TMDET: web server for detecting transmembrane regions of proteins by using their 3D coordinates

The structure of integral membrane proteins is determined in the absence of the lipid bilayer; consequently the membrane localization of the protein is usually not specified in the corresponding PDB file. Recently, we have developed a new method called TMDET which determines the most possible localization of the membrane relative to the protein structure, and gives the annotation of the membrane embedded parts of the sequence. The entire Protein Data Bank has been scanned by the new TMDET algorithm resulting in the database of structurally determined transmembrane proteins (PDB_TM). Here we present the web interface of the TMDET algorithm to allow scientists to determine the membrane localization of structural data prior to deposition or to analyze model structures.     

MAPS: an interactive web server for membrane annotation of transmembrane protein structures

The exact positioning of the membrane in transmembrane (TM) proteins plays important functional roles. Yet, the structures of TM proteins in protein data bank (pdb) have no information about the explicit position of the membrane. Using a simple hydrophobic lipid-protein mismatch energy function and a flexible lipid/water boundary, the position of lipid bilayer for representative TM proteins in pdb have been annotated. A web server called MAPS (Membrane Annotation of Protein Structures; available at: http://www.boseinst.ernet.in/gautam/maps) has been set up that allows the user to interactively analyze membrane-protein orientations of any uploaded pdb structure with user-defined membrane flexibility parameters.     

JUZBOX: A web server for extracting biomedical words from the protein sequence

The recognition of gene/protein names in literature is one of the pivotal steps in the processing of biological literatures for information extraction or data mining. We have compiled a lexicon of biomedical words (conserved patterns/ potential motifs) which has the combination of only 20 alphabets of amino acids. The remaining 6 letters of the English alphabets (B, J, O, U, X, Z) are treated as invalid amino acid characters (to our context), We have jumbled the 6 letters for the sake of usage and convenience and termed as ’JUZBOX‘ and these characters were filtered in the biomedical lexicon. Undoubtedly, the generation of biomedical words from protein sequence using JUZBOX have applications specific for functional annotation.

Availability

JUZBOX is available freely at http://www.spices.res.in/juzbox     

I-TASSER server for protein 3D structure prediction

Background  

Prediction of 3-dimensional protein structures from amino acid sequences represents one of the most important problems in computational structural biology. The community-wide Critical Assessment of Structure Prediction (CASP) experiments have been designed to obtain an objective assessment of the state-of-the-art of the field, where I-TASSER was ranked as the best method in the server section of the recent 7th CASP experiment. Our laboratory has since then received numerous requests about the public availability of the I-TASSER algorithm and the usage of the I-TASSER predictions.     

XtalPred: a web server for prediction of protein crystallizability

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     

RANKPROP: a web server for protein remote homology detection

Summary: We present a large-scale implementation of the RANKPROPprotein homology ranking algorithm in the form of an openlyaccessible web server. We use the NRDB40 PSI-BLAST all-versus-allprotein similarity network of 1.1 million proteins to constructthe graph for the RANKPROP algorithm, whereas previously, resultswere only reported for a database of 108 000 proteins. We alsodescribe two algorithmic improvements to the original algorithm,including propagation from multiple homologs of the query andbetter normalization of ranking scores, that lead to higheraccuracy and to scores with a probabilistic interpretation. Availability: The RANKPROP web server and source code are availableat http://rankprop.gs.washington.edu Contact: iain{at}nec-labs.com; noble{at}gs.washington.edu Associate Editor: Burkhard Rost     

The SuMo server: 3D search for protein functional sites

SUMMARY: We provide the scientific community with a web server which gives access to SuMo, a bioinformatic system for finding similarities in arbitrary 3D structures or substructures of proteins. SuMo is based on a unique representation of macromolecules using selected triplets of chemical groups having their own geometry and symmetry, regardless of the restrictive notions of main chain and lateral chains of amino acids. The heuristic for extracting similar sites was used to drive two major large-scale approaches. First, searching for ligand binding sites onto a query structure has been made possible by comparing the structure against each of the ligand binding sites found in the Protein Data Bank (PDB). Second, the reciprocal process, i.e. searching for a given 3D site of interest among the structures of the PDB is also possible and helps detect cross-reacting targets in drug design projects. AVAILABILITY: The web server is freely accessible to academia through http://sumo-pbil.ibcp.fr and full support is available from MEDIT (http://www.medit.fr). CONTACT: mjambon@burnham.org.     

IWS: integrated web server for protein sequence and structure analysis

Rapid increase in protein sequence information from genome sequencing projects demand the intervention of bioinformatics tools to recognize interesting gene-products and associated function. Often, multiple algorithms need to be employed to improve accuracy in predictions and several structure prediction algorithms are on the public domain. Here, we report the availability of an Integrated Web-server as a bioinformatics online package dedicated for in-silico analysis of protein sequence and structure data (IWS). IWS provides web interface to both in-house and widely accepted programs from major bioinformatics groups, organized as 10 different modules. IWS also provides interactive images for Analysis Work Flow, which will provide transparency to the user to carry out analysis by moving across modules seamlessly and to perform their predictions in a rapid manner. AVAILABILITY: IWS IS AVAILABLE FROM THE URL: http://caps.ncbs.res.in/iws.     

R-CHIE: a web server and R package for visualizing RNA secondary structures

Visually examining RNA structures can greatly aid in understanding their potential functional roles and in evaluating the performance of structure prediction algorithms. As many functional roles of RNA structures can already be studied given the secondary structure of the RNA, various methods have been devised for visualizing RNA secondary structures. Most of these methods depict a given RNA secondary structure as a planar graph consisting of base-paired stems interconnected by roundish loops. In this article, we present an alternative method of depicting RNA secondary structure as arc diagrams. This is well suited for structures that are difficult or impossible to represent as planar stem-loop diagrams. Arc diagrams can intuitively display pseudo-knotted structures, as well as transient and alternative structural features. In addition, they facilitate the comparison of known and predicted RNA secondary structures. An added benefit is that structure information can be displayed in conjunction with a corresponding multiple sequence alignments, thereby highlighting structure and primary sequence conservation and variation. We have implemented the visualization algorithm as a web server R-chie as well as a corresponding R package called R4RNA, which allows users to run the software locally and across a range of common operating systems.     

GCI: A network server for interactive 3D graphics

The Graphics Command Interpreter (GCI) is an independent server module that can be interfaced to any program that needs interactive three-dimensional (3D) graphics capabilities. The principal advantage of GCI is its simplicity. Only a limited set of powerful features have been implemented, including object management, global and local transformations, rotation, translation, clipping, scaling, viewport operations, window management, menu handling and picking.GCI and the master (client) program it serves run concurrently, communicating over a local or remote TCP/IP network. GCI sets up socket communication and provides a 3D graphics window and a terminal emulator for the master program. Communication between the two programs is via ASCII strings over standard I/O channels. The implied language for messages is very simple. GCI interprets messages from the master program and implements them as changes of graphical objects or as text messages to the user. GCI provides the user with facilities to manipulate the view of the displayed 3D objects interactively, independently of the master program, and to communicate mouse-controlled selection of menu items or 3D points as well as keyboard strings to the master program.The program is written in C and initially implemented using the Silicon Graphics GL graphics library. As the need to link special libraries to the master program is completely avoided, GCI can very easily be interfaced to existing programs written in any language and running on any operating system capable of TCP/IP communication. The program is freely available.     

InterProSurf: a web server for predicting interacting sites on protein surfaces

A new web server, InterProSurf, predicts interacting amino acid residues in proteins that are most likely to interact with other proteins, given the 3D structures of subunits of a protein complex. The prediction method is based on solvent accessible surface area of residues in the isolated subunits, a propensity scale for interface residues and a clustering algorithm to identify surface regions with residues of high interface propensities. Here we illustrate the application of InterProSurf to determine which areas of Bacillus anthracis toxins and measles virus hemagglutinin protein interact with their respective cell surface receptors. The computationally predicted regions overlap with those regions previously identified as interface regions by sequence analysis and mutagenesis experiments. AVAILABILITY: The InterProSurf web server is available at http://curie.utmb.edu/     

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.     

VADAR: a web server for quantitative evaluation of protein structure quality

VADAR (Volume Area Dihedral Angle Reporter) is a comprehensive web server for quantitative protein structure evaluation. It accepts Protein Data Bank (PDB) formatted files or PDB accession numbers as input and calculates, identifies, graphs, reports and/or evaluates a large number (>30) of key structural parameters both for individual residues and for the entire protein. These include excluded volume, accessible surface area, backbone and side chain dihedral angles, secondary structure, hydrogen bonding partners, hydrogen bond energies, steric quality, solvation free energy as well as local and overall fold quality. These derived parameters can be used to rapidly identify both general and residue-specific problems within newly determined protein structures. The VADAR web server is freely accessible at http://redpoll.pharmacy.ualberta.ca/vadar.     

LGA: A method for finding 3D similarities in protein structures

We present the LGA (Local-Global Alignment) method, designed to facilitate the comparison of protein structures or fragments of protein structures in sequence dependent and sequence independent modes. The LGA structure alignment program is available as an online service at http://PredictionCenter.llnl.gov/local/lga. Data generated by LGA can be successfully used in a scoring function to rank the level of similarity between two structures and to allow structure classification when many proteins are being analyzed. LGA also allows the clustering of similar fragments of protein structures.