On the efficiency of energy migration from the chlorosome to the main bacteriochlorophyll in green bacteria

It is shown that the results provided in a number of publications based on structural characteristics of chlorosomes of green bacteria are in explicit contradiction with their kinetic and energy characteristics. The data on chlorosome structure and composition give no explanation as to how the additional electronic excitations generated by light in its dominating pigment C750 feed the main photosystem. To reveal the contradictions, the structural and spectral data on the chlorosome are analyzed using the theory of inductive resonance developed by Förster.     

The structural changes in the ribosome during the elongation cycle

The plenty of data about structural changes in the ribosome during its functioning has been accumulated. The most interesting information on such changes was obtained by cryo-EM of various ribosomal complexes with the ligands and by combination of rRNA site-directed mutagenesis with the analysis of structural changes in ribosome by chemical modification technique (chemical probing). The most studied structural transformations of the ribosome interacting with tRNAs and elongation factors are considered in this review. The structural rearrangements are discussed in the context of interactions between the functional centers of the ribosome. We also describe the system of tertiary contacts between the rRNA helices and proteins which forms the universal structure in the ribosome. We pay attention that by means of such system the allosteric conformational signal can be transmitted between the functional centers. Besides the discussion of different biochemical data in the scope of structural data we also consider the hypothesis that the position of GTPase associated center (GAC) in the ribosome regulates the binding of elongation factors.     

Structure and functions of the prokaryotic elongation factor G

Structural and functional data on elongation factor G (EF-G) are reviewed with regard to nucleotide exchange, GTP hydrolysis, mechanism of action of fusidic acid, and functional roles of the EF-G structural domains in translocation. Biochemical data are correlated with structural dynamics of the EF-G molecule on interaction with various ligands. Data on EF-Tu are also considered, as EF-G and EF-Tu share certain structural and functional features.     

Structure and Functions of the Prokaryotic Elongation Factor G

Structural and functional data on elongation factor G (EF-G) are reviewed with regard to nucleotide exchange, GTP hydrolysis, mechanism of action of fusidic acid, and functional roles of the EF-G structural domains in translocation. Biochemical data are correlated with structural dynamics of the EF-G molecule on interaction with various ligands. Data on EF-Tu are also considered, as EF-G and EF-Tu share certain structural and functional features.     

Structural changes in the ribosome during the elongation cycle

Ample data on structural changes that arise in the ribosome during translation have been accumulated. The most interesting information on such changes has been obtained by cryoelectron microscopy of ribosome complexes with various ligands and by rRNA site-directed mutagenesis combined with a structural analysis of the ribosome by a chemical modification technique (chemical probing). The review considers the best-known structural changes that arise in the translating ribosome upon its interactions with tRNA and the elongation factors. The changes are discussed in the context of interactions between the functional centers of the ribosome. A universal system of rRNA helices and proteins is described in detail. The system integrates the functional centers of the ribosome and allows transduction of allosteric conformational signals. Biochemical data are considered in terms of the structures and interactions of ribosomal elements, and a hypothesis is advanced that the position of the GTPase-associated center in the ribosome regulates the binding of the elongation factors.     

Combining NMR and small angle X-ray and neutron scattering in the structural analysis of a ternary protein-RNA complex

Many processes in the regulation of gene expression and signaling involve the formation of protein complexes involving multi-domain proteins. Individual domains that mediate protein-protein and protein-nucleic acid interactions are typically connected by flexible linkers, which contribute to conformational dynamics and enable the formation of complexes with distinct binding partners. Solution techniques are therefore required for structural analysis and to characterize potential conformational dynamics. Nuclear magnetic resonance spectroscopy (NMR) provides such information but often only sparse data are obtained with increasing molecular weight of the complexes. It is therefore beneficial to combine NMR data with additional structural restraints from complementary solution techniques. Small angle X-ray/neutron scattering (SAXS/SANS) data can be efficiently combined with NMR-derived information, either for validation or by providing additional restraints for structural analysis. Here, we show that the combination of SAXS and SANS data can help to refine structural models obtained from data-driven docking using HADDOCK based on sparse NMR data. The approach is demonstrated with the ternary protein-protein-RNA complex involving two RNA recognition motif (RRM) domains of Sex-lethal, the N-terminal cold shock domain of Upstream-to-N-Ras, and msl-2 mRNA. Based on chemical shift perturbations we have mapped protein-protein and protein-RNA interfaces and complemented this NMR-derived information with SAXS data, as well as SANS measurements on subunit-selectively deuterated samples of the ternary complex. Our results show that, while the use of SAXS data is beneficial, the additional combination with contrast variation in SANS data resolves remaining ambiguities and improves the docking based on chemical shift perturbations of the ternary protein-RNA complex.     

Computational methods for defining the allowed conformational space of 16S rRNA based on chemical footprinting data.

Structural models for 16S ribosomal RNA have been proposed based on combinations of crosslinking, chemical protection, shape, and phylogenetic evidence. These models have been based for the most part on independent data sets and different sets of modeling assumptions. In order to evaluate such models meaningfully, methods are required to explicitly model the spatial certainty with which individual structural components are positioned by specific data sets. In this report, we use a constraint satisfaction algorithm to explicitly assess the location of the secondary structural elements of the 16S RNA, as well as the certainty with which these elements can be positioned. The algorithm initially assumes that these helical elements can occupy any position and orientation and then systematically eliminates those positions and orientations that do not satisfy formally parameterized interpretations of structural constraints. Using a conservative interpretation of the hydroxyl radical footprinting data, the positions of the ribosomal proteins as defined by neutron diffraction studies, and the secondary structure of 16S rRNA, the location of the RNA secondary structural elements can be defined with an average precision of 25 A (ranging from 12.8 to 56.3 A). The uncertainty in individual helix positions is both heterogeneous and dependent upon the number of constraints imposed on the helix. The topology of the resulting model is consistent with previous models based on independent approaches. The result of our computation is a conservative upper bound on the possible positions of the RNA secondary structural elements allowed by this data set, and provides a suitable starting point for refinement with other sources of data or different sets of modeling assumptions.     

Structural Similarities between Brain and Linguistic Data Provide Evidence of Semantic Relations in the Brain

This paper presents a new method of analysis by which structural similarities between brain data and linguistic data can be assessed at the semantic level. It shows how to measure the strength of these structural similarities and so determine the relatively better fit of the brain data with one semantic model over another. The first model is derived from WordNet, a lexical database of English compiled by language experts. The second is given by the corpus-based statistical technique of latent semantic analysis (LSA), which detects relations between words that are latent or hidden in text. The brain data are drawn from experiments in which statements about the geography of Europe were presented auditorily to participants who were asked to determine their truth or falsity while electroencephalographic (EEG) recordings were made. The theoretical framework for the analysis of the brain and semantic data derives from axiomatizations of theories such as the theory of differences in utility preference. Using brain-data samples from individual trials time-locked to the presentation of each word, ordinal relations of similarity differences are computed for the brain data and for the linguistic data. In each case those relations that are invariant with respect to the brain and linguistic data, and are correlated with sufficient statistical strength, amount to structural similarities between the brain and linguistic data. Results show that many more statistically significant structural similarities can be found between the brain data and the WordNet-derived data than the LSA-derived data. The work reported here is placed within the context of other recent studies of semantics and the brain. The main contribution of this paper is the new method it presents for the study of semantics and the brain and the focus it permits on networks of relations detected in brain data and represented by a semantic model.     

Structural and functional topography of the human ribosome

This review covers data on the structural organization of functional sites in the human ribosome, namely, the messenger RNA binding center, the binding site of the hepatitis C virus RNA internal ribosome entry site, and the peptidyl transferase center. The data summarized here have been obtained primarily by means of a site-directed cross-linking approach with application of the analogs of the respective ribosomal ligands bearing cross-linkers at the designed positions. These data are discussed taking into consideration available structural data on ribosomes from various kingdoms obtained with the use of cryo-electron microscopy, X-ray crystallography, and other approaches.     

Assessment of the probabilities for evolutionary structural changes in protein folds

MOTIVATION: The evolution of protein sequences can be described by a stepwise process, where each step involves changes of a few amino acids. In a similar manner, the evolution of protein folds can be at least partially described by an analogous process, where each step involves comparatively simple changes affecting few secondary structure elements. A number of such evolution steps, justified by biologically confirmed examples, have previously been proposed by other researchers. However, unlike the situation with sequences, as far as we know there have been no attempts to estimate the comparative probabilities for different kinds of such structural changes. RESULTS: We have tried to assess the comparative probabilities for a number of known structural changes, and to relate the probabilities of such changes with the distance between protein sequences. We have formalized these structural changes using a topological representation of structures (TOPS), and have developed an algorithm for measuring structural distances that involve few evolutionary steps. The probabilities of structural changes then were estimated on the basis of all-against-all comparisons of the sequence and structure of protein domains from the CATH-95 representative set. The results obtained are reasonably consistent for a number of different data subsets and permit the identification of several 'most popular' types of evolutionary changes in protein structure. The results also suggest that alterations in protein structure are more likely to occur when the sequence similarity is >10% (the average similarity being approximately 6% for the data sets employed in this study), and that the distribution of probabilities of structural changes is fairly uniform within the interval of 15-50% sequence similarity. AVAILABILITY: The algorithms have been implemented on the Windows operating system in C++ and using the Borland Visual Component Library. The source code is available on request from the first author. The data sets used for this study (representative sets of protein domains, matrices of sequence similarities and structural distances) are available on http://bioinf.mii.lu.lv/epsrc_project/struct_ev.html.     

Review: nucleotide-dependent conformational changes of the chaperonin containing TCP-1

Current biochemical and structural studies on the conformational changes induced by the nature of nucleotide bound to the chaperonin containing testis complex polypeptide 1 (CCT) are examined to see how consistent the data are. This exercise suggests that the biochemical and structural data are in good agreement. CCT clearly appears as a folding nano-machine fueled by ATP. A careful comparison of the biochemical and structural data, however, highlights a number of points that remain to be carefully documented in order to better understand the nature of the conformational changes in CCT that yield folded target proteins. Special effort should be made to clearly answer the points listed at the end of this review in order to obtain the dynamic sequence of events yielding folded proteins in the eukaryotic cytoplasm similar to what has been obtained for prokaryotes.     

An Expert System Approach to the Assessment of Hepatotoxic Potential

Hepatotoxicity is a major cause of pharmaceutical drug attrition and is also a concern within other chemical industries. In silico approaches to the prediction of hepatotoxicity are an important tool in the early identification of adverse effects in the liver associated with exposure to a chemical. Here, we describe work in progress to develop an expert system approach to the prediction of hepatotoxicity, focussing particularly on the identification of structural alerts associated with its occurrence. The development of 74 such structural alerts based on public‐domain literature and proprietary data sets is described. Evaluation results indicate that, whilst these structural alerts are effective in identifying the hepatotoxicity of many chemicals, further research is needed to develop additional structural alerts to account for the hepatotoxicity of a number of chemicals which is not currently predicted. Preliminary results also suggest that the specificity of the structural alerts may be improved by the combined use of applicability domains based on physicochemical properties such as log P and molecular weight. In the longer term, the performance of predictive models is likely to benefit from the further integration of diverse data and prediction model types.     

Incorporating residual dipolar couplings into the NMR solution structure determination of nucleic acids

NMR solution structures of nucleic acids are generally less well defined than similar-sized proteins. Most NMR structures of nucleic acids are defined only by short-range interactions, such as intrabase-pair or sequential nuclear Overhauser effects (NOEs), and J-coupling constants, and there are no long-range structural data on the tertiary structure. Residual dipolar couplings represent an extremely valuable source of distance and angle information for macromolecules but they average to zero in isotropic solutions. With the recent advent of general methods for partial alignment of macromolecules in solution, residual dipolar couplings are rapidly becoming indispensable constraints for solution NMR structural studies. These residual dipolar couplings give long-range global structural information and thus complement the strictly local structural data obtained from standard NOE and torsion angle constraints. Such global structural data are especially important in nucleic acids due to the more elongated, less-globular structure of many DNAs and RNAs. Here we review recent progress in application of residual dipolar couplings to structural studies of nucleic acids. We also present results showing how refinement procedures affect the final solution structures of nucleic acids.Copyright 2001 John Wiley & Sons, Inc.     

Using Integrative Modeling Platform to compute,validate, and archive a model of a protein complex structure

Biology is advanced by producing structural models of biological systems, such as protein complexes. Some systems are recalcitrant to traditional structure determination methods. In such cases, it may still be possible to produce useful models by integrative structure determination that depends on simultaneous use of multiple types of data. An ensemble of models that are sufficiently consistent with the data is produced by a structural sampling method guided by a data‐dependent scoring function. The variation in the ensemble of models quantified the uncertainty of the structure, generally resulting from the uncertainty in the input information and actual structural heterogeneity in the samples used to produce the data. Here, we describe how to generate, assess, and interpret ensembles of integrative structural models using our open source Integrative Modeling Platform program ( https://integrativemodeling.org ).     

Phytostructural characterization of several vegetation types in northern Portugal. II. The structural expressivity and the resistance of the vegetation

Abstract

The encouraging results obtained in a previous work induced the authors to pursue here the characterization of the structure of the vegetation in northern Portugal, using the phytostructural methodology proposed earlier by the authors. With this objective, eight different types of vegetal communities, representative of the apparent states of the successional process present in this area, and representing the diversity of plant community types in the same area, were selected. The phytostructural method was elaborated on the basis of three types of structural basic matrices regarding diversity, abundance and cover. The data obtained were collected in a contingency matrix, which was then treated by means of a statistical multivariate analysis. Three structural tendencies emerged from this analysis. With the aim of studying their stability, the results are discussed in terms of resistance and resilience, according to the Highest Expressive Amplitude (HEA) concept, and by considering the intra- and inter-community structural dynamics as structural parameters. The data obtained suggest structural situations with different degrees of non-equilibrium that reflect resistance to environmental factors. The resistance of the vegetation is correlated with the apparent functional connectivity detected for the communities analysed.     

Data-driven docking for the study of biomolecular complexes

With the amount of genetic information available, a lot of attention has focused on systems biology, in particular biomolecular interactions. Considering the huge number of such interactions, and their often weak and transient nature, conventional experimental methods such as X-ray crystallography and NMR spectroscopy are not sufficient to gain structural insight into these. A wealth of biochemical and/or biophysical data can, however, readily be obtained for biomolecular complexes. Combining these data with docking (the process of modeling the 3D structure of a complex from its known constituents) should provide valuable structural information and complement the classical structural methods. In this review we discuss and illustrate the various sources of data that can be used to map interactions and their combination with docking methods to generate structural models of the complexes. Finally a perspective on the future of this kind of approach is given.     

Piecewise linear approximation of protein structures using the principle of minimum message length

Simple and concise representations of protein-folding patterns provide powerful abstractions for visualizations, comparisons, classifications, searching and aligning structural data. Structures are often abstracted by replacing standard secondary structural features-that is, helices and strands of sheet-by vectors or linear segments. Relying solely on standard secondary structure may result in a significant loss of structural information. Further, traditional methods of simplification crucially depend on the consistency and accuracy of external methods to assign secondary structures to protein coordinate data. Although many methods exist automatically to identify secondary structure, the impreciseness of definitions, along with errors and inconsistencies in experimental structure data, drastically limit their applicability to generate reliable simplified representations, especially for structural comparison. This article introduces a mathematically rigorous algorithm to delineate protein structure using the elegant statistical and inductive inference framework of minimum message length (MML). Our method generates consistent and statistically robust piecewise linear explanations of protein coordinate data, resulting in a powerful and concise representation of the structure. The delineation is completely independent of the approaches of using hydrogen-bonding patterns or inspecting local substructural geometry that the current methods use. Indeed, as is common with applications of the MML criterion, this method is free of parameters and thresholds, in striking contrast to the existing programs which are often beset by them. The analysis of results over a large number of proteins suggests that the method produces consistent delineation of structures that encompasses, among others, the segments corresponding to standard secondary structure. AVAILABILITY: http://www.csse.monash.edu.au/~karun/pmml.     

Focal adhesions - the cytoskeletal connection

Cellular contacts with the extracellular matrix are regulated by the Rho family of GTPases through their effects on both the actin and the microtubule cytoarchitecture. Recent genetic, biochemical and structural data have highlighted the role played by a subset of actin-binding proteins in coupling integrins to cytoskeletal actin and in assembling signalling complexes that are important for cell motility and cell proliferation.     

Chemical compound navigator: a web-based chem-BLAST, chemical taxonomy-based search engine for browsing compounds

A novel technique to annotate, query, and analyze chemical compounds has been developed and is illustrated by using the inhibitor data on HIV protease-inhibitor complexes. In this method, all chemical compounds are annotated in terms of standard chemical structural fragments. These standard fragments are defined by using criteria, such as chemical classification; structural, chemical, or functional groups; and commercial, scientific or common names or synonyms. These fragments are then organized into a data tree based on their chemical substructures. Search engines have been developed to use this data tree to enable query on inhibitors of HIV protease (http://xpdb.nist.gov/hivsdb/hivsdb.html). These search engines use a new novel technique, Chemical Block Layered Alignment of Substructure Technique (Chem-BLAST) to search on the fragments of an inhibitor to look for its chemical structural neighbors. This novel technique to annotate and query compounds lays the foundation for the use of the Semantic Web concept on chemical compounds to allow end users to group, sort, and search structural neighbors accurately and efficiently. During annotation, it enables the attachment of "meaning" (i.e., semantics) to data in a manner that far exceeds the current practice of associating "metadata" with data by creating a knowledge base (or ontology) associated with compounds. Intended users of the technique are the research community and pharmaceutical industry, for which it will provide a new tool to better identify novel chemical structural neighbors to aid drug discovery.     

Functional architecture of the CFTR chloride channel

Cystic fibrosis is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR), a member of the ATP-binding cassette (ABC) family of membrane transport proteins. CFTR is unique among ABC proteins in that it functions not as an active transporter but as an ATP-gated Cl^? channel. As an ion channel, the function of the CFTR transmembrane channel pore that mediates Cl^? movement has been studied in great detail. On the other hand, only low resolution structural data is available on the transmembrane parts of the protein. The structure of the channel pore has, however, been modeled on the known structure of active transporter ABC proteins. Currently, significant barriers exist to building a unified view of CFTR pore structure and function. Reconciling functional data on the channel with indirect structural data based on other proteins with very different transport functions and substrates has proven problematic. This review summarizes current structural and functional models of the CFTR Cl^? channel pore, including a comprehensive review of previous electrophysiological investigations of channel structure and function. In addition, functional data on the three-dimensional arrangement of pore-lining helices, as well as contemporary hypotheses concerning conformational changes in the pore that occur during channel opening and closing, are discussed. Important similarities and differences between different models of the pore highlight current gaps in our knowledge of CFTR structure and function. In order to fill these gaps, structural and functional models of the membrane-spanning pore need to become better integrated.