Rationalization and prediction of drug resistant mutations in targets for clinical anti-tubercular drugs

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.

Influence of Side-Chain on Structural Order and Photophysical Properties in Thiophene Based Diketopyrrolopyrroles: A Systematic Study

In this work, we have synthesized a series of TDPP derivatives with different alkyl groups such as n-hexyl (-C6H13) 3a, 2-ethylhexyl (-(2-C2H5)C6H12) 3b, triethylene glycol mono methyl ether (-(CH2CH2O)(3c)H-3, TEG) 3c, and octadodecyl (-(8-C8H17)C12H22) 3d. N,N dialkylation of Othiophene-diketopyrrolopyrrole (TDPP, 1) strongly influences its solubility, solid state packing, and structural order. These materials allow us to explicitly study the influence of alkyl chain on solid state packing and photophysical properties. TDPP moiety containing two different alkyl groups 3e (TEG and 2-ethylhexyl) and 3f (TEG and n-hexyl) were synthesized for the first time. The absorption spectra of all derivatives exhibited a red shift in solid state when compared to their solution spectra. The type of alkyl chains leads to change in the optical band gaps in solid state. The fluorescence study reveals that TDPP derivatives have strong pi-pi interaction in the solid state and the extent of bathochromic shift is due to combination of intramolecular interaction and formation of aggregates in solid state. This behavior strongly depends on the nature of alkyl chain. The presence of strong C-H center dot center dot center dot O inter chain interactions and CH-pi interactions in solid state exhibits strong influence on the photophysical properties of TDPP chromophore.

Methodology for Pavement Design Reliability and Back Analysis Using Markov Chain Monte Carlo Simulation

Given the increasing cost of designing and building new highway pavements, reliability analysis has become vital to ensure that a given pavement performs as expected in the field. Recognizing the importance of failure analysis to safety, reliability, performance, and economy, back analysis has been employed in various engineering applications to evaluate the inherent uncertainties of the design and analysis. The probabilistic back analysis method formulated on Bayes' theorem and solved using the Markov chain Monte Carlo simulation method with a Metropolis-Hastings algorithm has proved to be highly efficient to address this issue. It is also quite flexible and is applicable to any type of prior information. In this paper, this method has been used to back-analyze the parameters that influence the pavement life and to consider the uncertainty of the mechanistic-empirical pavement design model. The load-induced pavement structural responses (e.g., stresses, strains, and deflections) used to predict the pavement life are estimated using the response surface methodology model developed based on the results of linear elastic analysis. The failure criteria adopted for the analysis were based on the factor of safety (FOS), and the study was carried out for different sample sizes and jumping distributions to estimate the most robust posterior statistics. From the posterior statistics of the case considered, it was observed that after approximately 150 million standard axle load repetitions, the mean values of the pavement properties decrease as expected, with a significant decrease in the values of the elastic moduli of the expected layers. An analysis of the posterior statistics indicated that the parameters that contribute significantly to the pavement failure were the moduli of the base and surface layer, which is consistent with the findings from other studies. After the back analysis, the base modulus parameters show a significant decrease of 15.8% and the surface layer modulus a decrease of 3.12% in the mean value. The usefulness of the back analysis methodology is further highlighted by estimating the design parameters for specified values of the factor of safety. The analysis revealed that for the pavement section considered, a reliability of 89% and 94% can be achieved by adopting FOS values of 1.5 and 2, respectively. The methodology proposed can therefore be effectively used to identify the parameters that are critical to pavement failure in the design of pavements for specified levels of reliability. DOI: 10.1061/(ASCE)TE.1943-5436.0000455. (C) 2013 American Society of Civil Engineers.

An estimate of equilibrium sensitivity of global terrestrial carbon cycle using NCAR CCSM4

Increasing concentrations of atmospheric CO2 influence climate, terrestrial biosphere productivity and ecosystem carbon storage through its radiative, physiological and fertilization effects. In this paper, we quantify these effects for a doubling of CO2 using a low resolution configuration of the coupled model NCAR CCSM4. In contrast to previous coupled climate-carbon modeling studies, we focus on the near-equilibrium response of the terrestrial carbon cycle. For a doubling of CO2, the radiative effect on the physical climate system causes global mean surface air temperature to increase by 2.14 K, whereas the physiological and fertilization on the land biosphere effects cause a warming of 0.22 K, suggesting that these later effects increase global warming by about 10 % as found in many recent studies. The CO2-fertilization leads to total ecosystem carbon gain of 371 Gt-C (28 %) while the radiative effect causes a loss of 131 Gt-C (10 %) indicating that climate warming damps the fertilization-induced carbon uptake over land. Our model-based estimate for the maximum potential terrestrial carbon uptake resulting from a doubling of atmospheric CO2 concentration (285-570 ppm) is only 242 Gt-C. This highlights the limited storage capacity of the terrestrial carbon reservoir. We also find that the terrestrial carbon storage sensitivity to changes in CO2 and temperature have been estimated to be lower in previous transient simulations because of lags in the climate-carbon system. Our model simulations indicate that the time scale of terrestrial carbon cycle response is greater than 500 years for CO2-fertilization and about 200 years for temperature perturbations. We also find that dynamic changes in vegetation amplify the terrestrial carbon storage sensitivity relative to a static vegetation case: because of changes in tree cover, changes in total ecosystem carbon for CO2-direct and climate effects are amplified by 88 and 72 %, respectively, in simulations with dynamic vegetation when compared to static vegetation simulations.

chain complex and quadrilaterals for normal surfaces

We interpret a normal surface in a (singular) three-manifold in terms of the homology of a chain complex. This allows us to study the relation between normal surfaces and their quadrilateral coordinates. Specifically, we give a proof of an (unpublished) observation independently given by Casson and Rubinstein saying that quadrilaterals determine a normal surface up to vertex linking spheres. We also characterize the quadrilateral coordinates that correspond to a normal surface in a (possibly ideal) triangulation.

The sequence and structure of snake gourd (Trichosanthes anguina) seed lectin, a three-chain nontoxic homologue of type II RIPs

The sequence and structure of snake gourd seed lectin (SGSL), a nontoxic homologue of type II ribosome-inactivating proteins (RIPs), have been determined by mass spectrometry and X-ray crystallography, respectively. As in type II RIPs, the molecule consists of a lectin chain made up of two beta-trefoil domains. The catalytic chain, which is connected through a disulfide bridge to the lectin chain in type II RIPs, is cleaved into two in SGSL. However, the integrity of the three-dimensional structure of the catalytic component of the molecule is preserved. This is the first time that a three-chain RIP or RIP homologue has been observed. A thorough examination of the sequence and structure of the protein and of its interactions with the bound methyl-alpha-galactose indicate that the nontoxicity of SGSL results from a combination of changes in the catalytic and the carbohydrate-binding sites. Detailed analyses of the sequences of type II RIPs of known structure and their homologues with unknown structure provide valuable insights into the evolution of this class of proteins. They also indicate some variability in carbohydrate-binding sites, which appears to contribute to the different levels of toxicity exhibited by lectins from various sources.

Splicing Functions and Global Dependency on Fission Yeast Slu7 Reveal Diversity in Spliceosome Assembly

The multiple short introns in Schizosaccharomyces pombe genes with degenerate cis sequences and atypically positioned polypyrimidine tracts make an interesting model to investigate canonical and alternative roles for conserved splicing factors. Here we report functions and interactions of the S. pombe slu7(+) (spslu7(+)) gene product, known from Saccharomyces cerevisiae and human in vitro reactions to assemble into spliceosomes after the first catalytic reaction and to dictate 3' splice site choice during the second reaction. By using a missense mutant of this essential S. pombe factor, we detected a range of global splicing derangements that were validated in assays for the splicing status of diverse candidate introns. We ascribe widespread, intron-specific SpSlu7 functions and have deduced several features, including the branch nucleotide-to-3' splice site distance, intron length, and the impact of its A/U content at the 5' end on the intron's dependence on SpSlu7. The data imply dynamic substrate-splicing factor relationships in multiintron transcripts. Interestingly, the unexpected early splicing arrest in spslu7-2 revealed a role before catalysis. We detected a salt-stable association with U5 snRNP and observed genetic interactions with spprp1(+), a homolog of human U5-102k factor. These observations together point to an altered recruitment and dependence on SpSlu7, suggesting its role in facilitating transitions that promote catalysis, and highlight the diversity in spliceosome assembly.