Target selection and annotation for the structural genomics of the amidohydrolase and enolase superfamilies.
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ABSTRACT:
SUBMITTER: Pieper U
PROVIDER: S-EPMC2693957 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Structural genomics presents an enormous challenge with up to 100 000 protein targets in the human genome alone. At current rates of structure deter-mination, judicious selection of targets is necessary. Here, a phylogenetic approach to target selection is described which makes use of the National Center for Biotechnology Information database of Clusters of Orthologous Groups (COGS). The strategy is designed so that each new protein structure is likely to provide novel sequence-fold information. To demonstrate this approach, the NMR solution structure of YciH (COG0023), a putative translation initiation factor from Escherichia coli, has been determined and its fold classified. YciH is an ortholog of eIF-1/SUI1, an integral component of the translation initiation complex in eukaryotes. The structure consists of two antiparallel alpha-helices packed against the same side of a five-stranded beta-sheet. The first 31 residues of the 11.5 kDa protein are unstructured in solution. Comparative analysis indicates that the folded portion of YciH resembles a number of structures with the alpha-beta plait topology, though its sequence is not homologous to any of them. Thus, the phylogenetic approach to target selection described here was used successfully to identify a new homologous superfamily within this topology.
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Project description:The current pace of structural biology now means that protein three-dimensional structure can be known before protein function, making methods for assigning homology via structure comparison of growing importance. Previous research has suggested that sequence similarity after structure-based alignment is one of the best discriminators of homology and often functional similarity. Here, we exploit this observation, together with a merger of protein structure and sequence databases, to predict distant homologous relationships. We use the Structural Classification of Proteins (SCOP) database to link sequence alignments from the SMART and Pfam databases. We thus provide new alignments that could not be constructed easily in the absence of known three-dimensional structures. We then extend the method of Murzin (1993b) to assign statistical significance to sequence identities found after structural alignment and thus suggest the best link between diverse sequence families. We find that several distantly related protein sequence families can be linked with confidence, showing the approach to be a means for inferring homologous relationships and thus possible functions when proteins are of known structure but of unknown function. The analysis also finds several new potential superfamilies, where inspection of the associated alignments and superimpositions reveals conservation of unusual structural features or co-location of conserved amino acids and bound substrates. We discuss implications for Structural Genomics initiatives and for improvements to sequence comparison methods.
| S-EPMC2373547 | biostudies-literature
Project description:BACKGROUND: Development of novel antibacterial drugs is both an urgent healthcare necessity and a partially neglected field. The last decades have seen a substantial decrease in the discovery of novel antibiotics, which combined with the recent thrive of multi-drug-resistant pathogens have generated a scenario of general concern. The procedures involved in the discovery and development of novel antibiotics are economically challenging, time consuming and lack any warranty of success. Furthermore, the return-on-investment for an antibacterial drug is usually marginal when compared to other therapeutics, which in part explains the decrease of private investment. RESULTS: In this work we present antibacTR, a computational pipeline designed to aid researchers in the selection of potential drug targets, one of the initial steps in antibacterial-drug discovery. The approach was designed and implemented as part of two publicly funded initiatives aimed at discovering novel antibacterial targets, mechanisms and drugs for a priority list of Gram-negative pathogens: Acinetobacter baumannii, Escherichia coli, Helicobacter pylori, Pseudomonas aeruginosa and Stenotrophomonas maltophilia. However, at present this list has been extended to cover a total of 74 fully sequenced Gram-negative pathogens. antibacTR is based on sequence comparisons and queries to multiple databases (e.g. gene essentiality, virulence factors) to rank proteins according to their potential as antibacterial targets. The dynamic ranking of potential drug targets can easily be executed, customized and accessed by the user through a web interface which also integrates computational analyses performed in-house and visualizable on-site. These include three-dimensional modeling of protein structures and prediction of active sites among other functionally relevant ligand-binding sites. CONCLUSIONS: Given its versatility and ease-of-use at integrating both experimental annotation and computational analyses, antibacTR may effectively assist microbiologists, medicinal-chemists and other researchers working in the field of antibacterial drug-discovery. The public web-interface for antibacTR is available at 'http://bioinf.uab.cat/antibactr'.
| S-EPMC3932961 | biostudies-literature
Project description:The New York Consortium on Membrane Protein Structure (NYCOMPS), a part of the Protein Structure Initiative (PSI) in the USA, has as its mission to establish a high-throughput pipeline for determination of novel integral membrane protein structures. Here we describe our current target selection protocol, which applies structural genomics approaches informed by the collective experience of our team of investigators. We first extract all annotated proteins from our reagent genomes, i.e. the 96 fully sequenced prokaryotic genomes from which we clone DNA. We filter this initial pool of sequences and obtain a list of valid targets. NYCOMPS defines valid targets as those that, among other features, have at least two predicted transmembrane helices, no predicted long disordered regions and, except for community nominated targets, no significant sequence similarity in the predicted transmembrane region to any known protein structure. Proteins that feed our experimental pipeline are selected by defining a protein seed and searching the set of all valid targets for proteins that are likely to have a transmembrane region structurally similar to that of the seed. We require sequence similarity aligning at least half of the predicted transmembrane region of seed and target. Seeds are selected according to their feasibility and/or biological interest, and they include both centrally selected targets and community nominated targets. As of December 2008, over 6,000 targets have been selected and are currently being processed by the experimental pipeline. We discuss how our target list may impact structural coverage of the membrane protein space.
| S-EPMC2780672 | biostudies-literature
Project description:Many protein structures determined in high-throughput structural genomics centers, despite their significant novelty and importance, are available only as PDB depositions and are not accompanied by a peer-reviewed manuscript. Because of this they are not accessible by the standard tools of literature searches, remaining underutilized by the broad biological community.To address this issue we have developed TOPSAN, The Open Protein Structure Annotation Network, a web-based platform that combines the openness of the wiki model with the quality control of scientific communication. TOPSAN enables research collaborations and scientific dialogue among globally distributed participants, the results of which are reviewed by experts and eventually validated by peer review. The immediate goal of TOPSAN is to harness the combined experience, knowledge, and data from such collaborations in order to enhance the impact of the astonishing number and diversity of structures being determined by structural genomics centers and high-throughput structural biology.TOPSAN combines features of automated annotation databases and formal, peer-reviewed scientific research literature, providing an ideal vehicle to bridge a gap between rapidly accumulating data from high-throughput technologies and a much slower pace for its analysis and integration with other, relevant research.
| S-EPMC2936398 | biostudies-literature
Project description:BACKGROUND: The availability of suitable recombinant protein is still a major bottleneck in protein structure analysis. The Protein Structure Factory, part of the international structural genomics initiative, targets human proteins for structure determination. It has implemented high throughput procedures for all steps from cloning to structure calculation. This article describes the selection of human target proteins for structure analysis, our high throughput cloning strategy, and the expression of human proteins in Escherichia coli host cells. RESULTS AND CONCLUSION: Protein expression and sequence data of 1414 E. coli expression clones representing 537 different proteins are presented. 139 human proteins (18%) could be expressed and purified in soluble form and with the expected size. All E. coli expression clones are publicly available to facilitate further functional characterisation of this set of human proteins.
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Project description:The evolution of enzymes affects how well a species can adapt to new environmental conditions. During enzyme evolution, certain aspects of molecular function are conserved while other aspects can vary. Aspects of function that are more difficult to change or that need to be reused in multiple contexts are often conserved, while those that vary may indicate functions that are more easily changed or that are no longer required. In analogy to the study of conservation patterns in enzyme sequences and structures, we have examined the patterns of conservation and variation in enzyme function by analyzing graph isomorphisms among enzyme substrates of a large number of enzyme superfamilies. This systematic analysis of substrate substructures establishes the conservation patterns that typify individual superfamilies. Specifically, we determined the chemical substructures that are conserved among all known substrates of a superfamily and the substructures that are reacting in these substrates and then examined the relationship between the two. Across the 42 superfamilies that were analyzed, substantial variation was found in how much of the conserved substructure is reacting, suggesting that superfamilies may not be easily grouped into discrete and separable categories. Instead, our results suggest that many superfamilies may need to be treated individually for analyses of evolution, function prediction, and guiding enzyme engineering strategies. Annotating superfamilies with these conserved and reacting substructure patterns provides information that is orthogonal to information provided by studies of conservation in superfamily sequences and structures, thereby improving the precision with which we can predict the functions of enzymes of unknown function and direct studies in enzyme engineering. Because the method is automated, it is suitable for large-scale characterization and comparison of fundamental functional capabilities of both characterized and uncharacterized enzyme superfamilies.
| S-EPMC2453236 | biostudies-literature
Project description:Enolase is a glycolytic metalloenzyme involved in carbon metabolism. The advantage of targeting enolase lies in its essentiality in many biological processes such as cell wall formation and RNA turnover and as a plasminogen receptor. We initially used a DARTS assay to identify enolase as a target in Escherichia coli. The antibacterial activities of α-, β-, and γ-substituted seven-member ring tropolones were first evaluated against four strains representing a range of Gram-negative bacteria. We observed that the chemical properties and position of the substituents on the tropolone ring play an important role in the biological activity of the investigated compounds. Both α- and β-substituted phenyl derivatives of tropolone were the most active with minimum inhibitory concentrations in the range of 11-14 μg/mL. The potential inhibitory activity of the synthetic tropolones was further evaluated using an enolase inhibition assay, X-ray crystallography, and molecular docking simulations. The catalytic activity of enolase was effectively inhibited by both the naturally occurring β-thujaplicin and the α- and β-substituted phenyl derivatives of tropolones with IC50 values in range of 8-11 μM. Ligand binding parameters were assessed by isothermal titration calorimetry and differential scanning calorimetry techniques and agreed with the in vitro data. Our studies validate the antibacterial potential of tropolones with careful consideration of the position and character of chelating moieties for stronger interaction with metal ions and residues in the enolase active site.
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Project description:Structural genomics (SG) initiatives are expanding the universe of protein fold space by rapidly determining structures of proteins that were intentionally selected on the basis of low sequence similarity to proteins of known structure. Often these proteins have no associated biochemical or cellular functions. The SG success has resulted in an accelerated deposition of novel structures. In some cases the structural bioinformatics analysis applied to these novel structures has provided specific functional assignment. However, this approach has also uncovered limitations in the functional analysis of uncharacterized proteins using traditional sequence and backbone structure methodologies. A novel method, named pvSOAR (pocket and void Surface of Amino Acid Residues), of comparing the protein surfaces of geometrically defined pockets and voids was developed. pvSOAR was able to detect previously unrecognized and novel functional relationships between surface features of proteins. In this study, pvSOAR is applied to several structural genomics proteins. We examined the surfaces of YecM, BioH, and RpiB from Escherichia coli as well as the CBS domains from inosine-5'-monosphate dehydrogenase from Streptococcus pyogenes, conserved hypothetical protein Ta549 from Thermoplasm acidophilum, and CBS domain protein mt1622 from Methanobacterium thermoautotrophicum with the goal to infer information about their biochemical function.
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Project description:Exoribonucleases play an important role in all aspects of RNA metabolism. Biochemical and genetic analyses in recent years have identified many new RNases and it is now clear that a single cell can contain multiple enzymes of this class. Here, we analyze the structure and phylogenetic distribution of the known exoribonucleases. Based on extensive sequence analysis and on their catalytic properties, all of the exoribonucleases and their homologs have been grouped into six superfamilies and various subfamilies. We identify common motifs that can be used to characterize newly-discovered exoribonucleases, and based on these motifs we correct some previously misassigned proteins. This analysis may serve as a useful first step for developing a nomenclature for this group of enzymes.
| S-EPMC56904 | biostudies-literature