PROTMAP2D: visualization, comparison and analysis of 2D maps of protein structure

MOTIVATION: Protein structure comparison is a fundamental problem in structural biology and bioinformatics. Two-dimensional maps of distances between residues in the structure contain sufficient information to restore the 3D representation, while maps of contacts reveal characteristic patterns of interactions between secondary and super-secondary structures and are very attractive for visual analysis. The overlap of 2D maps of two structures can be easily calculated, providing a sensitive measure of protein structure similarity. PROTMAP2D is a software tool for calculation of contact and distance maps based on user-defined criteria, quantitative comparison of pairs or series of contact maps (e.g. alternative models of the same protein, model versus native structure, different trajectories from molecular dynamics simulations, etc.) and visualization of the results. AVAILABILITY: PROTMAP2D for Windows / Linux / MacOSX is freely available for academic users from http://genesilico.pl/protmap2d.htm     

Voro3D: 3D Voronoi tessellations applied to protein structures

SUMMARY: Voro3D is an original easy-to-use tool, which provides a brand new point of view on protein structures through the three-dimensional (3D) Voronoi tessellations. To construct the Voronoi cells associated with each amino acid by a number of different tessellation methods, Voro3D uses a protein structure file in the PDB format as an input. After calculation, different structural properties of interest like secondary structures assignment, environment accessibility and exact contact matrices can be derived without any geometrical cut-off. Voro3D provides also a visualization of these tessellations superimposed on the associated protein structure, from which it is possible to model a polygonal protein surface using a model solvent or to quantify, for instance, the contact areas between a protein and a ligand. AVAILABILITY: The software executable file for PC using Windows 98, 2000, NT, XP can be freely downloaded at http://www.lmcp.jussieu.fr/~mornon/voronoi.html CONTACT: franck.dupuis@sanofi-aventis.com; jean-paul-mornon@imcp.jussieu.fr.     

Reconstruction of 3D structures from protein contact maps

The prediction of the protein tertiary structure from solely its residue sequence (the so called Protein Folding Problem) is one of the most challenging problems in Structural Bioinformatics. We focus on the protein residue contact map. When this map is assigned it is possible to reconstruct the 3D structure of the protein backbone. The general problem of recovering a set of 3D coordinates consistent with some given contact map is known as a unit-disk-graph realization problem and it has been recently proven to be NP-Hard. In this paper we describe a heuristic method (COMAR) that is able to reconstruct with an unprecedented rate (3-15 seconds) a 3D model that exactly matches the target contact map of a protein. Working with a non-redundant set of 1760 proteins, we find that the scoring efficiency of finding a 3D model very close to the protein native structure depends on the threshold value adopted to compute the protein residue contact map. Contact maps whose threshold values range from 10 to 18 Ångstroms allow reconstructing 3D models that are very similar to the proteins native structure.     

ViTO: tool for refinement of protein sequence-structure alignments

SUMMARY: ViTO is a graphical application, including an editor, of multiple sequence alignment and a three-dimensional (3D) structure viewer. It is possible to manipulate alignments containing hundreds of sequences and to display a dozen structures. ViTO can handle so-called 'multiparts' alignments to allow the visualization of complex structures (multi-chain proteins and/or small molecules and DNA) and the editing of the corresponding alignment. The 3D viewer and the alignment editor are connected together allowing rapid refinement of sequence-structure alignment by taking advantage of the immediate visualization of resulting insertions/deletions and strict conservations in their structural context. More generally, it allows the mapping of informations about the sequence conservation extracted from the alignment onto the 3D structures in a dynamic way. ViTO is also connected to two comparative modelling programs, SCWRL and MODELLER. These features make ViTO a powerful tool to characterize protein families and to optimize the alignments for comparative modelling. AVAILABILITY: http://bioserv.cbs.cnrs.fr/VITO/DOC/. SUPPLEMENTARY INFORMATION: http://bioserv.cbs.cnrs.fr/VITO/DOC/index.html.     

Three-dimensional analysis of plant structure using high-resolution X-ray computed tomography

High-resolution X-ray computed tomography (HRCT) is a non-invasive approach to 3D visualization and quantification of biological structure. The data, based on differential X-ray attenuation, are analogous to those otherwise obtainable only by serial sectioning. Requiring no fixing, sectioning or staining, HRCT produces a 3D digital map of the specimen that allows measurements and visualizations, including arbitrarily oriented sections. In spite of its application throughout the natural sciences, HRCT has yet to be applied in extant plant structural research.     

Guidelines for visualizing and annotating rule-based models

Rule-based modeling provides a means to represent cell signaling systems in a way that captures site-specific details of molecular interactions. For rule-based models to be more widely understood and (re)used, conventions for model visualization and annotation are needed. We have developed the concepts of an extended contact map and a model guide for illustrating and annotating rule-based models. An extended contact map represents the scope of a model by providing an illustration of each molecule, molecular component, direct physical interaction, post-translational modification, and enzyme-substrate relationship considered in a model. A map can also illustrate allosteric effects, structural relationships among molecular components, and compartmental locations of molecules. A model guide associates elements of a contact map with annotation and elements of an underlying model, which may be fully or partially specified. A guide can also serve to document the biological knowledge upon which a model is based. We provide examples of a map and guide for a published rule-based model that characterizes early events in IgE receptor (FcεRI) signaling. We also provide examples of how to visualize a variety of processes that are common in cell signaling systems but not considered in the example model, such as ubiquitination. An extended contact map and an associated guide can document knowledge of a cell signaling system in a form that is visual as well as executable. As a tool for model annotation, a map and guide can communicate the content of a model clearly and with precision, even for large models.     

Prediction of helix-helix contacts and interacting helices in polytopic membrane proteins using neural networks

Despite rapidly increasing numbers of available 3D structures, membrane proteins still account for less than 1% of all structures in the Protein Data Bank. Recent high-resolution structures indicate a clearly broader structural diversity of membrane proteins than initially anticipated, motivating the development of reliable structure prediction methods specifically tailored for this class of molecules. One important prediction target capturing all major aspects of a protein's 3D structure is its contact map. Our analysis shows that computational methods trained to predict residue contacts in globular proteins perform poorly when applied to membrane proteins. We have recently published a method to identify interacting alpha-helices in membrane proteins based on the analysis of coevolving residues in predicted transmembrane regions. Here, we present a substantially improved algorithm for the same problem, which uses a newly developed neural network approach to predict helix-helix contacts. In addition to the input features commonly used for contact prediction of soluble proteins, such as windowed residue profiles and residue distance in the sequence, our network also incorporates features that apply to membrane proteins only, such as residue position within the transmembrane segment and its orientation toward the lipophilic environment. The obtained neural network can predict contacts between residues in transmembrane segments with nearly 26% accuracy. It is therefore the first published contact predictor developed specifically for membrane proteins performing with equal accuracy to state-of-the-art contact predictors available for soluble proteins. The predicted helix-helix contacts were employed in a second step to identify interacting helices. For our dataset consisting of 62 membrane proteins of solved structure, we gained an accuracy of 78.1%. Because the reliable prediction of helix interaction patterns is an important step in the classification and prediction of membrane protein folds, our method will be a helpful tool in compiling a structural census of membrane proteins.     

KING (Kinemage,Next Generation): A versatile interactive molecular and scientific visualization program

Proper visualization of scientific data is important for understanding spatial relationships. Particularly in the field of structural biology, where researchers seek to gain an understanding of the structure and function of biological macromolecules, it is important to have access to visualization programs which are fast, flexible, and customizable. We present KiNG, a Java program for visualizing scientific data, with a focus on macromolecular visualization. KiNG uses the kinemage graphics format, which is tuned for macromolecular structures, but is also ideal for many other kinds of spatially embedded information. KiNG is written in cross‐platform, open‐source Java code, and can be extended by end users through simple or elaborate “plug‐in” modules. Here, we present three such applications of KiNG to problems in structural biology (protein backbone rebuilding), bioinformatics of high‐dimensional data (e.g., protein sidechain chi angles), and classroom education (molecular illustration). KiNG is a mature platform for rapidly creating and capitalizing on scientific visualizations. As a research tool, it is invaluable as a test bed for new methods of visualizing scientific data and information. It is also a powerful presentation tool, whether for structure browsing, teaching, direct 3D display on the web, or as a method for creating pictures and videos for publications. KiNG is freely available for download at http://kinemage.biochem.duke.edu .     

1D2DSimScore: A novel method for comparing contacts in biomacromolecules and their complexes

The biologically relevant structures of proteins and nucleic acids and their complexes are dynamic. They include a combination of regions ranging from rigid structural segments to structural switches to regions that are almost always disordered, which interact with each other in various ways. Comparing conformational changes and variation in contacts between different conformational states is essential to understand the biological functions of proteins, nucleic acids, and their complexes. Here, we describe a new computational tool, 1D2DSimScore, for comparing contacts and contact interfaces in all kinds of macromolecules and macromolecular complexes, including proteins, nucleic acids, and other molecules. 1D2DSimScore can be used to compare structural features of macromolecular models between alternative structures obtained in a particular experiment or to score various predictions against a defined “ideal” reference structure. Comparisons at the level of contacts are particularly useful for flexible molecules, for which comparisons in 3D that require rigid-body superpositions are difficult, and in biological systems where the formation of specific inter-residue contacts is more relevant for the biological function than the maintenance of a specific global 3D structure. Similarity/dissimilarity scores calculated by 1D2DSimScore can be used to complement scores describing 3D structural similarity measures calculated by the existing tools.     

Low-resolution density maps from atomic models: how stepping "back" can be a step "forward"

Atomic-resolution structures have had a tremendous impact on modern biological science. Much useful information also has been gleaned by merging and correlating atomic-resolution structural details with lower-resolution (15-40 A), three-dimensional (3D) reconstructions computed from images recorded with cryo-transmission electron microscopy (cryoTEM) procedures. One way to merge these structures involves reducing the resolution of an atomic model to a level comparable to a cryoTEM reconstruction. A low-resolution density map can be derived from an atomic-resolution structure by retrieving a set of atomic coordinates editing the coordinate file, computing structure factors from the model coordinates, and computing the inverse Fourier transform of the structure factors. This method is a useful tool for structural studies primarily in combination with 3D cryoTEM reconstructions. It has been used to assess the quality of 3D reconstructions, to determine corrections for the phase-contrast transfer function of the transmission electron microscope, to calibrate the dimensions and handedness of 3D reconstructions, to produce difference maps, to model features in macromolecules or macromolecular complexes, and to generate models to initiate model-based determination of particle orientation and origin parameters for 3D reconstruction.     

MolSurfer: A macromolecular interface navigator

We describe the current status of the Java molecular graphics tool, MolSurfer. MolSurfer has been designed to assist the analysis of the structures and physico-chemical properties of macromolecular interfaces. MolSurfer provides a coupled display of two-dimensional (2D) maps of the interfaces generated with the ADS software and a three-dimensional (3D) view of the macromolecular structure in the Java PDB viewer, WebMol. The interfaces are analytically defined and properties such as electrostatic potential or hydrophobicity are projected on to them. MolSurfer has been applied previously to analyze a set of 39 protein-protein complexes, with structures available from the Protein Data Bank (PDB). A new application, described here, is the visualization of 75 interfaces in structures of protein-DNA and protein-RNA complexes. Another new feature is that the MolSurfer web server is now able to compute and map Poisson-Boltzmann electrostatic potentials of macromolecules onto interfaces. The MolSurfer web server is available at http://projects.villa-bosch.de/mcm/software/molsurfer.     

XdomView: protein domain and exon position visualization

SUMMARY: The relationship between intron distribution in the eukaryotic gene and protein structural elements is essential for understanding the origin and evolution of genes. XdomView is a web-based viewer mapping protein structural domains and intron positions in eukaryotic homologues to its tertiary structure. The association of sequence signals to 3D structure in XdomView provides a valuable visualization environment for eukaryotic gene organization, gene evolution, protein folding and protein structure classification. AVAILABILITY: Freely available from http://surya.bic.nus.edu.sg/xdom.     

A parameterized algorithm for protein structure alignment.

This paper proposes a parameterized polynomial time approximation scheme (PTAS) for aligning two protein structures, in the case where one protein structure is represented by a contact map graph and the other by a contact map graph or a distance matrix. If the sequential order of alignment is not required, the time complexity is polynomial in the protein size and exponential with respect to two parameters D(u)/D(l) and D(c)/D(l), which usually can be treated as constants. In particular, D(u) is the distance threshold determining if two residues are in contact or not, D(c) is the maximally allowed distance between two matched residues after two proteins are superimposed, and D(l) is the minimum inter-residue distance in a typical protein. This result clearly demonstrates that the computational hardness of the contact map based protein structure alignment problem is related not to protein size but to several parameters modeling the problem. The result is achieved by decomposing the protein structure using tree decomposition and discretizing the rigid-body transformation space. Preliminary experimental results indicate that on a Linux PC, it takes from ten minutes to one hour to align two proteins with approximately 100 residues.     

Low-Resolution Density Maps from Atomic Models: How Stepping “Back” Can Be a Step “Forward”

Atomic-resolution structures have had a tremendous impact on modern biological science. Much useful information also has been gleaned by merging and correlating atomic-resolution structural details with lower-resolution (15–40 Å), three-dimensional (3D) reconstructions computed from images recorded with cryo-transmission electron microscopy (cryoTEM) procedures. One way to merge these structures involves reducing the resolution of an atomic model to a level comparable to a cryoTEM reconstruction. A low-resolution density map can be derived from an atomic-resolution structure by retrieving a set of atomic coordinates editing the coordinate file, computing structure factors from the model coordinates, and computing the inverse Fourier transform of the structure factors. This method is a useful tool for structural studies primarily in combination with 3D cryoTEM reconstructions. It has been used to assess the quality of 3D reconstructions, to determine corrections for the phase-contrast transfer function of the transmission electron microscope, to calibrate the dimensions and handedness of 3D reconstructions, to produce difference maps, to model features in macromolecules or macromolecular complexes, and to generate models to initiate model-based determination of particle orientation and origin parameters for 3D reconstruction.     

Recoverable one-dimensional encoding of three-dimensional protein structures

One-dimensional (1D) structures of proteins such as secondary structure and contact number provide intuitive pictures to understand how the native three-dimensional (3D) structure of a protein is encoded in the amino acid sequence. However, it is still not clear whether a given set of 1D structures contains sufficient information for recovering the underlying 3D structure. Here we show that the 3D structure of a protein can be recovered from a set of three types of 1D structures, namely, secondary structure, contact number and residue-wise contact order which is introduced here for the first time. Using simulated annealing molecular dynamics simulations, the structures satisfying the given native 1D structural restraints were sought for 16 proteins of various structural classes and of sizes ranging from 56 to 146 residues. By selecting the structures best satisfying the restraints, all the proteins showed a coordinate RMS deviation of <4 A from the native structure, and, for most of them, the deviation was even <2 A. The present result opens a new possibility to protein structure prediction and our understanding of the sequence-structure relationship.     

Analysis of 3D structural differences in the IgG-binding domains based on the interresidue average-distance statistics

It is well-known that the IgG-binding domain from staphylococcal protein A folds into a 3α helix bundle structure, while the IgG-binding domain of streptococcal protein G forms an (α + β) structure. Recently, He et al. (Biochemistry 44:14055–14061, 2005) made mutants of these proteins from the wild types of protein A and protein G strains. These mutants are referred to as protein A219 and protein G311, and it was showed that these two mutants have different 3D structures, i.e., the 3α helix bundle structure and the (α + β) structure, respectively, despite the high sequence identity (59%). The purpose of our study was to clarify how such 3D structural differences are coded in the sequences with high homology. To address this problem, we introduce a predicted contact map constructed based on the interresidue average-distance statistics for prediction of folding properties of a protein. We refer to this map as an average distance map (ADM). Furthermore, the statistics of interresidue distances can be converted to an effective interresidue potential. We calculated the contact frequency of each residue of a protein in random conformations with this effective interresidue potential, and then we obtained values similar to ϕ values. We refer to this contact frequency of each residue as a p(μ) value. The comparison of the p(μ) values to the ϕ values for a protein suggests that p(μ) values reveal the information on the folding initiation site. Using these techniques, we try to extract the information on the difference in the 3D structures of protein A219 and protein G311 coded in their amino acid sequences in the present work. The results show that the ADM analyses and the p(μ) value analyses predict the information of folding initiation sites, which can be used to detect the 3D difference in both proteins.     

Towards optimal views of proteins

MOTIVATION: Graphical representations of proteins in online databases generally give default views orthogonal to the PDB file coordinate system. These views are often uninformative in terms of protein structure and/or function. Here we discuss the development of a simple automatic algorithm to provide a 'good' view of a protein domain with respect to its structural features. RESULTS: We used dimension reduction with the preservation of topology (using Kohonen's self organising map) to map 3D carbon alpha coordinates into 2D. The original protein structure was then rotated to the view which corresponded most closely to the 2D mapping. This procedure, which we call OVOP, was evaluated in a public blind trial on the web against random views and a 'flattest' view. The OVOP views were consistently rated 'better' than the other views by our volunteers. AVAILABILITY: The source code is available from the OVOP homepage: http://www.sbc.su.se/~oscar/ovop.     

TMCompare: transmembrane region sequence and structure.

TMCompare is an alignment and visualization tool for comparison of sequence information for membrane proteins contained in SWISS-PROT entries, with structural information contained in PDB files. The program can be used for: detection of breaks in alpha helical structure of transmembrane regions; examination of differences in coverage between PDB and SWISS-PROT files; examination of annotation differences between PDB files and associated SWISS-PROT files; examination and comparison of assigned PDB alpha helix regions and assigned SWISS-PROT transmembrane regions in linear sequence (one letter code) format; examination of these differences in 3D using the CHIME plugin, allowing; analysis of the alpha and non-alpha content of transmembrane regions. AVAILABILITY: TMCompare is available for use through selection of a query protein via the internet (http://www.membraneproteins.org/TMCompare) CONTACT: tmcompare@membraneproteins.org