WEBnm@: a web application for normal mode analyses of proteins

Background  

Normal mode analysis (NMA) has become the method of choice to investigate the slowest motions in macromolecular systems. NMA is especially useful for large biomolecular assemblies, such as transmembrane channels or virus capsids. NMA relies on the hypothesis that the vibrational normal modes having the lowest frequencies (also named soft modes) describe the largest movements in a protein and are the ones that are functionally relevant.     

Comparison of normal mode analyses on a small globular protein in dihedral angle space and Cartesian coordinate space

Normal mode analyses on the protein, bovine pancreatic trypsin inhibitor, in dihedral angle space and Cartesian coordinate space are compared. In Cartesian coordinate space it is found that modes of frequencies lower than 30 cm(-1) contribute 80% of the total mean-square fluctuation and are represented almost completely by motions in the dihedral angles. Bond angle and length fluctuations dominate in modes above 200 cm(-1), but contribute less than 2% to the total mean-square fluctuation. In the low-frequency modes a good correspondence between patterns of atomic displacements was found, but on average the root-mean-square fluctuations of the Cartesian coordinate modes are 13% greater than their dihedral angle counterparts. The main effect of fluctuations in the bond angles and lengths, therefore, is to allow the dihedral angles to become more flexible. As the important subspaces determined from the two methods overlap considerably, dihedral angle space analysis can be applied to proteins too large for Cartesian coordinate space analysis.     

Putative model for heat shock protein 70 complexation with receptor of advanced glycation end products through fluorescence proximity assays and normal mode analyses

Extracellular heat shock protein 70 (HSP70) is recognized by receptors on the plasma membrane, such as Toll-like receptor 4 (TLR4), TLR2, CD14, and CD40. This leads to activation of nuclear factor-kappa B (NF-κB), release of pro-inflammatory cytokines, enhancement of the phagocytic activity of innate immune cells, and stimulation of antigen-specific responses. However, the specific characteristics of HSP70 binding are still unknown, and all HSP70 receptors have not yet been described. Putative models for HSP70 complexation to the receptor for advanced glycation endproducts (RAGEs), considering both ADP- and ATP-bound states of HSP70, were obtained through molecular docking and interaction energy calculations. This interaction was detected and visualized by a proximity fluorescence-based assay in A549 cells and further analyzed by normal mode analyses of the docking complexes. The interacting energy of the complexes showed that the most favored docking situation occurs between HSP70 ATP-bound and RAGE in its monomeric state. The fluorescence proximity assay presented a higher number of detected spots in the HSP70 ATP treatment, corroborating with the computational result. Normal-mode analyses showed no conformational deformability in the interacting interface of the complexes. Results were compared with previous findings in which oxidized HSP70 was shown to be responsible for the differential modulation of macrophage activation, which could result from a signaling pathway triggered by RAGE binding. Our data provide important insights into the characteristics of HSP70 binding and receptor interactions, as well as putative models with conserved residues on the interface area, which could be useful for future site-directed mutagenesis studies.     

Thorough validation of protein normal mode analysis: a comparative study with essential dynamics

The deformation patterns of a large set of representative proteins determined by essential dynamics extracted from atomistic simulations and coarse-grained normal mode analysis are compared. Our analysis shows that the deformational space obtained with both approaches is quite similar when taking into account a representative number of modes. The results provide not only a comprehensive validation of the use of a low-frequency modal spectrum to describe protein flexibility, but also a complete picture of normal mode limitations.     

DisProt: a database of protein disorder

The Database of Protein Disorder (DisProt) is a curated database that provides structure and function information about proteins that lack a fixed three-dimensional (3D) structure under putatively native conditions, either in their entirety or in part. Starting from the central premise that intrinsic disorder is an important structural class of protein and in order to meet the increasing interest thereof, DisProt is aimed at becoming a central repository of disorder-related information. For each disordered protein, the database includes the name of the protein, various aliases, accession codes, amino acid sequence, location of the disordered region(s), and methods used for structural (disorder) characterization. If applicable, most entries also list the biological function(s) of each disordered region, how each region of disorder is used for function, as well as provide links to PubMed abstracts and major protein databases. AVAILABILITY: www.disprot.org     

Comparative analyses of parasites with a comprehensive database of genome-scale metabolic models

Protozoan parasites cause diverse diseases with large global impacts. Research on the pathogenesis and biology of these organisms is limited by economic and experimental constraints. Accordingly, studies of one parasite are frequently extrapolated to infer knowledge about another parasite, across and within genera. Model in vitro or in vivo systems are frequently used to enhance experimental manipulability, but these systems generally use species related to, yet distinct from, the clinically relevant causal pathogen. Characterization of functional differences among parasite species is confined to post hoc or single target studies, limiting the utility of this extrapolation approach. To address this challenge and to accelerate parasitology research broadly, we present a functional comparative analysis of 192 genomes, representing every high-quality, publicly-available protozoan parasite genome including Plasmodium, Toxoplasma, Cryptosporidium, Entamoeba, Trypanosoma, Leishmania, Giardia, and other species. We generated an automated metabolic network reconstruction pipeline optimized for eukaryotic organisms. These metabolic network reconstructions serve as biochemical knowledgebases for each parasite, enabling qualitative and quantitative comparisons of metabolic behavior across parasites. We identified putative differences in gene essentiality and pathway utilization to facilitate the comparison of experimental findings and discovered that phylogeny is not the sole predictor of metabolic similarity. This knowledgebase represents the largest collection of genome-scale metabolic models for both pathogens and eukaryotes; with this resource, we can predict species-specific functions, contextualize experimental results, and optimize selection of experimental systems for fastidious species.     

PFDB: a generic protein family database integrating the CATH domain structure database with sequence based protein family resources

MOTIVATION: The PFDB (Protein Family Database) is a new database designed to integrate protein family-related data with relevant functional and genomic data. It currently manages biological data for three projects-the CATH protein domain database (Orengo et al., 1997; Pearl et al., 2001), the VIDA virus domains database (Albà et al., 2001) and the Gene3D database (Buchan et al., 2001). The PFDB has been designed to accommodate protein families identified by a variety of sequence based or structure based protocols and provides a generic resource for biological research by enabling mapping between different protein families and diverse biochemical and genetic data, including complete genomes. RESULTS: A characteristic feature of the PFDB is that it has a number of meta-level entities (for example aggregation, collection and inclusion) represented as base tables in the final design. The explicit representation of relationships at the meta-level has a number of advantages, including flexibility-both in terms of the range of queries that can be formulated and the ability to integrate new biological entities within the existing design. A potential drawback with this approach-poor performance caused by the number of joins across meta-level tables-is avoided by implementing the PFDB with materialized views using the mature relational database technology of Oracle 8i. The resultant database is both fast and flexible. This paper presents the principles on which the database has been designed and implemented, and describes the current status of the database and query facilities supported.     

DBAli: a database of protein structure alignments

SUMMARY: The DBAli database includes approximately 35000 alignments of pairs of protein structures from SCOP (Lo Conte et al., Nucleic Acids Res., 28, 257-259, 2000) and CE (Shindyalov and Bourne, Protein Eng., 11, 739-747, 1998). DBAli is linked to several resources, including Compare3D (Shindyalov and Bourne, http://www.sdsc.edu/pb/software.htm, 1999) and ModView (Ilyin and Sali, http://guitar.rockefeller.edu/ModView/, 2001) for visualizing sequence alignments and structure superpositions. A flexible search of DBAli by protein sequence and structure properties allows construction of subsets of alignments suitable for a number of applications, such as benchmarking of sequence-sequence and sequence-structure alignment methods under a variety of conditions. AVAILABILITY: http://guitar.rockefeller.edu/DBAli/     

Effects of surface water on protein dynamics studied by a novel coarse-grained normal mode approach

Normal mode analysis (NMA) has received much attention as a direct approach to extract the collective motions of macromolecules. However, the stringent requirement of computational resources by classical all-atom NMA limits the size of the macromolecules to which the method is normally applied. We implemented a novel coarse-grained normal mode approach based on partitioning the all-atom Hessian matrix into relevant and nonrelevant parts. It is interesting to note that, using classical all-atom NMA results as a reference, we found that this method generates more accurate results than do other coarse-grained approaches, including elastic network model and block normal mode approaches. Moreover, this new method is effective in incorporating the energetic contributions from the nonrelevant atoms, including surface water molecules, into the coarse-grained protein motions. The importance of such improvements is demonstrated by the effect of surface water to shift vibrational modes to higher frequencies and by an increase in overlap of the coarse-grained eigenvector space (the motion directions) with that obtained from molecular dynamics simulations of solvated protein in a water box. These results not only confirm the quality of our method but also point out the importance of incorporating surface structural water in studying protein dynamics.     

ChemDB: a public database of small molecules and related chemoinformatics resources

MOTIVATION: The development of chemoinformatics has been hampered by the lack of large, publicly available, comprehensive repositories of molecules, in particular of small molecules. Small molecules play a fundamental role in organic chemistry and biology. They can be used as combinatorial building blocks for chemical synthesis, as molecular probes in chemical genomics and systems biology, and for the screening and discovery of new drugs and other useful compounds. RESULTS: We describe ChemDB, a public database of small molecules available on the Web. ChemDB is built using the digital catalogs of over a hundred vendors and other public sources and is annotated with information derived from these sources as well as from computational methods, such as predicted solubility and three-dimensional structure. It supports multiple molecular formats and is periodically updated, automatically whenever possible. The current version of the database contains approximately 4.1 million commercially available compounds and 8.2 million counting isomers. The database includes a user-friendly graphical interface, chemical reactions capabilities, as well as unique search capabilities. AVAILABILITY: Database and datasets are available on http://cdb.ics.uci.edu.     

SPiD: a subtilis protein interaction database.

MOTIVATION: Protein-protein interactions are a potential source of valuable clues in determining the functional role of as yet uncharacterized gene products in metabolic pathways. Graph-like structures emerging from the accumulation of interaction data make it difficult to maintain a consistent and global overview by hand. Bioinformatics tools are needed to perform this graph visualization while maintaining a link to the experimental data. RESULTS: "SPiD" is an online database for exploring networks of interacting proteins in Bacillus subtilis characterized by the two-hybrid system. Graphical displays of interaction networks are created dynamically as users interactively navigate through these networks. Third party applications can interface the database through a Common Object Request Broker Architecture (CORBA) tier. AVAILABILITY: SPiD is available through its web site at http://www-mig.versailles.inra.fr/bdsi/SPiD, and through an Interoperable Object Reference (IOR) and its associated Interface Definition Language (IDL). CONTACT: hoebeke@versailles.inra.fr     

MannDB – A microbial database of automated protein sequence analyses and evidence integration for protein characterization

Background  

MannDB was created to meet a need for rapid, comprehensive automated protein sequence analyses to support selection of proteins suitable as targets for driving the development of reagents for pathogen or protein toxin detection. Because a large number of open-source tools were needed, it was necessary to produce a software system to scale the computations for whole-proteome analysis. Thus, we built a fully automated system for executing software tools and for storage, integration, and display of automated protein sequence analysis and annotation data.     

Large‐scale comparison of protein essential dynamics from molecular dynamics simulations and coarse‐grained normal mode analyses

A large‐scale comparison of essential dynamics (ED) modes from molecular dynamic simulations and normal modes from coarse‐grained normal mode methods (CGNM) was performed on a dataset of 335 proteins. As CGNM methods, the elastic network model (ENM) and the rigid cluster normal mode analysis (RCNMA) were used. Low‐frequency normal modes from ENM correlate very well with ED modes in terms of directions of motions and relative amplitudes of motions. Notably, a similar performance was found if normal modes from RCNMA were used, despite a higher level of coarse graining. On average, the space spanned by the first quarter of ENM modes describes 84% of the space spanned by the five ED modes. Furthermore, no prominent differences for ED and CGNM modes among different protein structure classes (CATH classification) were found. This demonstrates the general potential of CGNM approaches for describing intrinsic motions of proteins with little computational cost. For selected cases, CGNM modes were found to be more robust among proteins that have the same topology or are of the same homologous superfamily than ED modes. In view of recent evidence regarding evolutionary conservation of vibrational dynamics, this suggests that ED modes, in some cases, might not be representative of the underlying dynamics that are characteristic of a whole family, probably due to insufficient sampling of some of the family members by MD. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

3Dee: a database of protein structural domains

The 3Dee database is a repository of protein structural domains. It stores alternative domain definitions for the same protein, organises domains into sequence and structural hierarchies, contains non-redundant set(s) of sequences and structures, multiple structure alignments for families of domains, and allows previous versions of the database to be regenerated. AVAILABILITY: 3Dee is accessible on the World Wide Web at the URL http://barton.ebi.ac.uk/servers/3Dee.html.     

PIR-ALN: a database of protein sequence alignments.

MOTIVATION: The Protein Information Resource (PIR) maintains a database of annotated and curated alignments in order to visually represent interrelationships among sequences in the PIR-International Protein Sequence Database, to spread and standardize protein names, features and keywords among members of a family or superfamily, and to aid us in classifying sequences, in identifying conserved regions, and in defining new homology domains. RESULTS: Release 22.0, (December 1998), of the PIR-ALN database contains a total of 3806 alignments, including 1303 superfamily, 2131 family and 372 homology domain alignments. This is an appropriate dataset to develop and extract patterns, test profiles, train neural networks or build Hidden Markov Models (HMMs). These alignments can be used to standardize and spread annotation to newer members by homology, as well as to understand the modular architecture of multidomain proteins. PIR-ALN includes 529 alignments that can be used to develop patterns not represented in PROSITE, Blocks, PRINTS and Pfam databases. The ATLAS information retrieval system can be used to browse and query the PIR-ALN alignments. AVAILABILITY: PIR-ALN is currently being distributed as a single ASCII text file along with the title, member, species, superfamily and keyword indexes. The quarterly and weekly updates can be accessed via the WWW at pir.georgetown.edu. The quarterly updates can also be obtained by anonymous FTP from the PIR FTP site at NBRF.Georgetown.edu, directory [ANONYMOUS.PIR.ALIGNMENT].     

ModBase: a database of comparative protein structure models

ModBase is a database of evaluated and annotated comparative protein structure models. The database also includes fold assignments and alignments on which the models were based.     

Threading a database of protein cores

We present an analysis of 10 blind predictions prepared for a recent conference, “Critical Assessment of Techniques for Protein Structure Prediction.”¹ The sequences of these proteins are not detectably similar to those of any protein in the structure database then available, but we attempted, by a threading method, to recognize similarity to known domain folds. Four of the 10 proteins, as we subsequently learned, do indeed show significant similarity to then-known structures. For 2 of these proteins the predictions were accurate, in the sense that a similar structure was at or near the top of the list of threading scores, and the threading alignment agreed well with the corresponding structural alignment. For the best predicted model mean alignment error relative to the optimal structural alignment was 2.7 residues, arising entirely from small “register shifts” of strands or helices. In the analysis we attempt to identify factors responsible for these successes and failures. Since our threading method does not use gap penalties, we may readily distinguish between errors arising from our prior definition of the “cores” of known structures and errors arising from inherent limitations in the threading potential. It would appear from the results that successful substructure recognition depends most critically on accurate definition of the “fold” of a database protein. This definition must correctly delineate substructures that are, and are not, likely to be conserved during protein evolution. © 1995 Wiley-Liss, Inc.