RESUMEN
We described previously the presence in Acinetobacter baumannii of a novel outer membrane (OM) protein, CarO, which functions as an L-ornithine OM channel and whose loss was concomitant with increased carbapenem resistance among clonally related nosocomial isolates of this opportunistic pathogen. Here, we describe the existence of extensive genetic diversity at the carO gene within the A. baumannii clinical population. The systematic analysis of carO sequences from A. baumannii isolates obtained from public hospitals in Argentina revealed the existence of four highly polymorphic carO variants among them. Sequence polymorphism between the different A. baumannii CarO variants was concentrated in three well-defined protein regions that superimposed mostly to predicted surface-exposed loops. Polymorphism among A. baumannii CarO variants was manifested in differential electrophoretic mobilities, antigenic properties, abilities to form stable oligomeric structures, and l-ornithine influx abilities through the A. baumannii OM under in vivo conditions. Incongruence between the phylogenies of the clinical A. baumannii isolates analyzed and those of the carO variants they harbor suggests the existence of assortative (entire-gene) carO recombinational exchange within the A. baumannii population. Exchange of carO variants possessing differential characteristics mediated by horizontal gene transfer may constitute an A. baumannii population strategy to survive radically changing environmental conditions, such as the leap from inanimate sources to human hosts and vice versa, persistence in a compromised host, and/or survival in health care facilities.
Asunto(s)
Acinetobacter baumannii/genética , Proteínas de la Membrana Bacteriana Externa/genética , Transferencia de Gen Horizontal , Variación Genética , Recombinación Genética , Infecciones por Acinetobacter/microbiología , Acinetobacter baumannii/aislamiento & purificación , Secuencia de Aminoácidos , Antígenos Bacterianos/química , Antígenos Bacterianos/genética , Antígenos Bacterianos/inmunología , Antígenos Bacterianos/metabolismo , Argentina , Proteínas de la Membrana Bacteriana Externa/química , Proteínas de la Membrana Bacteriana Externa/inmunología , Proteínas de la Membrana Bacteriana Externa/metabolismo , Análisis por Conglomerados , ADN Bacteriano/química , ADN Bacteriano/genética , Hospitales , Humanos , Datos de Secuencia Molecular , Ornitina/metabolismo , Filogenia , Multimerización de Proteína , Alineación de Secuencia , Análisis de Secuencia de ADN , Homología de Secuencia de AminoácidoRESUMEN
UNLABELLED: In the post-genomic era, the annotation of protein function facilitates the understanding of various biological processes. To extend the range of function annotation methods to the twilight zone of sequence identity, we have developed approaches that exploit both protein tertiary structure and/or protein sequence evolutionary relationships. To serve the scientific community, we have integrated the structure prediction tools, TASSER, TASSER-Lite and METATASSER, and the functional inference tools, FINDSITE, a structure-based algorithm for binding site prediction, Gene Ontology molecular function inference and ligand screening, EFICAz(2), a sequence-based approach to enzyme function inference and DBD-hunter, an algorithm for predicting DNA-binding proteins and associated DNA-binding residues, into a unified web resource, Protein Structure and Function prediction Resource (PSiFR). AVAILABILITY AND IMPLEMENTATION: PSiFR is freely available for use on the web at http://psifr.cssb.biology.gatech.edu/
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Conformación Proteica , Proteínas/química , Programas Informáticos , Sitios de Unión , Bases de Datos de Proteínas , Proteínas/metabolismoRESUMEN
The classical view of the space of protein structures is that it is populated by a discrete set of protein folds. For proteins up to 200 residues long, by using structural alignments and building upon ideas of the completeness and continuity of structure space, we show that nearly any structure is significantly related to any other using a transitive set of no more than 7 intermediate structurally related proteins. This result holds for all structures in the Protein Data Bank, even when structural relationships between evolutionary related proteins (as detected by threading or functional analyses) are excluded. A similar picture holds for an artificial library of compact, hydrogen-bonded, homopolypeptide structures. The 3 sets share the global connectivity features of random graphs, in which the local connectivity of each node (i.e., the number of neighboring structures per protein) is preserved. This high connectivity supports the continuous view of single-domain protein structure space. More importantly, these results do not depend on evolution, rather just on the physics of protein structures. The fact that evolutionary divergence need not be invoked to explain the continuous nature of protein structure space has implications for how the universe of protein structures might have originated, and how function should be transferred between proteins of similar structure.
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Proteínas/química , Fenómenos Biofísicos , Bases de Datos de Proteínas , Evolución Molecular , Modelos Moleculares , Péptidos/química , Pliegue de Proteína , Estructura Secundaria de Proteína , Proteínas/genética , Alineación de Secuencia , Homología Estructural de ProteínaRESUMEN
BACKGROUND: We previously developed EFICAz, an enzyme function inference approach that combines predictions from non-completely overlapping component methods. Two of the four components in the original EFICAz are based on the detection of functionally discriminating residues (FDRs). FDRs distinguish between member of an enzyme family that are homofunctional (classified under the EC number of interest) or heterofunctional (annotated with another EC number or lacking enzymatic activity). Each of the two FDR-based components is associated to one of two specific kinds of enzyme families. EFICAz exhibits high precision performance, except when the maximal test to training sequence identity (MTTSI) is lower than 30%. To improve EFICAz's performance in this regime, we: i) increased the number of predictive components and ii) took advantage of consensual information from the different components to make the final EC number assignment. RESULTS: We have developed two new EFICAz components, analogs to the two FDR-based components, where the discrimination between homo and heterofunctional members is based on the evaluation, via Support Vector Machine models, of all the aligned positions between the query sequence and the multiple sequence alignments associated to the enzyme families. Benchmark results indicate that: i) the new SVM-based components outperform their FDR-based counterparts, and ii) both SVM-based and FDR-based components generate unique predictions. We developed classification tree models to optimally combine the results from the six EFICAz components into a final EC number prediction. The new implementation of our approach, EFICAz2, exhibits a highly improved prediction precision at MTTSI < 30% compared to the original EFICAz, with only a slight decrease in prediction recall. A comparative analysis of enzyme function annotation of the human proteome by EFICAz2 and KEGG shows that: i) when both sources make EC number assignments for the same protein sequence, the assignments tend to be consistent and ii) EFICAz2 generates considerably more unique assignments than KEGG. CONCLUSION: Performance benchmarks and the comparison with KEGG demonstrate that EFICAz2 is a powerful and precise tool for enzyme function annotation, with multiple applications in genome analysis and metabolic pathway reconstruction. The EFICAz2 web service is available at: http://cssb.biology.gatech.edu/skolnick/webservice/EFICAz2/index.html.
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Inteligencia Artificial , Biología Computacional/métodos , Enzimas/clasificación , Programas Informáticos , Bases de Datos Factuales , Enzimas/química , Enzimas/fisiología , HumanosAsunto(s)
Biomarcadores/metabolismo , Metabolómica , Terapéutica/métodos , Animales , Asma/metabolismo , Humanos , Neoplasias/metabolismoRESUMEN
BACKGROUND: Certain endogenous metabolites can influence the rate of cancer cell growth. For example, diacylglycerol, ceramides and sphingosine, NAD+ and arginine exert this effect by acting as signaling molecules, while carrying out other important cellular functions. Metabolites can also be involved in the control of cell proliferation by directly regulating gene expression in ways that are signaling pathway-independent, e.g. by direct activation of transcription factors or by inducing epigenetic processes. The fact that metabolites can affect the cancer process on so many levels suggests that the change in concentration of some metabolites that occurs in cancer cells could have an active role in the progress of the disease. RESULTS: CoMet, a fully automated Computational Metabolomics method to predict changes in metabolite levels in cancer cells compared to normal references has been developed and applied to Jurkat T leukemia cells with the goal of testing the following hypothesis: Up or down regulation in cancer cells of the expression of genes encoding for metabolic enzymes leads to changes in intracellular metabolite concentrations that contribute to disease progression. All nine metabolites predicted to be lowered in Jurkat cells with respect to lymphoblasts that were examined (riboflavin, tryptamine, 3-sulfino-L-alanine, menaquinone, dehydroepiandrosterone, alpha-hydroxystearic acid, hydroxyacetone, seleno-L-methionine and 5,6-dimethylbenzimidazole), exhibited antiproliferative activity that has not been reported before, while only two (bilirubin and androsterone) of the eleven tested metabolites predicted to be increased or unchanged in Jurkat cells displayed significant antiproliferative activity. CONCLUSION: These results: a) demonstrate that CoMet is a valuable method to identify potential compounds for experimental validation, b) indicate that cancer cell metabolism may be regulated to reduce the intracellular concentration of certain antiproliferative metabolites, leading to uninhibited cellular growth and c) suggest that many other endogenous metabolites with important roles in carcinogenesis are awaiting discovery.
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Proliferación Celular , Leucemia de Células T/metabolismo , Biología de Sistemas , Antimetabolitos Antineoplásicos/farmacología , Proliferación Celular/efectos de los fármacos , Progresión de la Enfermedad , Diseño de Fármacos , Regulación Enzimológica de la Expresión Génica , Regulación Neoplásica de la Expresión Génica , Humanos , Células Jurkat , Leucemia de Células T/enzimología , Leucemia de Células T/genética , Leucemia de Células T/patología , Reproducibilidad de los ResultadosRESUMEN
Anaeromyxobacter dehalogenans strain 2CP-C is a versaphilic delta-Proteobacterium distributed throughout many diverse soil and sediment environments. 16S rRNA gene phylogenetic analysis groups A. dehalogenans together with the myxobacteria, which have distinguishing characteristics including strictly aerobic metabolism, sporulation, fruiting body formation, and surface motility. Analysis of the 5.01 Mb strain 2CP-C genome substantiated that this organism is a myxobacterium but shares genotypic traits with the anaerobic majority of the delta-Proteobacteria (i.e., the Desulfuromonadales). Reflective of its respiratory versatility, strain 2CP-C possesses 68 genes coding for putative c-type cytochromes, including one gene with 40 heme binding motifs. Consistent with its relatedness to the myxobacteria, surface motility was observed in strain 2CP-C and multiple types of motility genes are present, including 28 genes for gliding, adventurous (A-) motility and 17 genes for type IV pilus-based motility (i.e., social (S-) motility) that all have homologs in Myxococcus xanthus. Although A. dehalogenans shares many metabolic traits with the anaerobic majority of the delta-Proteobacteria, strain 2CP-C grows under microaerophilic conditions and possesses detoxification systems for reactive oxygen species. Accordingly, two gene clusters coding for NADH dehydrogenase subunits and two cytochrome oxidase gene clusters in strain 2CP-C are similar to those in M. xanthus. Remarkably, strain 2CP-C possesses a third NADH dehydrogenase gene cluster and a cytochrome cbb(3) oxidase gene cluster, apparently acquired through ancient horizontal gene transfer from a strictly anaerobic green sulfur bacterium. The mosaic nature of the A. dehalogenans strain 2CP-C genome suggests that the metabolically versatile, anaerobic members of the delta-Proteobacteria may have descended from aerobic ancestors with complex lifestyles.
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Deltaproteobacteria/genética , Genoma Bacteriano , Myxococcales/genética , Microbiología del Suelo , Proteínas Bacterianas/genética , Deltaproteobacteria/clasificación , Enzimas/clasificación , Enzimas/genética , Mosaicismo , Myxococcales/clasificación , Consumo de Oxígeno , Filogenia , ARN Bacteriano/genética , ARN Ribosómico 18S/genéticaRESUMEN
Ferredoxin (flavodoxin)-NADP(H) reductases (FNRs) are ubiquitous flavoenzymes that deliver NADPH or low-potential one-electron donors (ferredoxin, flavodoxin, adrenodoxin) to redox-based metabolic reactions in plastids, mitochondria and bacteria. Plastidic FNRs are quite efficient reductases. In contrast, FNRs from organisms possessing a heterotrophic metabolism or anoxygenic photosynthesis display turnover numbers 20- to 100-fold lower than those of their plastidic and cyanobacterial counterparts. Several structural features of these enzymes have yet to be explained. The residue Y308 in pea FNR is stacked nearly parallel to the re-face of the flavin and is highly conserved amongst members of the family. By computing the relative free energy for the lumiflavin-phenol pair at different angles with the relative position found for Y308 in pea FNR, it can be concluded that this amino acid is constrained against the isoalloxazine. This effect is probably caused by amino acids C266 and L268, which face the other side of this tyrosine. Simple and double FNR mutants of these amino acids were obtained and characterized. It was observed that a decrease or increase in the amino acid volume resulted in a decrease in the catalytic efficiency of the enzyme without altering the protein structure. Our results provide experimental evidence that the volume of these amino acids participates in the fine-tuning of the catalytic efficiency of the enzyme.
Asunto(s)
Ferredoxina-NADP Reductasa/química , Sustitución de Aminoácidos , Aminoácidos/química , Aminoácidos/genética , Catálisis , Dominio Catalítico/genética , Cristalografía por Rayos X , Ferredoxina-NADP Reductasa/genética , Flavina-Adenina Dinucleótido/análisis , Flavina-Adenina Dinucleótido/química , Calor , Cinética , Mutación , Conformación Proteica , Pliegue de Proteína , Estructura Secundaria de ProteínaRESUMEN
In this study, the immobilization of toxic uranium [U(VI)] mediated by the intrinsic phosphatase activities of naturally occurring bacteria isolated from contaminated subsurface soils was examined. The phosphatase phenotypes of strains belonging to the genera, Arthrobacter, Bacillus and Rahnella, previously isolated from subsurface soils at the US Department of Energy's (DOE) Oak Ridge Field Research Center (ORFRC), were determined. The ORFRC represents a unique, extreme environment consisting of highly acidic soils with co-occurring heavy metals, radionuclides and high nitrate concentrations. Isolates exhibiting phosphatase-positive phenotypes indicative of constitutive phosphatase activity were subsequently tested in U(VI) bioprecipitation assays. When aerobically grown in synthetic groundwater (pH 5.5) amended with 10 mM glycerol-3-phosphate (G3P), phosphatase-positive Bacillus and Rahnella spp. strains Y9-2 and Y9602 liberated sufficient phosphate to precipitate 73% and 95% of total soluble U added as 200 microM uranyl acetate respectively. In contrast, an Arthrobacter sp. X34 exhibiting a phosphatase-negative phenotype did not liberate phosphate from G3P or promote U(VI) precipitation. This study provides the first evidence of U(VI) precipitation via the phosphatase activity of naturally occurring Bacillus and Rahnella spp. isolated from the acidic subsurface at the DOE ORFRC.
Asunto(s)
Bacillus , Fosfatos/química , Rahnella , Microbiología del Suelo , Contaminantes Radiactivos del Suelo/química , Uranio/química , Aerobiosis , Bacillus/efectos de los fármacos , Bacillus/enzimología , Bacillus/genética , Bacillus/aislamiento & purificación , Biodegradación Ambiental , Precipitación Química , Farmacorresistencia Bacteriana , Metales/farmacología , Datos de Secuencia Molecular , Fosfatos/metabolismo , Monoéster Fosfórico Hidrolasas/metabolismo , Rahnella/efectos de los fármacos , Rahnella/enzimología , Rahnella/genética , Rahnella/aislamiento & purificación , Análisis de Secuencia de ADN , Contaminantes del Suelo/metabolismo , Contaminantes Radiactivos del Suelo/metabolismo , Contaminantes Radiactivos del Agua/metabolismoRESUMEN
BACKGROUND: The functional annotation of most genes in newly sequenced genomes is inferred from similarity to previously characterized sequences, an annotation strategy that often leads to erroneous assignments. We have performed a reannotation of 245 genomes using an updated version of EFICAz, a highly precise method for enzyme function prediction. RESULTS: Based on our three-field EC number predictions, we have obtained lower-bound estimates for the average enzyme content in Archaea (29%), Bacteria (30%) and Eukarya (18%). Most annotations added in KEGG from 2005 to 2006 agree with EFICAz predictions made in 2005. The coverage of EFICAz predictions is significantly higher than that of KEGG, especially for eukaryotes. Thousands of our novel predictions correspond to hypothetical proteins. We have identified a subset of 64 hypothetical proteins with low sequence identity to EFICAz training enzymes, whose biochemical functions have been recently characterized and find that in 96% (84%) of the cases we correctly identified their three-field (four-field) EC numbers. For two of the 64 hypothetical proteins: PA1167 from Pseudomonas aeruginosa, an alginate lyase (EC 4.2.2.3) and Rv1700 of Mycobacterium tuberculosis H37Rv, an ADP-ribose diphosphatase (EC 3.6.1.13), we have detected annotation lag of more than two years in databases. Two examples are presented where EFICAz predictions act as hypothesis generators for understanding the functional roles of hypothetical proteins: FLJ11151, a human protein overexpressed in cancer that EFICAz identifies as an endopolyphosphatase (EC 3.6.1.10), and MW0119, a protein of Staphylococcus aureus strain MW2 that we propose as candidate virulence factor based on its EFICAz predicted activity, sphingomyelin phosphodiesterase (EC 3.1.4.12). CONCLUSION: Our results suggest that we have generated enzyme function annotations of high precision and recall. These predictions can be mined and correlated with other information sources to generate biologically significant hypotheses and can be useful for comparative genome analysis and automated metabolic pathway reconstruction.
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Enzimas/genética , Enzimas/metabolismo , Animales , Archaea/enzimología , Archaea/genética , Bacterias/enzimología , Bacterias/genética , Células Eucariotas/enzimología , Genes Arqueales , Genes Bacterianos , Genoma , Genómica/métodosRESUMEN
The size and origin of the protein fold universe is of fundamental and practical importance. Analyzing randomly generated, compact sticky homopolypeptide conformations constructed in generic simplified and all-atom protein models, all have similar folds in the library of solved structures, the Protein Data Bank, and conversely, all compact, single-domain protein structures in the Protein Data Bank have structural analogues in the compact model set. Thus, both sets are highly likely complete, with the protein fold universe arising from compact conformations of hydrogen-bonded, secondary structures. Because side chains are represented by their Cbeta atoms, these results also suggest that the observed protein folds are insensitive to the details of side-chain packing. Sequence specificity enters both in fine-tuning the structure and thermodynamically stabilizing a given fold with respect to the set of alternatives. Scanning the models against a three-dimensional active-site library, close geometric matches are frequently found. Thus, the presence of active-site-like geometries also seems to be a consequence of the packing of compact, secondary structural elements. These results have significant implications for the evolution of protein structure and function.
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Bases de Datos de Proteínas , Evolución Molecular , Modelos Moleculares , Estructura Terciaria de Proteína , Animales , Sitios de Unión , Humanos , Pliegue de Proteína , Estructura Secundaria de Proteína , Proteínas/químicaRESUMEN
Many essential cellular processes such as signal transduction, transport, cellular motion and most regulatory mechanisms are mediated by protein-protein interactions. In recent years, new experimental techniques have been developed to discover the protein-protein interaction networks of several organisms. However, the accuracy and coverage of these techniques have proven to be limited, and computational approaches remain essential both to assist in the design and validation of experimental studies and for the prediction of interaction partners and detailed structures of protein complexes. Here, we provide a critical overview of existing structure-independent and structure-based computational methods. Although these techniques have significantly advanced in the past few years, we find that most of them are still in their infancy. We also provide an overview of experimental techniques for the detection of protein-protein interactions. Although the developments are promising, false positive and false negative results are common, and reliable detection is possible only by taking a consensus of different experimental approaches. The shortcomings of experimental techniques affect both the further development and the fair evaluation of computational prediction methods. For an adequate comparative evaluation of prediction and high-throughput experimental methods, an appropriately large benchmark set of biophysically characterized protein complexes would be needed, but is sorely lacking.
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Biofisica/métodos , Fenómenos Fisiológicos Celulares , Mapeo de Interacción de Proteínas , Algoritmos , Animales , Sitios de Unión , Transporte Biológico , Biología Computacional , Bases de Datos de Proteínas , Escherichia coli/metabolismo , Humanos , Modelos Biológicos , Filogenia , Unión Proteica , Programas InformáticosRESUMEN
The recently developed TASSER (Threading/ASSembly/Refinement) method is applied to predict the tertiary structures of all CASP6 targets. TASSER is a hierarchical approach that consists of template identification by the threading program PROSPECTOR_3, followed by tertiary structure assembly via rearranging continuous template fragments. Assembly occurs using parallel hyperbolic Monte Carlo sampling under the guide of an optimized, reduced force field that includes knowledge-based statistical potentials and spatial restraints extracted from threading alignments. Models are automatically selected from the Monte Carlo trajectories in the low-temperature replicas using the clustering program SPICKER. For all 90 CASP targets/domains, PROSPECTOR_3 generates initial alignments with an average root-mean-square deviation (RMSD) to native of 8.4 A with 79% coverage. After TASSER reassembly, the average RMSD decreases to 5.4 A over the same aligned residues; the overall cumulative TM-score increases from 39.44 to 52.53. Despite significant improvements over the PROSPECTOR_3 template alignment observed in all target categories, the overall quality of the final models is essentially dictated by the quality of threading templates: The average TM-scores of TASSER models in the three categories are, respectively, 0.79 [comparative modeling (CM), 43 targets/domains], 0.47 [fold recognition (FR), 37 targets/domains], and 0.30 [new fold (NF), 10 targets/domains]. This highlights the need to develop novel (or improved) approaches to identify very distant targets as well as better NF algorithms.
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Biología Computacional/métodos , Estructura Terciaria de Proteína , Proteómica/métodos , Algoritmos , Automatización , Simulación por Computador , Computadores , Interpretación Estadística de Datos , Bases de Datos de Proteínas , Modelos Moleculares , Método de Montecarlo , Pliegue de Proteína , Estructura Secundaria de Proteína , Reproducibilidad de los Resultados , Alineación de Secuencia , Programas InformáticosRESUMEN
EFICAz (Enzyme Function Inference by Combined Approach) is an automatic engine for large-scale enzyme function inference that combines predictions from four different methods developed and optimized to achieve high prediction accuracy: (i) recognition of functionally discriminating residues (FDRs) in enzyme families obtained by a Conservation-controlled HMM Iterative procedure for Enzyme Family classification (CHIEFc), (ii) pairwise sequence comparison using a family specific Sequence Identity Threshold, (iii) recognition of FDRs in Multiple Pfam enzyme families, and (iv) recognition of multiple Prosite patterns of high specificity. For FDR (i.e. conserved positions in an enzyme family that discriminate between true and false members of the family) identification, we have developed an Evolutionary Footprinting method that uses evolutionary information from homofunctional and heterofunctional multiple sequence alignments associated with an enzyme family. The FDRs show a significant correlation with annotated active site residues. In a jackknife test, EFICAz shows high accuracy (92%) and sensitivity (82%) for predicting four EC digits in testing sequences that are <40% identical to any member of the corresponding training set. Applied to Escherichia coli genome, EFICAz assigns more detailed enzymatic function than KEGG, and generates numerous novel predictions.
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Biología Computacional/métodos , Enzimas/genética , Enzimas/fisiología , Genómica/métodos , Programas Informáticos , Secuencia de Aminoácidos , Sitios de Unión , Bases de Datos de Proteínas , Enzimas/clasificación , Escherichia coli/enzimología , Escherichia coli/genética , Genoma BacterianoRESUMEN
Ferredoxin (flavodoxin)-NADP(H) reductases (FNRs) are ubiquitous flavoenzymes that deliver NADPH or low potential one-electron donors (ferredoxin, flavodoxin, adrenodoxin) to redox-based metabolisms in plastids, mitochondria and bacteria. Two great families of FAD-containing proteins displaying FNR activity have evolved from different and independent origins. The enzymes present in mitochondria and some bacterial genera are members of the structural superfamily of disulfide oxidoreductases whose prototype is glutathione reductase. A second group, comprising the FNRs from plastids and most eubacteria, constitutes a unique family, the plant-type FNRs, totally unrelated in sequence with the former. The two-domain structure of the plant family of FNR also provides the basic scaffold for an extended superfamily of electron transfer flavoproteins. In this article we compare FNR flavoenzymes from very different origins and describe how the natural history of these reductases shaped structure, flavin conformation and catalytic activity to face the very different metabolic demands they have to deal with in their hosts. We show that plant-type FNRs can be classified into a plastidic class, characterised by extended FAD conformation and high catalytic efficiency, and a bacterial class displaying a folded FAD molecule and low turnover rates. Sequence alignments supported this classification, providing a criterion to predict the structural and biochemical properties of newly identified members of the family.
Asunto(s)
Bacterias/enzimología , Ferredoxina-NADP Reductasa/fisiología , Plantas/enzimología , Mitocondrias/enzimología , Filogenia , Estructura Terciaria de ProteínaRESUMEN
MOTIVATION: Several protein function prediction methods employ structural features captured in three-dimensional (3D) descriptors of biologically relevant sites. These methods are successful when applied to high-resolution structures, but their detection ability in lower resolution predicted structures has only been tested for a few cases. RESULTS: A method that automatically generates a library of 3D functional descriptors for the structure-based prediction of enzyme active sites (automated functional templates, 593 in total for 162 different enzymes), based on functional and structural information automatically extracted from public databases, has been developed and evaluated using decoy structures. The applicability to predicted structures was investigated by analyzing decoys of varying quality, derived from enzyme native structures. For 35% of decoy structures, our method identifies the active site in models having 3-4 A coordinate root mean square deviation from the native structure, a quality that is reachable using state of the art protein structure prediction algorithms. AVAILABILITY: See http://www.bioinformatics.buffalo.edu/resources/aft/
Asunto(s)
Algoritmos , Modelos Moleculares , Proteínas/química , Proteínas/clasificación , Alineación de Secuencia/métodos , Análisis de Secuencia de Proteína/métodos , Secuencia de Aminoácidos , Sitios de Unión , Simulación por Computador , Bases de Datos de Proteínas , Enzimas/química , Enzimas/clasificación , Proteínas de Escherichia coli/química , Proteínas de Escherichia coli/clasificación , Datos de Secuencia Molecular , Unión Proteica , Conformación Proteica , Reproducibilidad de los Resultados , Sensibilidad y Especificidad , Relación Estructura-ActividadRESUMEN
We have applied the TOUCHSTONE structure prediction algorithm that spans the range from homology modeling to ab initio folding to all protein targets in CASP5. Using our threading algorithm PROSPECTOR that does not utilize input from metaservers, one threads against a representative set of PDB templates. If a template is significantly hit, Generalized Comparative Modeling designed to span the range from closely to distantly related proteins from the template is done. This involves freezing the aligned regions and relaxing the remaining structure to accommodate insertions or deletions with respect to the template. For all targets, consensus predicted side chain contacts from at least weakly threading templates are pooled and incorporated into ab initio folding. Often, TOUCHSTONE performs well in the CM to FR categories, with PROSPECTOR showing significant ability to identify analogous templates. When ab initio folding is done, frequently the best models are closer to the native state than the initial template. Among the particularly good predictions are T0130 in the CM/FR category, T0138 in the FR(H) category, T0135 in the FR(A) category, T0170 in the FR/NF category and T0181 in the NF category. Improvements in the approach are needed in the FR/NF and NF categories. Nevertheless, TOUCHSTONE was one of the best performing algorithms over all categories in CASP5.
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Algoritmos , Conformación Proteica , Proteínas/química , Modelos Moleculares , Estructura Secundaria de Proteína , Estructura Terciaria de ProteínaRESUMEN
MULTIPROSPECTOR, a multimeric threading algorithm for the prediction of protein-protein interactions, is applied to the genome of Saccharomyces cerevisiae. Each possible pairwise interaction among more than 6000 encoded proteins is evaluated against a dimer database of 768 complex structures by using a confidence estimate of the fold assignment and the magnitude of the statistical interfacial potentials. In total, 7321 interactions between pairs of different proteins are predicted, based on 304 complex structures. Quality estimation based on the coincidence of subcellular localizations and biological functions of the predicted interactors shows that our approach ranks third when compared with all other large-scale methods. Unlike other in silico methods, MULTIPROSPECTOR is able to identify the residues that participate directly in the interaction. Three hundred seventy-four of our predictions can be found by at least one of the other studies, which is compatible with the overlap between two different other methods. From the analysis of the mRNA abundance data, our method does not bias towards proteins with high abundance. Finally, several relevant predictions involved in various functions are presented. In summary, we provide a novel approach to predict protein-protein interactions on a genomic scale that is a useful complement to experimental methods.