904 resultados para Drug discovery


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A series of simple quinoline-chalcone conjugates have been synthesized by Claisen-Schmidt condensation reactions of substituted acetophenones with 2-chloro-3-formyl-quinoline and evaluated for their nucleolytic activity. The structures of the synthesized quinoline-chalcone conjugates were confirmed by IR, H-1 NMR, C-13 NMR and mass spectral analyses. Most of the prepared compounds showed significant DNA binding and photocleavage activities. The incorporation of an electron-donating group into ring A caused a moderate increase in the DNA binding and photocleavage activities. Compounds 3c and 3d exhibited promising DNA photocleavage against pUC 19 DNA with 85% inhibition at 100 mu M concentration. A structure-activity relationship analysis of these compounds was performed; compounds 3c and 3d are potential candidates for future drug discovery and development.

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Rich data bearing on the structural and evolutionary principles of protein protein interactions are paving the way to a better understanding of the regulation of function in the cell. This is particularly the case when these interactions are considered in the framework of key pathways. Knowledge of the interactions may provide insights into the mechanisms of crucial `driver' mutations in oncogenesis. They also provide the foundation toward the design of protein protein interfaces and inhibitors that can abrogate their formation or enhance them. The main features to learn from known 3-D structures of protein protein complexes and the extensive literature which analyzes them computationally and experimentally include the interaction details which permit undertaking structure-based drug discovery, the evolution of complexes and their interactions, the consequences of alterations such as post-translational modifications, ligand binding, disease causing mutations, host pathogen interactions, oligomerization, aggregation and the roles of disorder, dynamics, allostery and more to the protein and the cell. This review highlights some of the recent advances in these areas, including design, inhibition and prediction of protein protein complexes. The field is broad, and much work has been carried out in these areas, making it challenging to cover it in its entirety. Much of this is due to the fast increase in the number of molecules whose structures have been determined experimentally and the vast increase in computational power. Here we provide a concise overview. (C) 2014 Elsevier Ltd. All rights reserved.

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The understanding of protein-protein interactions is indispensable in comprehending most of the biological processes in a cell. Small-scale experiments as well as large-scale high-throughput techniques over the past few decades have facilitated identification and analysis of protein-protein interactions which form the basis of much of our knowledge on functional and regulatory aspects of proteins. However, such rich catalog of interaction data should be used with caution when establishing protein-protein interactions in silico, as the high-throughput datasets are prone to false positives. Numerous computational means developed to pursue genome-wide studies on protein-protein interactions at times overlook the mechanistic and molecular details, thus questioning the reliability of predicted protein-protein interactions. We review the development, advantages, and shortcomings of varied approaches and demonstrate that by providing a structural viewpoint in terms of shape complementarity and interaction energies at protein-protein interfaces coupled with information on expression and localization of proteins homologous to an interacting pair, it is possible to assess the credibility of predicted interactions in biological context. With a focus on human pathogen Mycobacterium tuberculosis H37Rv, we show that such scrupulous use of details at the molecular level can predict physicochemically viable protein-protein interactions across host and pathogen. Such predicted interactions have the potential to provide molecular basis of probable mechanisms of pathogenesis and hence open up ways to explore their usefulness as targets in the light of drug discovery. (c) 2014 IUBMB Life, 66(11):759-774, 2014

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A critical unmet need for treatment of drug-resistant tuberculosis (TB) is to find novel therapies that are efficacious, safe, and shorten the duration of treatment. Drug discovery approaches for TB primarily target essential genes of the pathogen Mycobacterium tuberculosis (Mtb) but novel strategies such as host-directed therapies and nonmicrobicidal targets are necessary to bring about a paradigm shift in treatment. Drugs targeting the host pathways and nonmicrobicidal proteins can be used only in conjunction with existing drugs as adjunct therapies. Significantly, host-directed adjunct therapies have the potential to decrease duration of treatment, as they are less prone to drug resistance, target the immune responses, and act via novel mechanism of action. Recent advances in targeting host-pathogen interactions have implicated pathways such as eicosanoid regulation and angiogenesis. Furthermore, several approved drugs such as metformin and verapamil have been identified that appear suitable for repurposing for the treatment of TB. These findings and the challenges in the area of host- and/or pathogen-directed adjunct therapies and their implications for TB therapy are discussed.

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Since the dawn of civilization, natural resources have remained the mainstay of various remedial approaches of humans vis-a-vis a large number of illnesses. Saraca asoca (Roxb.) de Wilde (Saraca indica L.) belonging to the family Caesalpiniaceae has been regarded as a universal panacea in old Indian Ayurvedic texts and has especially been used to manage gynaecological complications and infections besides treating haemmorhagic dysentery, uterine pain, bacterial infections, skin problems, tumours, worm infestations, cardiac and circulatory problems. Almost all parts of the plant are considered pharmacologically valuable. Extensive folkloric practices and ethnobotanical applications of this plant have even lead to the availability of several commercial S. asoca formulations recommended for different indications though adulteration of these remains a pressing concern. Though a wealth of knowledge on this plant is available in both the classical and modern literature, extensive research on its phytomedicinal worth using state-of-the-art tools and methodologies is lacking. Recent reports on bioprospecting of S. asoca endophytic fungi for industrial bioproducts and useful pharmacologically relevant metabolites provide a silver lining to uncover single molecular bio-effectors from its endophytes. Here, we describe socio-ethnobotanical usage, present the current pharmacological status and discuss potential bottlenecks in harnessing the proclaimed phytomedicinal worth of this prescribed Ayurvedic medicinal plant. Finally, we also look into the possible future of the drug discovery and pharmaceutical R&D efforts directed at exploring its pharma legacy.

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Development of effective therapies to eradicate persistent, slowly replicating M. tuberculosis (Mtb) represents a significant challenge to controlling the global TB epidemic. To develop such therapies, it is imperative to translate information from metabolome and proteome adaptations of persistent Mtb into the drug discovery screening platforms. To this end, reductive sulfur metabolism is genetically and pharmacologically implicated in survival, pathogenesis, and redox homeostasis of persistent Mtb. Therefore, inhibitors of this pathway are expected to serve as powerful tools in its preclinical and clinical validation as a therapeutic target for eradicating persisters. Here, we establish a first functional HTS platform for identification of APS reductase (APSR) inhibitors, a critical enzyme in the assimilation of sulfate for the biosynthesis of cysteine and other essential sulfur-containing molecules. Our HTS campaign involving 38?350 compounds led to the discovery of three distinct structural classes of APSR inhibitors. A class of bioactive compounds with known pharmacology displayed potent bactericidal activity in wild-type Mtb as well as MDR and XDR clinical isolates. Top compounds showed markedly diminished potency in a conditional Delta APSR mutant, which could be restored by complementation with Mtb APSR. Furthermore, ITC studies on representative compounds provided evidence for direct engagement of the APSR target. Finally, potent APSR inhibitors significantly decreased the cellular levels of key reduced sulfur-containing metabolites and also induced an oxidative shift in mycothiol redox potential of live Mtb, thus providing functional validation of our screening data. In summary, we have identified first-in-class inhibitors of APSR that can serve as molecular probes in unraveling the links between Mtb persistence, antibiotic tolerance, and sulfate assimilation, in addition to their potential therapeutic value.

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Quantum computing offers powerful new techniques for speeding up the calculation of many classically intractable problems. Quantum algorithms can allow for the efficient simulation of physical systems, with applications to basic research, chemical modeling, and drug discovery; other algorithms have important implications for cryptography and internet security.

At the same time, building a quantum computer is a daunting task, requiring the coherent manipulation of systems with many quantum degrees of freedom while preventing environmental noise from interacting too strongly with the system. Fortunately, we know that, under reasonable assumptions, we can use the techniques of quantum error correction and fault tolerance to achieve an arbitrary reduction in the noise level.

In this thesis, we look at how additional information about the structure of noise, or "noise bias," can improve or alter the performance of techniques in quantum error correction and fault tolerance. In Chapter 2, we explore the possibility of designing certain quantum gates to be extremely robust with respect to errors in their operation. This naturally leads to structured noise where certain gates can be implemented in a protected manner, allowing the user to focus their protection on the noisier unprotected operations.

In Chapter 3, we examine how to tailor error-correcting codes and fault-tolerant quantum circuits in the presence of dephasing biased noise, where dephasing errors are far more common than bit-flip errors. By using an appropriately asymmetric code, we demonstrate the ability to improve the amount of error reduction and decrease the physical resources required for error correction.

In Chapter 4, we analyze a variety of protocols for distilling magic states, which enable universal quantum computation, in the presence of faulty Clifford operations. Here again there is a hierarchy of noise levels, with a fixed error rate for faulty gates, and a second rate for errors in the distilled states which decreases as the states are distilled to better quality. The interplay of of these different rates sets limits on the achievable distillation and how quickly states converge to that limit.

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Background: Excessive apoptosis induces unwanted cell death and promotes pathological conditions. Drug discovery efforts aimed at decreasing apoptotic damage initially targeted the inhibition of effector caspases. Although such inhibitors were effective, safety problems led to slow pharmacological development. Therefore, apoptosis inhibition is still considered an unmet medical need. Methodology and Principal Findings: The interaction between Apaf-1 and the inhibitors was confirmed by NMR. Target specificity was evaluated in cellular models by siRNa based approaches. Cell recovery was confirmed by MTT, clonogenicity and flow cytometry assays. The efficiency of the compounds as antiapoptotic agents was tested in cellular and in vivo models of protection upon cisplatin induced ototoxicity in a zebrafish model and from hypoxia and reperfusion kidney damage in a rat model of hot ischemia. Conclusions: Apaf-1 inhibitors decreased Cytc release and apoptosome-mediated activation of procaspase-9 preventing cell and tissue damage in ex vivo experiments and in vivo animal models of apoptotic damage. Our results provide evidence that Apaf-1 pharmacological inhibition has therapeutic potential for the treatment of apoptosis-related diseases.

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In a multi-target complex network, the links (L-ij) represent the interactions between the drug (d(i)) and the target (t(j)), characterized by different experimental measures (K-i, K-m, IC50, etc.) obtained in pharmacological assays under diverse boundary conditions (c(j)). In this work, we handle Shannon entropy measures for developing a model encompassing a multi-target network of neuroprotective/neurotoxic compounds reported in the CHEMBL database. The model predicts correctly >8300 experimental outcomes with Accuracy, Specificity, and Sensitivity above 80%-90% on training and external validation series. Indeed, the model can calculate different outcomes for >30 experimental measures in >400 different experimental protocolsin relation with >150 molecular and cellular targets on 11 different organisms (including human). Hereafter, we reported by the first time the synthesis, characterization, and experimental assays of a new series of chiral 1,2-rasagiline carbamate derivatives not reported in previous works. The experimental tests included: (1) assay in absence of neurotoxic agents; (2) in the presence of glutamate; and (3) in the presence of H2O2. Lastly, we used the new Assessing Links with Moving Averages (ALMA)-entropy model to predict possible outcomes for the new compounds in a high number of pharmacological tests not carried out experimentally.

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Over the past decade, electrical detection of chemical and biological species using novel nanostructure-based devices has attracted significant attention for chemical, genomics, biomedical diagnostics, and drug discovery applications. The use of nanostructured devices in chemical/biological sensors in place of conventional sensing technologies has advantages of high sensitivity, low decreased energy consumption and potentially highly miniaturized integration. Owing to their particular structure, excellent electrical properties and high chemical stability, carbon nanotube and graphene based electrical devices have been widely developed for high performance label-free chemical/biological sensors. Here, we review the latest developments of carbon nanostructure-based transistor sensors in ultrasensitive detection of chemical/biological entities, such as poisonous gases, nucleic acids, proteins and cells.

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Marine sponges (Porifera) possess an extraordinary diversity of bioactive metabolites for new drug discovery and development. In vitro cultivation of sponge cells in a bioreactor system is very attractive for the sustainable production of sponge-derived bioactive metabolites; however, it is still a challenging task. The recent establishment of sponge primmorphs, multicellular aggregates from dissociated mixed-cell population (MCP), has been widely acknowledged to hold great promise for cultivation in vitro. Here we present a new method to establish an in vitro sponge primmorph culture from archaeocyte-dominant cell population (ADCP) enriched by a Ficoll gradient, rather than a mixed-cell population (MCP). Our rationale is based upon the totipotency (the ability of a cell to differentiate into other cell types) of archaeocyte cells and the different biological functions of various sponge cell types. A sponge, Hymeniacidon perleve collected from the China Yellow Sea was used as a model system for this investigation. Distinct dynamics of primmorph formation were observed while significant increases in DNA synthesis, cell proliferation (up to threefold), and cell growth (up to fourfold) were achieved. Furthermore, a time-dependent spiculogenesis was clearly demonstrated in our longterm culture, indicating high metabolic activity of primmorphs from the ADCP. This new method represents an important step forward to advance sponge cell culture in vitro that may lead to commercial exploitation of sponge-derived drugs. (C) 2003 Wiley Periodicals, Inc.

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Electrospray ionization mass spectrometry (ESI-MS) was used to investigate the binding of 13 alkaloids to two GC-rich DNA duplexes which are critical sequences in human survivin promoter. Negative ion ESI-MS was first applied to screen the binding of the alkaloids to the duplexes. Six alkaloids (including berberine, jatrorrhizine, palmatine, reserpine, berbamine, and tetrandrine) show complexation with the target DNA sequences. Relative binding affinities were estimated from the negative ion ESI data, and the alkaloids show a binding preference to the duplex with higher GC content. Positive ion ESI mass spectra of the complexes were also recorded and compared with those obtained in negative ion mode.

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We study the kinetics of the biomolecular binding process at the interface using energy landscape theory. The global kinetic connectivity case is considered for a downhill funneled energy landscape. By solving the kinetic master equation, the kinetic time for binding is obtained and shown to have a U-shape curve-dependence on the temperature. The kinetic minimum of the binding time monotonically decreases when the ratio of the underlying energy gap between native state and average non-native states versus the roughness or the fluctuations of the landscape increases. At intermediate temperatures,fluctuations measured by the higher moments of the binding time lead to non-Poissonian, non-exponential kinetics. At both high and very low temperatures, the kinetics is nearly Poissonian and exponential.