The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling

MOTIVATION: Homology models of proteins are of great interest for planning and analysing biological experiments when no experimental three-dimensional structures are available. Building homology models requires specialized programs and up-to-date sequence and structural databases. Integrating all required tools, programs and databases into a single web-based workspace facilitates access to homology modelling from a computer with web connection without the need of downloading and installing large program packages and databases. RESULTS: SWISS-MODEL workspace is a web-based integrated service dedicated to protein structure homology modelling. It assists and guides the user in building protein homology models at different levels of complexity. A personal working environment is provided for each user where several modelling projects can be carried out in parallel. Protein sequence and structure databases necessary for modelling are accessible from the workspace and are updated in regular intervals. Tools for template selection, model building and structure quality evaluation can be invoked from within the workspace. Workflow and usage of the workspace are illustrated by modelling human Cyclin A1 and human Transmembrane Protease 3. AVAILABILITY: The SWISS-MODEL workspace can be accessed freely at http://swissmodel.expasy.org/workspace/     

WebFARM: web server for finite automated restriction mapping

Restriction endonucleases are indispensable tools in molecular biology and biotechnology. Type II restriction endonucleases are part of restriction modification systems. DNA fragment extraction and restriction mapping are the basis for several biotechnological activities. WebFARM is a server application for identifying restriction endonuclease recognition sites and to give information regarding restriction mapping for given nucleotide sequences. WebFARM analyses given nucleotide sequence and identify restriction site for selected restriction endonucleases. It will also provide frequency of restriction for each restriction endonuclease. AVAILABILITY: http://webfarm.bioinfoindia.org/     

PRASA: An integrated web server that analyzes protein interaction types

This work presents the Protein Association Analyzer (PRASA) (http://zoro.ee.ncku.edu.tw/prasa/) that predicts protein interactions as well as interaction types. Protein interactions are essential to most biological functions. The existence of diverse interaction types, such as physically contacted or functionally related interactions, makes protein interactions complex. Different interaction types are distinct and should not be confused. However, most existing tools focus on a specific interaction type or mix different interaction types. This work collected 7234058 associations with experimentally verified interaction types from five databases and compiled individual probabilistic models for different interaction types. The PRASA result page shows predicted associations and their related references by interaction type. Experimental results demonstrate the performance difference when distinguishing between different interaction types. The PRASA provides a centralized and organized platform for easy browsing, downloading and comparing of interaction types, which helps reveal insights into the complex roles that proteins play in organisms.     

Primer Prim'r: A web based server for automated primer design

The Northeast Structural Genomics Consortium (NESG) is one of nine NIH-funded pilot projects created to develop technologies needed for structural studies of proteins on a genome-wide scale. One of the most challenging aspects of this emerging field is the production of protein samples amenable to structural determination. To do this efficiently, all steps in the protein production pipeline must be automated. Here we describe the Primer program (linked from http://www-nmr.cabm.rutgers.edu/bioinformatics, www-nmr.cabm.rutgers.edu/bioinformatics, a web-based primer design program freely available to the scientific community, which was created to automate this time consuming and laborious task. This program has the ability to simultaneously calculate plasmid specific primer sets for multiple open reading frame (ORF) targets, including 96-well and greater formats. Primer includes a library of commonly used plasmid systems and possesses the ability to upload user-defined plasmid systems. In addition to calculating gene-specific annealing regions for each target, the program also adds appropriate restriction endonuclease recognition or viral recombination sites while preserving a reading frame with plasmid based fusions. Primer has several useful features such as sorting calculated primer sets by target size, facilitating interpretation of PCR amplifications by agarose gel electrophoresis, as well as supplying the molecular biologist with many important characteristics of each target such as the expected size of the PCR amplified DNA fragment and internal restriction sites. The NESG has cloned over 1500 genes using oligonucleotide primers designed by Primer.     

An incremental approach to automated protein localisation

Background  

The subcellular localisation of proteins in intact living cells is an important means for gaining information about protein functions. Even dynamic processes can be captured, which can barely be predicted based on amino acid sequences. Besides increasing our knowledge about intracellular processes, this information facilitates the development of innovative therapies and new diagnostic methods. In order to perform such a localisation, the proteins under analysis are usually fused with a fluorescent protein. So, they can be observed by means of a fluorescence microscope and analysed. In recent years, several automated methods have been proposed for performing such analyses. Here, two different types of approaches can be distinguished: techniques which enable the recognition of a fixed set of protein locations and methods that identify new ones. To our knowledge, a combination of both approaches – i.e. a technique, which enables supervised learning using a known set of protein locations and is able to identify and incorporate new protein locations afterwards – has not been presented yet. Furthermore, associated problems, e.g. the recognition of cells to be analysed, have usually been neglected.     

PISCES: a protein sequence culling server

PISCES is a public server for culling sets of protein sequences from the Protein Data Bank (PDB) by sequence identity and structural quality criteria. PISCES can provide lists culled from the entire PDB or from lists of PDB entries or chains provided by the user. The sequence identities are obtained from PSI-BLAST alignments with position-specific substitution matrices derived from the non-redundant protein sequence database. PISCES therefore provides better lists than servers that use BLAST, which is unable to identify many relationships below 40% sequence identity and often overestimates sequence identity by aligning only well-conserved fragments. PDB sequences are updated weekly. PISCES can also cull non-PDB sequences provided by the user as a list of GenBank identifiers, a FASTA format file, or BLAST/PSI-BLAST output.     

PDBcor: An automated correlation extraction calculator for multi-state protein structures

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An automated filtration assay for protein kinase C ligands

[3H]Phorbol dibutyrate ([3H]PDBu) binding to soluble mouse brain protein kinase C (PKC) was established in a 96-well microtiter plate assay. [3H]PDBu-PKC receptor complexes were rapidly aspirated from wells, filtered, and washed onto glass fiber filter mats using an automated cell harvester. Results were compared to a modification of a previously described assay in which components were incubated in tubes, and manually delivered and washed onto filters with a manifold filtration apparatus. Both 96-well plate and tube assays gave qualitatively and quantitatively similar results since: (i) [3H]PDBu binding to PKC was phosphatidylserine (PS) dependent and calcium stimulatable; (ii) the amounts of [3H]PDBu bound by filters with each technique at receptors excess were similar, 3.2 +/- 0.3 and 3.1 +/- 0.4 pmol respectively; and (iii) the affinities of [3H]PDBu for PKC were comparable; Kd's were 1.95 +/- 0.3 and 2.2 +/- 0.55 nM, respectively. The 96-well plate assay was more accurate and rapid than the tube assay. The microtiter plate assay was adapted for use with [N,N-dimethyl-3H]N,N-dimethylstaurosporine ([3H]DMS). With [3H]PDBu and [3H]DMS as ligands, the 96-well plate method was used for the rapid discrimination of agents which bound selectively at the regulatory and/or catalytic domains of PKC.     

BPROMPT: A consensus server for membrane protein prediction

Protein structure prediction is a cornerstone of bioinformatics research. Membrane proteins require their own prediction methods due to their intrinsically different composition. A variety of tools exist for topology prediction of membrane proteins, many of them available on the Internet. The server described in this paper, BPROMPT (Bayesian PRediction Of Membrane Protein Topology), uses a Bayesian Belief Network to combine the results of other prediction methods, providing a more accurate consensus prediction. Topology predictions with accuracies of 70% for prokaryotes and 53% for eukaryotes were achieved. BPROMPT can be accessed at http://www.jenner.ac.uk/BPROMPT.     

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/     

An automated pipeline to screen membrane protein 2D crystallization

Electron crystallography relies on electron cryomicroscopy of two-dimensional (2D) crystals and is particularly well suited for studying the structure of membrane proteins in their native lipid bilayer environment. To obtain 2D crystals from purified membrane proteins, the detergent in a protein–lipid–detergent ternary mixture must be removed, generally by dialysis, under conditions favoring reconstitution into proteoliposomes and formation of well-ordered lattices. To identify these conditions a wide range of parameters such as pH, lipid composition, lipid-to-protein ratio, ionic strength and ligands must be screened in a procedure involving four steps: crystallization, specimen preparation for electron microscopy, image acquisition, and evaluation. Traditionally, these steps have been carried out manually and, as a result, the scope of 2D crystallization trials has been limited. We have therefore developed an automated pipeline to screen the formation of 2D crystals. We employed a 96-well dialysis block for reconstitution of the target protein over a wide range of conditions designed to promote crystallization. A 96-position magnetic platform and a liquid handling robot were used to prepare negatively stained specimens in parallel. Robotic grid insertion into the electron microscope and computerized image acquisition ensures rapid evaluation of the crystallization screen. To date, 38 2D crystallization screens have been conducted for 15 different membrane proteins, totaling over 3000 individual crystallization experiments. Three of these proteins have yielded diffracting 2D crystals. Our automated pipeline outperforms traditional 2D crystallization methods in terms of throughput and reproducibility.     

An automated decision-tree approach to predicting protein interaction hot spots

Protein-protein interactions can be altered by mutating one or more "hot spots," the subset of residues that account for most of the interface's binding free energy. The identification of hot spots requires a significant experimental effort, highlighting the practical value of hot spot predictions. We present two knowledge-based models that improve the ability to predict hot spots: K-FADE uses shape specificity features calculated by the Fast Atomic Density Evaluation (FADE) program, and K-CON uses biochemical contact features. The combined K-FADE/CON (KFC) model displays better overall predictive accuracy than computational alanine scanning (Robetta-Ala). In addition, because these methods predict different subsets of known hot spots, a large and significant increase in accuracy is achieved by combining KFC and Robetta-Ala. The KFC analysis is applied to the calmodulin (CaM)/smooth muscle myosin light chain kinase (smMLCK) interface, and to the bone morphogenetic protein-2 (BMP-2)/BMP receptor-type I (BMPR-IA) interface. The results indicate a strong correlation between KFC hot spot predictions and mutations that significantly reduce the binding affinity of the interface.     

An automated protein annotation filter for integrating web-based annotation tools

A wide range of web based prediction and annotation tools are frequently used for determining protein function from sequence. However, parallel processing of sequences for annotation through web tools is not possible due to several constraints in functional programming for multiple queries. Here, we propose the development of APAF as an automated protein annotation filter to overcome some of these difficulties through an integrated approach.     

An automated approach to network features of protein structure ensembles

Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone‐efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user‐friendly, standalone program package named PSN‐Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X‐ray structures. The novelty in network construction lies in the explicit consideration of side‐chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long‐range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross‐correlation/interaction energy in PSN‐Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN‐Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin‐conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN‐Ensemble for single‐static structures of active/inactive states of β2‐adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN‐Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN‐Ensemble/psn_index.html .     

MOFOID--not only the protein modeling server

MOFOID is a new server developed mainly for automated modeling of protein structures by their homology to the structures deposited in the PDB database. Selection of a template and calculation of the alignment is performed with the Smith-Waterman or Needleman-Wunsch algorithms implemented in the EMBOSS package. The final model is built and optimised with programs from the JACKAL package. The wide spectrum of options in the web-based interface and the possibility of uploading user's own alignment make MOFOID a suitable platform for testing new approaches in the alignment building. The server is available at https:// valis.ibb.waw.pl/mofoid/.