one of three prediction methods to apply to their sequence: PSIPRED, a highly accurate secondary structure prediction method; MEMSAT 2, a new version of a widely used transmembrane topology prediction method; or GenTHREADER, a sequence profile based fold recognition method. AVAILABILITY: Freely available to non-commercial users at http://globin.bio.warwick.ac.uk/psipred/     

The HMMTOP transmembrane topology prediction server

The HMMTOP transmembrane topology prediction server predicts both the localization of helical transmembrane segments and the topology of transmembrane proteins. Recently, several improvements have been introduced to the original method. Now, the user is allowed to submit additional information about segment localization to enhance the prediction power. This option improves the prediction accuracy as well as helps the interpretation of experimental results, i.e. in epitope insertion experiments. Availability: HMMTOP 2.0 is freely available to non-commercial users at http://www.enzim.hu/hmmtop. Source code is also available upon request to academic users.     

The MEMPACK alpha-helical transmembrane protein structure prediction server

MOTIVATION: The experimental difficulties of alpha-helical transmembrane protein structure determination make this class of protein an important target for sequence-based structure prediction tools. The MEMPACK prediction server allows users to submit a transmembrane protein sequence and returns transmembrane topology, lipid exposure, residue contacts, helix-helix interactions and helical packing arrangement predictions in both plain text and graphical formats using a number of novel machine learning-based algorithms. AVAILABILITY: The server can be accessed as a new component of the PSIPRED portal by at http://bioinf.cs.ucl.ac.uk/psipred/.     

Genome bioinformatic analysis of nonsynonymous SNPs

Background  

Genome-wide association studies of common diseases for common, low penetrance causal variants are underway. A proportion of these will alter protein sequences, the most common of which is the non-synonymous single nucleotide polymorphism (nsSNP). It would be an advantage if the functional effects of an nsSNP on protein structure and function could be predicted, both for the final identification process of a causal variant in a disease-associated chromosome region, and in further functional analyses of the nsSNP and its disease-associated protein.     

Novel bioinformatic developments for exome sequencing

With the widespread adoption of next generation sequencing technologies by the genetics community and the rapid decrease in costs per base, exome sequencing has become a standard within the repertoire of genetic experiments for both research and diagnostics. Although bioinformatics now offers standard solutions for the analysis of exome sequencing data, many challenges still remain; especially the increasing scale at which exome data are now being generated has given rise to novel challenges in how to efficiently store, analyze and interpret exome data of this magnitude. In this review we discuss some of the recent developments in bioinformatics for exome sequencing and the directions that this is taking us to. With these developments, exome sequencing is paving the way for the next big challenge, the application of whole genome sequencing.     

IMpRH server: an RH mapping server available on the Web

SUMMARY: The INRA-Minnesota Porcine Radiation Hybrid (IMpRH) Server provides both a mapping tool (IMpRH mapping tool) and a database (IMpRH database) of officially submitted results. The mapping tool permits the mapping of a new marker relatively to markers previously mapped on the IMpRH panel. The IMpRH database is the official database for submission of new results and queries. The database not only permits the sharing of public data but also semi-private and private data.     

The DISOPRED server for the prediction of protein disorder

Dynamically disordered regions appear to be relatively abundant in eukaryotic proteomes. The DISOPRED server allows users to submit a protein sequence, and returns a probability estimate of each residue in the sequence being disordered. The results are sent in both plain text and graphical formats, and the server can also supply predictions of secondary structure to provide further structural information. AVAILABILITY: The server can be accessed by non-commercial users at http://bioinf.cs.ucl.ac.uk/disopred/     

The LabelHash server and tools for substructure-based functional annotation

SUMMARY: The LabelHash server and tools are designed for large-scale substructure comparison. The main use is to predict the function of unknown proteins. Given a set of (putative) functional residues, LabelHash finds all occurrences of matching substructures in the entire Protein Data Bank, along with a statistical significance estimate and known functional annotations for each match. The results can be downloaded for further analysis in any molecular viewer. For Chimera, there is a plugin to facilitate this process. AVAILABILITY: The web site is free and open to all users with no login requirements at http://labelhash.kavrakilab.org     

Identifiying human MHC supertypes using bioinformatic methods

Classification of MHC molecules into supertypes in terms of peptide-binding specificities is an important issue, with direct implications for the development of epitope-based vaccines with wide population coverage. In view of extremely high MHC polymorphism (948 class I and 633 class II HLA alleles) the experimental solution of this task is presently impossible. In this study, we describe a bioinformatics strategy for classifying MHC molecules into supertypes using information drawn solely from three-dimensional protein structure. Two chemometric techniques-hierarchical clustering and principal component analysis-were used independently on a set of 783 HLA class I molecules to identify supertypes based on structural similarities and molecular interaction fields calculated for the peptide binding site. Eight supertypes were defined: A2, A3, A24, B7, B27, B44, C1, and C4. The two techniques gave 77% consensus, i.e., 605 HLA class I alleles were classified in the same supertype by both methods. The proposed strategy allowed "supertype fingerprints" to be identified. Thus, the A2 supertype fingerprint is Tyr(9)/Phe(9), Arg(97), and His(114) or Tyr(116); the A3-Tyr(9)/Phe(9)/Ser(9), Ile(97)/Met(97) and Glu(114) or Asp(116); the A24-Ser(9) and Met(97); the B7-Asn(63) and Leu(81); the B27-Glu(63) and Leu(81); for B44-Ala(81); the C1-Ser(77); and the C4-Asn(77).