MetaBase--the wiki-database of biological databases.

Biology is generating more data than ever. As a result, there is an ever increasing number of publicly available databases that analyse, integrate and summarize the available data, providing an invaluable resource for the biological community. As this trend continues, there is a pressing need to organize, catalogue and rate these resources, so that the information they contain can be most effectively exploited. MetaBase (MB) (http://MetaDatabase.Org) is a community-curated database containing more than 2000 commonly used biological databases. Each entry is structured using templates and can carry various user comments and annotations. Entries can be searched, listed, browsed or queried. The database was created using the same MediaWiki technology that powers Wikipedia, allowing users to contribute on many different levels. The initial release of MB was derived from the content of the 2007 Nucleic Acids Research (NAR) Database Issue. Since then, approximately 100 databases have been manually collected from the literature, and users have added information for over 240 databases. MB is synchronized annually with the static Molecular Biology Database Collection provided by NAR. To date, there have been 19 significant contributors to the project; each one is listed as an author here to highlight the community aspect of the project.

NetworkView: 3D display and analysis of protein·RNA interaction networks.

SUMMARY: NetworkView is an application for the display and analysis of protein·RNA interaction networks derived from structure and/or dynamics. These networks typically model individual protein residues and nucleic acid monomers as nodes and their pairwise contacts as edges with associated weights. NetworkView projects the network onto the underlying 3D molecular structure so that visualization and analysis of the network can be coupled to physical and biological properties. NetworkView is implemented as a plugin to the molecular visualization software VMD. AVAILABILITY AND IMPLEMENTATION: NetworkView is included with VMD, which is available at http://www.ks.uiuc.edu/Research/vmd/. Documentation, tutorials and supporting programs are available at http://www.scs.illinois.edu/schulten/software/. CONTACT: networkview@scs.illinois.edu

Dynamical networks in tRNA:protein complexes.

Community network analysis derived from molecular dynamics simulations is used to identify and compare the signaling pathways in a bacterial glutamyl-tRNA synthetase (GluRS):tRNA(Glu) and an archaeal leucyl-tRNA synthetase (LeuRS):tRNA(Leu) complex. Although the 2 class I synthetases have remarkably different interactions with their cognate tRNAs, the allosteric networks for charging tRNA with the correct amino acid display considerable similarities. A dynamic contact map defines the edges connecting nodes (amino acids and nucleotides) in the physical network whose overall topology is presented as a network of communities, local substructures that are highly intraconnected, but loosely interconnected. Whereas nodes within a single community can communicate through many alternate pathways, the communication between monomers in different communities has to take place through a smaller number of critical edges or interactions. Consistent with this analysis, there are a large number of suboptimal paths that can be used for communication between the identity elements on the tRNAs and the catalytic site in the aaRS:tRNA complexes. Residues and nucleotides in the majority of pathways for intercommunity signal transmission are evolutionarily conserved and are predicted to be important for allosteric signaling. The same monomers are also found in a majority of the suboptimal paths. Modifying these residues or nucleotides has a large effect on the communication pathways in the protein:RNA complex consistent with kinetic data.

Functional role of ribosomal signatures.

Although structure and sequence signatures in ribosomal RNA and proteins are defining characteristics of the three domains of life and instrumental in constructing the modern phylogeny, little is known about their functional roles in the ribosome. In this work, the largest coevolving RNA/protein signatures in the bacterial 30S ribosome are investigated both experimentally and computationally through all-atom molecular-dynamics simulations. The complex includes the N-terminal fragment of the ribosomal protein S4, which is a primary binding protein that initiates 30S small subunit assembly from the 5' domain, and helix 16 (h16), which is part of the five-way junction in 16S rRNA. Our results show that the S4 N-terminus signature is intrinsically disordered in solution, whereas h16 is relatively stable by itself. The dynamic disordered property of the protein is exploited to couple the folding and binding process to the five-way junction, and the results provide insight into the mechanism for the early and fast binding of S4 in the assembly of the ribosomal small subunit.

MultiSeq: unifying sequence and structure data for evolutionary analysis.

BACKGROUND: Since the publication of the first draft of the human genome in 2000, bioinformatic data have been accumulating at an overwhelming pace. Currently, more than 3 million sequences and 35 thousand structures of proteins and nucleic acids are available in public databases. Finding correlations in and between these data to answer critical research questions is extremely challenging. This problem needs to be approached from several directions: information science to organize and search the data; information visualization to assist in recognizing correlations; mathematics to formulate statistical inferences; and biology to analyze chemical and physical properties in terms of sequence and structure changes. RESULTS: Here we present MultiSeq, a unified bioinformatics analysis environment that allows one to organize, display, align and analyze both sequence and structure data for proteins and nucleic acids. While special emphasis is placed on analyzing the data within the framework of evolutionary biology, the environment is also flexible enough to accommodate other usage patterns. The evolutionary approach is supported by the use of predefined metadata, adherence to standard ontological mappings, and the ability for the user to adjust these classifications using an electronic notebook. MultiSeq contains a new algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of a homologous group of distantly related proteins. The method, based on the multidimensional QR factorization of multiple sequence and structure alignments, removes redundancy from the alignments and orders the protein sequences by increasing linear dependence, resulting in the identification of a minimal basis set of sequences that spans the evolutionary space of the homologous group of proteins. CONCLUSION: MultiSeq is a major extension of the Multiple Alignment tool that is provided as part of VMD, a structural visualization program for analyzing molecular dynamics simulations. Both are freely distributed by the NIH Resource for Macromolecular Modeling and Bioinformatics and MultiSeq is included with VMD starting with version 1.8.5. The MultiSeq website has details on how to download and use the software: http://www.scs.uiuc.edu/~schulten/multiseq/

Visualizing the dual space of biological molecules.

An important part of protein structure characterization is the determination of excluded space such as fissures in contact interfaces, pores, inaccessible cavities, and catalytic pockets. We introduce a general tessellation method for visualizing the dual space around, within, and between biological molecules. Using Delaunay triangulation, a three-dimensional graph is constructed to provide a displayable discretization of the continuous volume. This graph structure is also used to compare the dual space of a system in two different states. Tessellator, a cross-platform implementation of the algorithm, is used to analyze the cavities within myoglobin, the protein-RNA docking interface between aspartyl-tRNA synthetase and tRNA(Asp), and the ammonia channel in the hisH-hisF complex of imidazole glycerol phosphate synthase.

Exploring residue component contributions to dynamical network models of allostery.

Allosteric regulation in biological systems is of considerable interest given the vast number of proteins that exhibit such behavior. Network models obtained from molecular dynamics simulations have been shown to be powerful tools for the analysis of allostery. In this work, different coarse-grain residue representations (nodes) are used together with a dynamical network model to investigate models of allosteric regulation. This model assumes that allosteric signals are dependent on positional correlations of protein substituents, as determined through molecular dynamics simulations, and uses correlated motion to generate a signaling weight between two given nodes. We examine four types of network models using different node representations in Cartesian coordinates: the (i) residue alpha-carbons, (ii) sidechain center of mass, (iii) backbone center of mass, and the entire (iv) residue center of mass. All correlations are filtered by a dynamic contact map that defines the allowable interactions between nodes based on physical proximity. We apply the four models to imidazole glycerol phosphate synthase (IGPS), which provides a well-studied experimental framework in which allosteric communication is known to persist across disparate protein domains (e.g. a protein dimer interface). IGPS is modeled as a network of nodes and weighted edges. Optimal allosteric pathways are traced using the Floyd Warshall algorithm for weighted networks, and community analysis (a form of hierarchical clustering) is performed using the Girvan-Newman algorithm. Our results show that dynamical information encoded in the residue center of mass must be included in order to detect residues that are experimentally known to play a role in allosteric communication for IGPS. More broadly, this new method may be useful for predicting pathways of allosteric communication for any biomolecular system in atomic detail.

Assembly of the five-way junction in the ribosomal small subunit using hybrid MD-Go simulations.

Assembly of the bacterial ribosomal small subunit (SSU) begins with the folding of the five-way junction upon interaction with the primary binding protein S4. This complex contains the largest contiguous molecular signature, which is a conserved feature in all bacterial 16S rRNAs. In a previous study, we used all-atom molecular dynamics simulations to demonstrate that the co-evolving signature in the N-terminus of S4 is intrinsically disordered and capable of accelerating the binding process through a fly casting mechanism. In this paper, comparisons between the all-atom MD simulations and FRET experiments identify multiple metastable conformations of the naked five-way junction without the presence of S4. Furthermore, we capture the simultaneous folding and binding of the five-way junction and r-protein S4 by use of a structure-based Go potential implemented within the framework of the all-atom molecular dynamics CHARMM force field. Different folding pathways are observed for the refolding of the five-way junction upon partial binding of S4. Our simulations illustrate the complex nature of RNA folding in the presence of a protein binding partner and provide insight into the role of population shift and the induced fit mechanisms in the protein:RNA folding and binding process.

Experimental and computational determination of tRNA dynamics.

As the molecular representation of the genetic code, tRNA plays a central role in the translational machinery where it interacts with several proteins and other RNAs during the course of protein synthesis. These interactions exploit the dynamic flexibility of tRNA. In this minireview, we discuss the effects of modified bases, ions, and proteins on tRNA structure and dynamics and the challenges of observing its motions over the cycle of translation.

Exit strategies for charged tRNA from GluRS.

For several class I aminoacyl-tRNA synthetases (aaRSs), the rate-determining step in aminoacylation is the dissociation of charged tRNA from the enzyme. In this study, the following factors affecting the release of the charged tRNA from aaRSs are computationally explored: the protonation states of amino acids and substrates present in the active site, and the presence and the absence of AMP and elongation factor Tu. Through molecular modeling, internal pK(a) calculations, and molecular dynamics simulations, distinct, mechanistically relevant post-transfer states with charged tRNA bound to glutamyl-tRNA synthetase from Thermus thermophilus (Glu-tRNA(Glu)) are considered. The behavior of these nonequilibrium states is characterized as a function of time using dynamical network analysis, local energetics, and changes in free energies to estimate transitions that occur during the release of the tRNA. The hundreds of nanoseconds of simulation time reveal system characteristics that are consistent with recent experimental studies. Energetic and network results support the previously proposed mechanism in which the transfer of amino acid to tRNA is accompanied by the protonation of AMP to H-AMP. Subsequent migration of proton to water reduces the stability of the complex and loosens the interface both in the presence and in the absence of AMP. The subsequent undocking of AMP or tRNA then proceeds along thermodynamically competitive pathways. Release of the tRNA acceptor stem is further accelerated by the deprotonation of the alpha-ammonium group on the charging amino acid. The proposed general base is Glu41, a residue binding the alpha-ammonium group that is conserved in both structure and sequence across nearly all class I aaRSs. This universal handle is predicted through pK(a) calculations to be part of a proton relay system for destabilizing the bound charging amino acid following aminoacylation. Addition of elongation factor Tu to the aaRS.tRNA complex stimulates the dissociation of the tRNA core and the tRNA acceptor stem.

The role of L1 stalk-tRNA interaction in the ribosome elongation cycle.

The ribosomal L1 stalk is a mobile structure implicated in directing tRNA movement during translocation through the ribosome. This article investigates three aspects of L1 stalk-tRNA interaction. First, by combining data from cryo electron microscopy, X-ray crystallography, and molecular dynamics simulations through the molecular dynamics flexible fitting method, we obtained atomic models of different tRNAs occupying the hybrid P/E state interacting with the L1 stalk. These models confirm the assignment of fluorescence resonance energy transfer states from previous single-molecule investigations of L1 stalk dynamics. Second, the models reconcile how initiator tRNA(fMet) interacts less strongly with the L1 stalk compared to elongator tRNA(Phe), as seen in previous single-molecule experiments. Third, results from a simulation of the entire ribosome in which the L1 stalk is moved from a half-closed conformation to its open conformation are found to support the hypothesis that L1 stalk opening is involved in tRNA release from the ribosome.

Dynamics of Recognition between tRNA and elongation factor Tu.

Elongation factor Tu (EF-Tu) binds to all standard aminoacyl transfer RNAs (aa-tRNAs) and transports them to the ribosome while protecting the ester linkage between the tRNA and its cognate amino acid. We use molecular dynamics simulations to investigate the dynamics of the EF-Tu.guanosine 5'-triphosphate.aa-tRNA(Cys) complex and the roles played by Mg2+ ions and modified nucleosides on the free energy of protein.RNA binding. Individual modified nucleosides have pronounced effects on the structural dynamics of tRNA and the EF-Tu.Cys-tRNA(Cys) interface. Combined energetic and evolutionary analyses identify the coevolution of residues in EF-Tu and aa-tRNAs at the binding interface. Highly conserved EF-Tu residues are responsible for both attracting aa-tRNAs as well as providing nearby nonbonded repulsive energies that help fine-tune molecular attraction at the binding interface. In addition to the 3' CCA end, highly conserved tRNA nucleotides G1, G52, G53, and U54 contribute significantly to EF-Tu binding energies. Modification of U54 to thymine affects the structure of the tRNA common loop resulting in a change in binding interface contacts. In addition, other nucleotides, conserved within certain tRNA specificities, may be responsible for tuning aa-tRNA binding to EF-Tu. The trend in EF-Tu.Cys-tRNA(Cys) binding energies observed as the result of mutating the tRNA agrees with experimental observation. We also predict variations in binding free energies upon misacylation of tRNA(Cys) with d-cysteine or O-phosphoserine and upon changing the protonation state of l-cysteine. Principal components analysis in each case reveals changes in the communication network across the protein.tRNA interface and is the basis for the entropy calculations.

Multiple Alignment of protein structures and sequences for VMD.

Multiple Alignment is a new interface for performing and analyzing multiple protein structure alignments. It enables viewing levels of sequence and structure similarity on the aligned structures and performing a variety of evolutionary and bioinformatic tasks, including the construction of structure-based phylogenetic trees and minimal basis sets of structures that best represent the topology of the phylogenetic tree. It is implemented as a plugin for VMD (Visual Molecular Dynamics), which is distributed by the NIH Resource for Macromolecular Modeling and Bioinformatics at the University of Illinois.