28 resultados para DRUG-RESISTANCE

em Indian Institute of Science - Bangalore - Índia


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Using computer modeling of three-dimensional structures and structural information available on the crystal structures of HIV-1 protease, we investigated the structural effects of mutations, in treatment-naive and treatment-exposed individuals from India and postulated mechanisms of resistance in clade C variants. A large number of models (14) have been generated by computational mutation of the available crystal structures of drug bound proteases. Localized energy minimization was carried out in and around the sites of mutation in order to optimize the geometry of interactions present. Most of the mutations result in structural differences at the flap that favors the semiopen state of the enzyme. Some of the mutations were also found to confer resistance by affecting the geometry of the active site. The E35D mutation affects the flap structure in clade B strains and E35N and E35K mutation, seen in our modeled strains, have a more profound effect. Common polymorphisms at positions 36 and 63 in clade C also affected flap structure. Apart from a few other residues Gln-58, Asn-83, Asn-88, and Gln-92 and their interactions are important for the transition from the closed to the open state. Development of protease inhibitors by structure-based design requires investigation of mechanisms operative for clade C to improve the efficacy of therapy.

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Mycobacterial spheroplasts were prepared by treatment of the glycinesensitized cells with a combination of lipase and lysozyme. They were stable for several hours at room temperature but were lysed on treatment with 0.1% sodium dodecyl sulfate. The spheroplasts could be regenerated on a suitable medium. Fusion and regeneration of the spheroplasts were attempted using drug resistant mutant strains ofM. smegmalis. Recombinants were obtained from spheroplast fusion mediated by polyethylene glycol and dimethyl sulfoxide. Simultaneous expression of rccombinant properties was observed only after an initial lag in the isolated clones. This has been explained as due to “chromosome inactivation” in the fused product.

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Importance of the field: The shift in focus from ligand based design approaches to target based discovery over the last two to three decades has been a major milestone in drug discovery research. Currently, it is witnessing another major paradigm shift by leaning towards the holistic systems based approaches rather the reductionist single molecule based methods. The effect of this new trend is likely to be felt strongly in terms of new strategies for therapeutic intervention, new targets individually and in combinations, and design of specific and safer drugs. Computational modeling and simulation form important constituents of new-age biology because they are essential to comprehend the large-scale data generated by high-throughput experiments and to generate hypotheses, which are typically iterated with experimental validation. Areas covered in this review: This review focuses on the repertoire of systems-level computational approaches currently available for target identification. The review starts with a discussion on levels of abstraction of biological systems and describes different modeling methodologies that are available for this purpose. The review then focuses on how such modeling and simulations can be applied for drug target discovery. Finally, it discusses methods for studying other important issues such as understanding targetability, identifying target combinations and predicting drug resistance, and considering them during the target identification stage itself. What the reader will gain: The reader will get an account of the various approaches for target discovery and the need for systems approaches, followed by an overview of the different modeling and simulation approaches that have been developed. An idea of the promise and limitations of the various approaches and perspectives for future development will also be obtained. Take home message: Systems thinking has now come of age enabling a `bird's eye view' of the biological systems under study, at the same time allowing us to `zoom in', where necessary, for a detailed description of individual components. A number of different methods available for computational modeling and simulation of biological systems can be used effectively for drug target discovery.

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Development of multidrug resistance (MDR) is a major deterrent in the effective treatment of metastatic cancers by chemotherapy. Even though MDR and cancer invasiveness have been correlated, the molecular basis of this link remains obscure. We show here that treatment with chemotherapeutic drugs increases the expression of several ATP binding cassette transporters (ABC transporters) associated with MDR, as well as epithelial-mesenchymal transition (EMT) markers, selectively in invasive breast cancer cells, but not in immortalized or non-invasive cells. Interestingly, the mere induction of an EMT in immortalized and non-invasive cell lines increased their expression of ABC transporters, migration, invasion, and drug resistance. Conversely, reversal of EMT in invasive cells by downregulating EMT-inducing transcription factors reduced their expression of ABC transporters, invasion, and rendered them more chemosensitive. Mechanistically, we demonstrate that the promoters of ABC transporters carry several binding sites for EMT-inducing transcription factors, and overexpression of Twist, Snail, and FOXC2 increases the promoter activity of ABC transporters. Furthermore, chromatin immunoprecipitation studies revealed that Twist binds directly to the E-box elements of ABC transporters. Thus, our study identifies EMT inducers as novel regulators of ABC transporters, thereby providing molecular insights into the long-standing association between invasiveness and MDR. Targeting EMT transcription factors could hence serve as novel strategies to curb both metastasis and the associated drug resistance. Cell Death and Disease (2011) 2, e179; doi:10.1038/cddis.2011.61; published online 7 July 2011

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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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Introduction: Advances in genomics technologies are providing a very large amount of data on genome-wide gene expression profiles, protein molecules and their interactions with other macromolecules and metabolites. Molecular interaction networks provide a useful way to capture this complex data and comprehend it. Networks are beginning to be used in drug discovery, in many steps of the modern discovery pipeline, with large-scale molecular networks being particularly useful for the understanding of the molecular basis of the disease. Areas covered: The authors discuss network approaches used for drug target discovery and lead identification in the drug discovery pipeline. By reconstructing networks of targets, drugs and drug candidates as well as gene expression profiles under normal and disease conditions, the paper illustrates how it is possible to find relationships between different diseases, find biomarkers, explore drug repurposing and study emergence of drug resistance. Furthermore, the authors also look at networks which address particular important aspects such as off-target effects, combination-targets, mechanism of drug action and drug safety. Expert opinion: The network approach represents another paradigm shift in drug discovery science. A network approach provides a fresh perspective of understanding important proteins in the context of their cellular environments, providing a rational basis for deriving useful strategies in drug design. Besides drug target identification and inferring mechanism of action, networks enable us to address new ideas that could prove to be extremely useful for new drug discovery, such as drug repositioning, drug synergy, polypharmacology and personalized medicine.

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The scenario of tuberculosis has gone deadly due to its high prevalence and emergence of widespread drug resistance. It is now high time to develop novel antimycobacterial strategies and to understand novel mechanisms of existing antimycobacterial compounds so that we are equipped with newer tuberculosis controlling molecules in the days to come. Iron has proven to be essential for pathogenesis of tuberculosis and retinoic acid is known to influence the iron metabolism pathway. Retenoic acid is also known to exhibit antitubercular effect in in vivo system. Therefore there is every possibility that retinoic acid by affecting the iron metabolism pathway exhibits its antimycobacterial effect. These aspects are reviewed in the present manuscript for understanding the antimycobacterial role of retinoic acid in the context of iron metabolism and other immunological aspects.

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Recent reports suggest the existence of a subpopulation of stem-like cancer cells, termed as cancer stem cells (CSCs), which bear functional and phenotypic resemblance with the adult, tissue-resident stem cells. Side population (SP) assay based on differential efflux of Hoechst 33342 has been effectively used for the isolation of CSCs. The drug resistance properties of SP cells are typically due to the increased expression of ABC transporters leading to drug efflux. Conventionally used chemotherapeutic drugs may often leads to an enrichment of SP, revealing their inability to target the drug-resistant SP and CSCs. Thus, identification of agents that can reduce the SP phenotype is currently in vogue in cancer therapeutics. Withania somnifera (WS) and Tinospora cordifolia (TC) have been used in Ayurveda for treating various diseases, including cancer. In the current study, we have investigated the effects of ethanolic (ET) extracts of WS and TC on the cancer SP phenotype. Interestingly, we found significant decrease in SP on treatment with TC-ET, but not with WS-ET. The SP-inhibitory TC-ET was further fractionated into petroleum ether (TC-PET), dichloromethane (TC-DCM), and n-butyl alcohol (TC-nBT) fractions using bioactivity-guided fractionation. Our data revealed that TC-PET and TC-DCM, but not TC-nBT, significantly inhibited SP in a dose-dependent manner. Furthermore, flow cytometry-based functional assays revealed that TC-PET and TC-DCM significantly inhibited ABC-B1 and ABC-G2 transporters and sensitized cancer cells toward chemotherapeutic drug-mediated cytotoxicity. Thus, the TC-PET and TC-DCM may harbor phytochemicals with the potential to reverse the drug-resistant phenotype, thus improving the efficacy of cancer chemotherapy.

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The present study focuses prudent elucidation of microbial pollution and antibiotic sensitivity profiling of the fecal coliforms isolated from River Cauvery, a major drinking water source in Karnataka, India. Water samples were collected from ten hotspots during the year 2011-2012. The physiochemical characteristics and microbial count of water samples collected from most of the hotspots exhibited greater biological oxygen demand and bacterial count especially coliforms in comparison with control samples (p <= 0.01). The antibiotic sensitivity testing was performed using 48 antibiotics against the bacterial isolates by disk-diffusion assay. The current study showed that out of 848 bacterial isolates, 93.51 % (n=793) of the isolates were found to be multidrug-resistant to most of the current generation antibiotics. Among the major isolates, 96.46 % (n=273) of the isolates were found to be multidrug-resistant to 30 antibiotics and they were identified to be Escherichia coli by 16S rDNA gene sequencing. Similarly, 93.85 % (n=107), 94.49 % (n=103), and 90.22 % (n=157) of the isolates exhibited multiple drug resistance to 32, 40, and 37 antibiotics, and they were identified to be Enterobacter cloacae, Pseudomonas trivialis, and Shigella sonnei, respectively. The molecular studies suggested the prevalence of blaTEM genes in all the four isolates and dhfr gene in Escherichia coli and Sh. sonnei. Analogously, most of the other Gram-negative bacteria were found to be multidrug-resistant and the Gram-positive bacteria, Staphylococcus spp. isolated from the water samples were found to be methicillin and vancomycin-resistant Staphylococcus aureus. This is probably the first study elucidating the bacterial pollution and antibiotic sensitivity profiling of fecal coliforms isolated from River Cauvery, Karnataka, India.

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Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

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Elicitation of drug resistance and various survival strategies inside host macrophages have been the hallmarks of Mycobacterium tuberculosis as a successful pathogen. ATP Binding Cassette (ABC) transporter type proteins are known to be involved in the efflux of drugs in bacterial and mammalian systems. FtsE, an ABC transporter type protein, in association with the integral membrane protein FtsX, is involved in the assembly of potassium ion transport proteins and probably of cell division proteins as well, both of which being relevant to tubercle bacillus. In this study, we cloned ftsE gene of M. tuberculosis, overexpressed and purified. The recombinant MtFtsE-6xHis protein and the native MtFtsE protein were found localized on the membrane of E. coli and M. tuberculosis cells, respectively. MtFtsE-6xHis protein showed ATP binding in vitro, for which the K42 residue in the Walker A motif was found essential. While MtFtsE-6xHis protein could partially complement growth defect of E. coli ftsE temperature-sensitive strain MFT1181, co-expression of MtFtsE and MtFtsX efficiently complemented the growth defect, indicating that the MtFtsE and MtFtsX proteins might be performing an associated function. MtFtsE and MtFtsX-6xHis proteins were found to exist as a complex on the membrane of E. coli cells co-expressing the two proteins.

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Background & objectives: The multiple drug resistance (MDR) is a serious health problem and major challenge to the global drug discovery programmes. Most of the genetic determinants that confer resistance to antibiotics are located on R-plasmids in bacteria. The present investigation was undertaken to investigate the ability of organic extract of the fruits of Helicteres isora to cure R-plasmids from certain clinical isolates. mMethods: Active fractions demonstrating antibacterial and antiplasmid activities were isolated from the acetone extracts of shade dried fruits of H. isora by bioassay guided fractionation. Minimal inhibitory concentration (MIC) of antibiotics and organic extracts was determined by agar dilution method. Plasmid curing activity of organic fractions was determined by evaluating the ability of bacterial colonies (pre treated with organic fraction for 18 h) to grow in the presence of antibiotics. The physical loss of plasmid DNA in the cured derivatives was further confirmed by agarose gel electrophoresis. Results: The active fraction did not inhibit the growth of either the clinical isolates or the strains harbouring reference plasmids even at a concentration of 400 mu g/ml. However, the same fraction could cure plasmids from Enterococcus faecalis, Escherichia coli, Bacillus cereus and E. coli (RP4) at curing efficiencies of 14, 26, 22 and 2 per cent respectively. The active fraction mediated plasmid curing resulted in the subsequent loss of antibiotic resistance encoded in the plasmids as revealed by antibiotic resistance profile of cured strains. The physical loss of plasmid was also confirmed by agarose gel electrophoresis. Interpretation & conclusions: The active fraction of acetone extract of H. isora fruits cured R-plasmids from Gram-positive and Gram-negative clinical isolates as well as reference strains. Such plasmid loss reversed the multiple antibiotic resistance in cured derivatives making them sensitive to low concentrations of antibiotics. Acetone fractions of H. isora may be a source to develop antiplasmid agents of natural origin to contain the development and spread of plasmid borne multiple antibiotic resistance.

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A human primary lung carcinoma cell line (HPL-R1) established from the tumor biopsy of a lung cancer patient, lacking in cytochrome P1-450 [aryl hydrocarbon (benzo[a]pyrene) hydroxylase (AHH)], was cloned and used to obtain variants deficient in the expression of thymidine-kinase via treatment with 5-bromo-2'-deoxyuridine, and selection for drug resistance phenotype. The variant cell line, precharacterized for thymidine kinase negative phenotype, was transfected with the thymidine kinase gene bearing p R-tk and px1-tk plasmids. Transfections from both the plasmids, demonstrated a frequency of 5.5 X 10(-5). The transfectants showed a 76-100% retention of the transferred phenotype. These data suggest that transfection in variant human cells can approach significant levels of stability observed with rodent cell recipients.

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Nevirapine forms the mainstay of our efforts to curtail the pediatric AIDS epidemic through prevention of mother-to-child transmission of HIV-1. A key limitation, however, is the rapid selection of HIV-1 strains resistant to nevirapine following the administration of a single dose. This rapid selection of resistance suggests that nevirapine-resistant strains preexist in HIV-1 patients and may adversely affect outcomes of treatment. The frequencies of nevirapine-resistant strains in vivo, however, remain poorly estimated, possibly because they exist as a minority below current assay detection limits. Here, we employ stochastic simulations and a mathematical model to estimate the frequencies of strains carrying different combinations of the common nevirapine resistance mutations K103N, V106A, Y181C, Y188C, and G190A in chronically infected HIV-1 patients naive to nevirapine. We estimate the relative fitness of mutant strains from an independent analysis of previous competitive growth assays. We predict that single mutants are likely to preexist in patients at frequencies (similar to 0.01% to 0.001%) near or below current assay detection limits (>0.01%), emphasizing the need for more-sensitive assays. The existence of double mutants is subject to large stochastic variations. Triple and higher mutants are predicted not to exist. Our estimates are robust to variations in the recombination rate, cellular superinfection frequency, and the effective population size. Thus, with 10(7) to 10(8) infected cells in HIV-1 patients, even when undetected, nevirapine-resistant genomes may exist in substantial numbers and compromise efforts to prevent mother-to-child transmission of HIV-1, accelerate the failure of subsequent antiretroviral treatments, and facilitate the transmission of drug resistance.