994 resultados para Critical Sequence
Resumo:
Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called `early warning signals', and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data.
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Comparison of multiple protein structures has a broad range of applications in the analysis of protein structure, function and evolution. Multiple structure alignment tools (MSTAs) are necessary to obtain a simultaneous comparison of a family of related folds. In this study, we have developed a method for multiple structure comparison largely based on sequence alignment techniques. A widely used Structural Alphabet named Protein Blocks (PBs) was used to transform the information on 3D protein backbone conformation as a ID sequence string. A progressive alignment strategy similar to CLUSTALW was adopted for multiple PB sequence alignment (mulPBA). Highly similar stretches identified by the pairwise alignments are given higher weights during the alignment. The residue equivalences from PB based alignments are used to obtain a three dimensional fit of the structures followed by an iterative refinement of the structural superposition. Systematic comparisons using benchmark datasets of MSTAs underlines that the alignment quality is better than MULTIPROT, MUSTANG and the alignments in HOMSTRAD, in more than 85% of the cases. Comparison with other rigid-body and flexible MSTAs also indicate that mulPBA alignments are superior to most of the rigid-body MSTAs and highly comparable to the flexible alignment methods. (C) 2012 Elsevier Masson SAS. All rights reserved.
Ca2+ Binding to the ExDxD Motif Regulates the DNA Cleavage Specificity of a Promiscuous Endonuclease
Resumo:
Most of the restriction endonucleases (REases) are dependent on Mg2+ for DNA cleavage, and in general, Ca2+ inhibits their activity. RKpnI, an HNH active site containing beta beta alpha-Me finger nuclease, is an exception. In presence of Ca2+, the enzyme exhibits high-fidelity DNA cleavage and complete suppression of Mg2+-induced promiscuous activity. To elucidate the mechanism of unusual Ca2+-mediated activity, we generated alanine variants in the putative Ca-2+ binding motif, E(132)xD(134)xD(136), of the enzyme. Mutants showed decreased levels of DNA cleavage in the presence of Ca2+. We demonstrate that ExDxD residues are involved in Ca2+ coordination; however, the invariant His of the catalytic HNH motif acts as a general base for nucleophile activation, and the other two active site residues, D148 and Q175, also participate in Ca2+-mediated cleavage. Insertion of a 10-amino acid linker to disrupt the spatial organization of the ExDxD and HNH motifs impairs Ca2+ binding and affects DNA cleavage by the enzyme. Although ExDxD mutant enzymes retained efficient cleavage at the canonical sites in the presence of Mg2+, the promiscuous activity was greatly reduced, indicating that the carboxyl residues of the acidic triad play an important role in sequence recognition by the enzyme. Thus, the distinct Ca2+ binding motif that confers site specific cleavage upon Ca2+ binding is also critical for the promiscuous activity of the Mg2+-bound enzyme, revealing its role in metal ion-mediated modulation of DNA cleavage.
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Heat shock protein information resource (HSPIR) is a concerted database of six major heat shock proteins (HSPs), namely, Hsp70, Hsp40, Hsp60, Hsp90, Hsp100 and small HSP. The HSPs are essential for the survival of all living organisms, as they protect the conformations of proteins on exposure to various stress conditions. They are a highly conserved group of proteins involved in diverse physiological functions, including de novo folding, disaggregation and protein trafficking. Moreover, their critical role in the control of disease progression made them a prime target of research. Presently, limited information is available on HSPs in reference to their identification and structural classification across genera. To that extent, HSPIR provides manually curated information on sequence, structure, classification, ontology, domain organization, localization and possible biological functions extracted from UniProt, GenBank, Protein Data Bank and the literature. The database offers interactive search with incorporated tools, which enhances the analysis. HSPIR is a reliable resource for researchers exploring structure, function and evolution of HSPs.
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We report the draft genome sequence of methicillin-resistant Staphylococcus aureus (MRSA) strain ST672, an emerging disease clone in India, from a septicemia patient. The genome size is about 2.82 Mb with 2,485 open reading frames (ORFs). The staphylococcal cassette chromosome mec (SCCmec) element (type V) and immune evasion cluster appear to be different from those of strain ST772 on preliminary examination.
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Resistance to therapy limits the effectiveness of drug treatment in many diseases. Drug resistance can be considered as a successful outcome of the bacterial struggle to survive in the hostile environment of a drug-exposed cell. An important mechanism by which bacteria acquire drug resistance is through mutations in the drug target. Drug resistant strains (multi-drug resistant and extensively drug resistant) of Mycobacterium tuberculosis are being identified at alarming rates, increasing the global burden of tuberculosis. An understanding of the nature of mutations in different drug targets and how they achieve resistance is therefore important. An objective of this study is to first decipher sequence as well as structural bases for the observed resistance in known drug resistant mutants and then to predict positions in each target that are more prone to acquiring drug resistant mutations. A curated database containing hundreds of mutations in the 38 drug targets of nine major clinical drugs, associated with resistance is studied here. Mutations have been classified into those that occur in the binding site itself, those that occur in residues interacting with the binding site and those that occur in outer zones. Structural models of the wild type and mutant forms of the target proteins have been analysed to seek explanations for reduction in drug binding. Stability analysis of an entire array of 19 mutations at each of the residues for each target has been computed using structural models. Conservation indices of individual residues, binding sites and whole proteins are computed based on sequence conservation analysis of the target proteins. The analyses lead to insights about which positions in the polypeptide chain have a higher propensity to acquire drug resistant mutations. Thus critical insights can be obtained about the effect of mutations on drug binding, in terms of which amino acid positions and therefore which interactions should not be heavily relied upon, which in turn can be translated into guidelines for modifying the existing drugs as well as for designing new drugs. The methodology can serve as a general framework to study drug resistant mutants in other micro-organisms as well.
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Drought is the most crucial environmental factor that limits productivity of many crop plants. Exploring novel genes and gene combinations is of primary importance in plant drought tolerance research. Stress tolerant genotypes/species are known to express novel stress responsive genes with unique functional significance. Hence, identification and characterization of stress responsive genes from these tolerant species might be a reliable option to engineer the drought tolerance. Safflower has been found to be a relatively drought tolerant crop and thus, it has been the choice of study to characterize the genes expressed under drought stress. In the present study, we have evaluated differential drought tolerance of two cultivars of safflower namely, A1 and Nira using selective physiological marker traits and we have identified cultivar A1 as relatively drought tolerant. To identify the drought responsive genes, we have constructed a stress subtracted cDNA library from cultivar A1 following subtractive hybridization. Analysis of similar to 1,300 cDNA clones resulted in the identification of 667 unique drought responsive ESTs. Protein homology search revealed that 521 (78 %) out of 667 ESTs showed significant similarity to known sequences in the database and majority of them previously identified as drought stress-related genes and were found to be involved in a variety of cellular functions ranging from stress perception to cellular protection. Remaining 146 (22 %) ESTs were not homologous to known sequences in the database and therefore, they were considered to be unique and novel drought responsive genes of safflower. Since safflower is a stress-adapted oil-seed crop this observation has great relevance. In addition, to validate the differential expression of the identified genes, expression profiles of selected clones were analyzed using dot blot (reverse northern), and northern blot analysis. We showed that these clones were differentially expressed under different abiotic stress conditions. The implications of the analyzed genes in abiotic stress tolerance are discussed in our study.
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We introduce the defect sequence for a contractive tuple of Hilbert space operators and investigate its properties. The defect sequence is a sequence of numbers, called defect dimensions associated with a contractive tuple. We show that there are upper bounds for the defect dimensions. The tuples for which these upper bounds are obtained, are called maximal contractive tuples. The upper bounds are different in the non-commutative and in the commutative case. We show that the creation operators on the full Fock space and the coordinate multipliers on the Drury-Arveson space are maximal. We also study pure tuples and see how the defect dimensions play a role in their irreducibility. (C) 2012 Elsevier Inc. All rights reserved.
Resumo:
Background: Interaction of non-structural protein 5A (NS5A) of Hepatitis C virus (HCV) with human kinases namely, casein kinase 1 alpha (ck1 alpha) and protein kinase R (PKR) have different functional implications such as regulation of viral replication and evasion of interferon induced immune response respectively. Understanding the structural and molecular basis of interactions of the viral protein with two different human kinases can be useful in developing strategies for treatment against HCV. Results: Serine 232 of NS5A is known to be phosphorylated by human ck1 alpha. A structural model of NS5A peptide containing phosphoacceptor residue Serine 232 bound to ck1 alpha has been generated using the known 3-D structures of kinase-peptide complexes. The substrate interacting residues in ck1 alpha has been identified from the model and these are found to be conserved well in the ck1 family. ck1 alpha - substrate peptide complex has also been used to understand the structural basis of association between ck1 alpha and its other viral stress induced substrate, tumour suppressor p53 transactivation domain which has a crystal structure available. Interaction of NS5A with another human kinase PKR is primarily genotype specific. NS5A from genotype 1b has been shown to interact and inhibit PKR whereas NS5A from genotype 2a/3a are unable to bind and inhibit PKR efficiently. This is one of the main reasons for the varied response to interferon therapy in HCV patients across different genotypes. Using PKR crystal structure, sequence alignment and evolutionary trace analysis some of the critical residues responsible for the interaction of NS5A 1b with PKR have been identified. Conclusions: The substrate interacting residues in ck1 alpha have been identified using the structural model of kinase substrate peptide. The PKR interacting NS5A 1b residues have also been predicted using PKR crystal structure, NS5A sequence analysis along with known experimental results. Functional significance and nature of interaction of interferon sensitivity determining region and variable region 3 of NS5A in different genotypes with PKR which was experimentally shown are also supported by the findings of evolutionary trace analysis. Designing inhibitors to prevent this interaction could enable the HCV genotype 1 infected patients respond well to interferon therapy.
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The Notch signalling pathway is implicated in a wide variety of cellular processes throughout metazoan development. Although the downstream mechanism of Notch signalling has been extensively studied, the details of its ligand-mediated receptor activation are not clearly understood. Although the role of Notch ELRs EGF (epidermal growth factor)-like-repeats] 11-12 in ligand binding is known, recent studies have suggested interactions within different ELRs of the Notch receptor whose significance remains to be understood. Here, we report critical inter-domain interactions between human Notch1 ELRs 21-30 and the ELRs 11-15 that are modulated by calcium. Surface plasmon resonance analysis revealed that the interaction between ELRs 21-30 and ELRs 11-15 is similar to 10-fold stronger than that between ELRs 11-15 and the ligands. Although there was no interaction between Notch 1 ELRs 21-30 and the ligands in vitro, addition of pre-clustered Jagged1Fc resulted in the dissociation of the preformed complex between ELRs 21-30 and 11-15, suggesting that inter-domain interactions compete for ligand binding. Furthermore, the antibodies against ELRs 21-30 inhibited ligand binding to the full-length Notch1 and subsequent receptor activation, with the antibodies against ELRs 25-26 being the most effective. These results suggest that the ELRs 25-26 represent a cryptic ligand-binding site which becomes exposed only upon the presence of the ligand. Thus, using specific antibodies against various domains of the Notch1 receptor, we demonstrate that, although ELRs 11-12 are the principal ligand-binding site, the ELRs 25-26 serve as a secondary binding site and play an important role in receptor activation.
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We report spontaneous translocation of small interfering RNA (siRNA) inside carbon nanotubes (CNTs) of various diameters and chirality using all atom molecular dynamics simulations with explicit solvent. We use umbrella sampling method to calculate the free energy landscape of the siRNA entry and translocation event. Free energy profiles show that siRNA gains free energy while translocating inside CNT, and barrier for siRNA exit from CNT ranges from 40 to 110 kcal/mol depending on CNT chirality and salt concentration. The translocation time tau decreases with the increase of CNT diameter with a critical diameter of 24 angstrom for the translocation. In contrast, double strand DNA of the same sequence does not translocate inside CNT due to large free energy barrier for the translocation. This study helps in understanding the nucleic acid transport through nanopores at microscopic level and may help designing carbon nanotube based sensor for siRNA. (C) 2013 American Institute of Physics. http://dx.doi.org/10.1063/1.4773302]
Resumo:
Online remote visualization and steering of critical weather applications like cyclone tracking are essential for effective and timely analysis by geographically distributed climate science community. A steering framework for controlling the high-performance simulations of critical weather events needs to take into account both the steering inputs of the scientists and the criticality needs of the application including minimum progress rate of simulations and continuous visualization of significant events. In this work, we have developed an integrated user-driven and automated steering framework InSt for simulations, online remote visualization, and analysis for critical weather applications. InSt provides the user control over various application parameters including region of interest, resolution of simulation, and frequency of data for visualization. Unlike existing efforts, our framework considers both the steering inputs and the criticality of the application, namely, the minimum progress rate needed for the application, and various resource constraints including storage space and network bandwidth to decide the best possible parameter values for simulations and visualization.
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The paper identified and characterized a special multi-degree of freedom toggle behavior, called double toggle, observed in a typical MCCB switching mechanism. For an idealized system, the condition of toggle sequence is derived geometrically. The existing tools available in a multi-body dynamics package are used for exploring the dynamic behavior of such systems parametrically. The double toggle mechanism is found to make the system insensitive to the operator's behavior; however, the system is vulnerable under extreme usage. The linkage kinematics and stopper locations are found to have dominant role on the behavior of the system. It is revealed that the operating time is immune to the inertial property of the input link and sensitive to that of the output link. Novel designs exploiting this observation, in terms of spring and toggle placements, to enhance switching performance have also been reported in the paper. Detailed study revealed that strategic placement of the spring helps in selective alteration of system performance. Thus, the study establishes the critical importance of the kinematic design of MCCB over the dynamic parameters. (C) 2013 Elsevier Ltd. All rights reserved.
Resumo:
For most fluids, there exist a maximum and a minimum in the curvature of the reduced vapor pressure curve, p(r) = p(r)(T-r) (with p(r) = p/p(c) and T-r = T/T-c, p(c) and T-c being the pressure and temperature at the critical point). By analyzing National Institute of Standards and Technology (NIST) data on the liquid-vapor coexistence curve for 105 fluids, we find that the maximum occurs in the reduced temperature range 0.5 <= T-r <= 0.8 while the minimum occurs in the reduced temperature range 0.980 <= T-r <= 0.995. Vapor pressure equations for which d(2)p(r)/dT(r)(2) diverges at the critical point present a minimum in their curvature. Therefore, the point of minimum curvature can be used as a marker for the critical region. By using the well-known Ambrose-Walton (AW) vapor pressure equation we obtain the reduced temperatures of the maximum and minimum curvature in terms of the Pitzer acentric factor. The AW predictions are checked against those obtained from NIST data. (C) 2013 Elsevier Ltd. All rights reserved.
Resumo:
Background: Development of sensitive sequence search procedures for the detection of distant relationships between proteins at superfamily/fold level is still a big challenge. The intermediate sequence search approach is the most frequently employed manner of identifying remote homologues effectively. In this study, examination of serine proteases of prolyl oligopeptidase, rhomboid and subtilisin protein families were carried out using plant serine proteases as queries from two genomes including A. thaliana and O. sativa and 13 other families of unrelated folds to identify the distant homologues which could not be obtained using PSI-BLAST. Methodology/Principal Findings: We have proposed to start with multiple queries of classical serine protease members to identify remote homologues in families, using a rigorous approach like Cascade PSI-BLAST. We found that classical sequence based approaches, like PSI-BLAST, showed very low sequence coverage in identifying plant serine proteases. The algorithm was applied on enriched sequence database of homologous domains and we obtained overall average coverage of 88% at family, 77% at superfamily or fold level along with specificity of similar to 100% and Mathew's correlation coefficient of 0.91. Similar approach was also implemented on 13 other protein families representing every structural class in SCOP database. Further investigation with statistical tests, like jackknifing, helped us to better understand the influence of neighbouring protein families. Conclusions/Significance: Our study suggests that employment of multiple queries of a family for the Cascade PSI-BLAST searches is useful for predicting distant relationships effectively even at superfamily level. We have proposed a generalized strategy to cover all the distant members of a particular family using multiple query sequences. Our findings reveal that prior selection of sequences as query and the presence of neighbouring families can be important for covering the search space effectively in minimal computational time. This study also provides an understanding of the `bridging' role of related families.