927 resultados para Drug discovery


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The enzyme dihydroorotate dehydrogenase (DHODH) has been suggested as a promising target for the design of trypanocidal agents. We report here the discovery of novel inhibitors of Trypanosoma cruzi DHODH identified by a combination of virtual screening and ITC methods. Monitoring of the enzymatic reaction in the presence of selected ligands together with structural information obtained from X-ray crystallography analysis have allowed the identification and validation of a novel site of interaction (S2 site). This has provided important structural insights for the rational design of T cruzi and Leishmania major DHODH inhibitors. The most potent compound (1) in the investigated series inhibits TcDHODH enzyme with K(i)(app) value of 19.28 mu M and possesses a ligand efficiency of 0.54 kcal mol(-1) per non-H atom. The compounds described in this work are promising hits for further development. (C) 2010 Elsevier Masson SAS. All rights reserved.

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The traditional drug discovery pipeline for the identification and development of compounds that selectively target specific molecules to ameliorate disease remains a major focus for medical research. However, the zebrafish is increasingly providing alternative strategies for various components of this pipeline. Zebrafish and their embryos are small, easily accessible and relatively low cost, making them applicable to high-throughput, small molecule screening. Zebrafish can also be manipulated by a range of forward and reverse genetics techniques to facilitate gene discovery and functional studies. Moreover, their physiological and developmental complexity provides accurate models of human disease to underpin mechanism of action and in vivo validation studies. Finally, several of these biological characteristics make zebrafish eminently suitable for toxicity testing, including eco-toxicology. Here we review the application of zebrafish to preclinical drug development and toxicity testing, including recent advances in mutant generation, drug screening and toxicology that serve to further enhance the capabilities of this valuable model organism in drug discovery.

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Drug discovery, development and registration is an expensive and time-consuming process associated with a high failure rate [Pessetto et al. (Mol Cancer Ther 12:1299-1309, 2013), Woodcock and Woosley (Annu Rev Med 59:1-12, 2008)]. Drug 'repurposing' is the identification of new therapeutic purposes for already approved drugs and is more affordable and achievable than novel drug discovery [Pessetto et al. (Mol Cancer Ther 12:1299-1309, 2013)]. Auranofin is a drug that is approved for the treatment of rheumatoid arthritis but is being investigated for potential therapeutic application in a number of other diseases including cancer, neurodegenerative disorders, HIV/AIDS, parasitic infections and bacterial infections [Tejman-Yarden et al. (Antimicrob Agents Chemother 57:2029-2035, 2013)]. The main mechanism of action of auranofin is through the inhibition of reduction/oxidation (redox) enzymes that are essential for maintaining intracellular levels of reactive oxygen species. Inhibition of these enzymes leads to cellular oxidative stress and intrinsic apoptosis [Pessetto et al. (Mol Cancer Ther 12:1299-1309, 2013), Fan et al. (Cell Death Dis 5:e1191, 2014), Fiskus et al. (Cancer Res 74:2520-2532, 2014), Marzano et al. (Free Radic Biol Med 42:872-881, 2007)]. Drugs such as auranofin that have already been approved for human use [Tejman-Yarden et al. (Antimicrob Agents Chemother 57:2029-2035, 2013)] can be brought into clinical use for other diseases relatively quickly and for a fraction of the cost of new drugs.

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The increase in incidence of infectious diseases worldwide, particularly in developing countries, is worrying. Each year, 14 million people are killed by infectious diseases, mainly HIV/AIDS, respiratory infections, malaria and tuberculosis. Despite the great burden in the poor countries, drug discovery to treat tropical diseases has come to a standstill. There is no interest by the pharmaceutical industry in drug development against the major diseases of the poor countries, since the financial return cannot be guaranteed. This has created an urgent need for new therapeutics to neglected diseases. A possible approach has been the exploitation of the inhibition of unique targets, vital to the pathogen such as the shikimate pathway enzymes, which are present in bacteria, fungi and apicomplexan parasites but are absent in mammals. The chorismate synthase (CS) catalyses the seventh step in this pathway, the conversion of 5-enolpyruvylshikimate-3-phosphate to chorismate. The strict requirement for a reduced flavin mononucleotide and the anti 1,4 elimination are both unusual aspects which make CS reaction unique among flavin-dependent enzymes, representing an important target for the chemotherapeutic agents development. In this review we present the main biochemical features of CS from bacterial and fungal sources and their difference from the apicomplexan CS. The CS mechanisms proposed are discussed and compared with structural data. The CS structures of some organisms are compared and their distinct features analyzed. Some known CS inhibitors are presented and the main characteristics are discussed. The structural and kinetics data reviewed here can be useful for the design of inhibitors. © 2007 Bentham Science Publishers Ltd.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Drug discovery has moved toward more rational strategies based on our increasing understanding of the fundamental principles of protein-ligand interactions. Structure( SBDD) and ligand-based drug design (LBDD) approaches bring together the most powerful concepts in modern chemistry and biology, linking medicinal chemistry with structural biology. The definition and assessment of both chemical and biological space have revitalized the importance of exploring the intrinsic complementary nature of experimental and computational methods in drug design. Major challenges in this field include the identification of promising hits and the development of high-quality leads for further development into clinical candidates. It becomes particularly important in the case of neglected tropical diseases (NTDs) that affect disproportionately poor people living in rural and remote regions worldwide, and for which there is an insufficient number of new chemical entities being evaluated owing to the lack of innovation and R&D investment by the pharmaceutical industry. This perspective paper outlines the utility and applications of SBDD and LBDD approaches for the identification and design of new small-molecule agents for NTDs.

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The structural peculiarities of a protein are related to its biological function. In the fatty acid elongation cycle, one small carrier protein shuttles and delivers the acyl intermediates from one enzyme to the other. The carrier has to recognize several enzymatic counterparts, specifically interact with each of them, and finally transiently deliver the carried substrate to the active site. Carry out such a complex game requires the players to be flexible and efficiently adapt their structure to the interacting protein or substrate. In a drug discovery effort, the structure-function relationships of a target system should be taken into account to optimistically interfere with its biological function. In this doctoral work, the essential role of structural plasticity in key steps of fatty acid biosynthesis in Plasmodium falciparum is investigated by means of molecular simulations. The key steps considered include the delivery of acyl substrates and the structural rearrangements of catalytic pockets upon ligand binding. The ground-level bases for carrier/enzyme recognition and interaction are also put forward. The structural features of the target have driven the selection of proper drug discovery tools, which captured the dynamics of biological processes and could allow the rational design of novel inhibitors. The model may be perspectively used for the identification of novel pathway-based antimalarial compounds.

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During the previous 10 years, global R&D expenditure in the pharmaceuticals and biotechnology sector has steadily increased, without a corresponding increase in output of new medicines. To address this situation, the biopharmaceutical industry's greatest need is to predict the failures at the earliest possible stage of the drug development process. A major key to reducing failures in drug screenings is the development and use of preclinical models that are more predictive of efficacy and safety in clinical trials. Further, relevant animal models are needed to allow a wider testing of novel hypotheses. Key to this is the developing, refining, and validating of complex animal models that directly link therapeutic targets to the phenotype of disease, allowing earlier prediction of human response to medicines and identification of safety biomarkers. Morehover, well-designed animal studies are essential to bridge the gap between test in cell cultures and people. Zebrafish is emerging, complementary to other models, as a powerful system for cancer studies and drugs discovery. We aim to investigate this research area designing a new preclinical cancer model based on the in vivo imaging of zebrafish embryogenesis. Technological advances in imaging have made it feasible to acquire nondestructive in vivo images of fluorescently labeled structures, such as cell nuclei and membranes, throughout early Zebrafishsh embryogenesis. This In vivo image-based investigation provides measurements for a large number of features at cellular level and events including nuclei movements, cells counting, and mitosis detection, thereby enabling the estimation of more significant parameters such as proliferation rate, highly relevant for investigating anticancer drug effects. In this work, we designed a standardized procedure for accessing drug activity at the cellular level in live zebrafish embryos. The procedure includes methodologies and tools that combine imaging and fully automated measurements of embryonic cell proliferation rate. We achieved proliferation rate estimation through the automatic classification and density measurement of epithelial enveloping layer and deep layer cells. Automatic embryonic cells classification provides the bases to measure the variability of relevant parameters, such as cell density, in different classes of cells and is finalized to the estimation of efficacy and selectivity of anticancer drugs. Through these methodologies we were able to evaluate and to measure in vivo the therapeutic potential and overall toxicity of Dbait and Irinotecan anticancer molecules. Results achieved on these anticancer molecules are presented and discussed; furthermore, extensive accuracy measurements are provided to investigate the robustness of the proposed procedure. Altogether, these observations indicate that zebrafish embryo can be a useful and cost-effective alternative to some mammalian models for the preclinical test of anticancer drugs and it might also provides, in the near future, opportunities to accelerate the process of drug discovery.

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In the past years, genome biology had disclosed an ever-growing kind of biological targets that emerged as ideal points for therapeutic intervention. Nevertheless, the number of new chemical entities (NCEs) translated into effective therapies employed in the clinic, still not observed. Innovative strategies in drug discovery combined with different approaches to drug design should be searched for bridge this gap. In this context organic synthetic chemistry had to provide for effective strategies to achieve biologically active small molecules to consider not only as potentially drug candidates, but also as chemical tools to dissect biological systems. In this scenario, during my PhD, inspired by the Biology-oriented Synthesis approach, a small library of hybrid molecules endowed with privileged scaffolds, able to block cell cycle and to induce apoptosis and cell differentiation, merged with natural-like cores were synthesized. A synthetic platform which joined a Domino Knoevenagel-Diels Alder reaction with a Suzuki coupling was performed in order to reach the hybrid compounds. These molecules can represent either antitumor lead candidates, or valuable chemical tools to study molecular pathways in cancer cells. The biological profile expressed by some of these derivatives showed a well defined antiproliferative activity on leukemia Bcr-Abl expressing K562 cell lines. A parallel project regarded the rational design and synthesis of minimally structurally hERG blockers with the purpose of enhancing the SAR studies of a previously synthesized collection. A Target-Oriented Synthesis approach was applied. Combining conventional and microwave heating, the desired final compounds were achieved in good yields and reaction rates. The preliminary biological results of the compounds, showed a potent blocking activity. The obtained small set of hERG blockers, was able to gain more insight the minimal structural requirements for hERG liability, which is mandatory to investigate in order to reduce the risk of potential side effects of new drug candidates.

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The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

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Divalent metal transporter-1 (SLC11A2/DMT1) uses the H+ electrochemical gradient as the driving force to transport divalent metal ions such as Fe2+, Mn2+ and others metals into mammalian cells. DMT1 is ubiquitously expressed, most notably in proximal duodenum, immature erythroid cells, brain and kidney. This transporter mediates H+-coupled transport of ferrous iron across the apical membrane of enterocytes. In addition, in cells such as to erythroid precursors, following transferrin receptor (TfR) mediated endocytosis; it mediates H+-coupled exit of ferrous iron from endocytic vesicles into the cytosol. Dysfunction of human DMT1 is associated with several pathologies such as iron deficiency anemia hemochromatosis, Parkinson's disease and Alzheimer's disease, as well as colorectal cancer and esophageal adenocarcinoma, making DMT1 an attractive target for drug discovery. In the present study, we performed a ligand-based virtual screening of the Princeton database (700,000 commercially available compounds) to search for pharmacophore shape analogs of recently reported DMT1 inhibitors. We discovered a new compound, named pyrimidinone 8, which mediates a reversible linear non-competitive inhibition of human DMT1 (hDMT1) transport activity with a Ki of ∼20 μM. This compound does not affect hDMT1 cell surface expression and shows no dependence on extracellular pH. To our knowledge, this is the first experimental evidence that hDMT1 can be allosterically modulated by pharmacological agents. Pyrimidinone 8 represents a novel versatile tool compound and it may serve as a lead structure for the development of therapeutic compounds for pre-clinical assessment.

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Tuberculosis is a chronic infectious disease that is transmitted by cough-propelled droplets that carry the etiologic bacterium, Mycobacterium tuberculosis. Although currently available drugs kill most isolates of M. tuberculosis, strains resistant to each of these have emerged, and multiply resistant strains are increasingly widespread. The growing problem of drug resistance combined with a global incidence of seven million new cases per year underscore the urgent need for new antituberculosis therapies. The recent publication of the complete sequence of the M. tuberculosis genome has made possible, for the first time, a comprehensive genomic approach to the biology of this organism and to the drug discovery process. We used a DNA microarray containing 97% of the ORFs predicted from this sequence to monitor changes in M. tuberculosis gene expression in response to the antituberculous drug isoniazid. Here we show that isoniazid induced several genes that encode proteins physiologically relevant to the drug’s mode of action, including an operonic cluster of five genes encoding type II fatty acid synthase enzymes and fbpC, which encodes trehalose dimycolyl transferase. Other genes, not apparently within directly affected biosynthetic pathways, also were induced. These genes, efpA, fadE23, fadE24, and ahpC, likely mediate processes that are linked to the toxic consequences of the drug. Insights gained from this approach may define new drug targets and suggest new methods for identifying compounds that inhibit those targets.

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The brain cholecystokinin-B/gastrin receptor (CCK-BR) is a major target for drug development because of its postulated role in modulating anxiety, memory, and the perception of pain. Drug discovery efforts have resulted in the identification of small synthetic molecules that can selectively activate this receptor subtype. These drugs include the peptide-derived compound PD135,158 as well as the nonpeptide benzodiazepine-based ligand, L-740,093 (S enantiomer). We now report that the maximal level of receptor-mediated second messenger signaling that can be achieved by these compounds (drug efficacy) markedly differs among species homologs of the CCK-BR. Further analysis reveals that the observed differences in drug efficacy are in large part explained by single or double aliphatic amino acid substitutions between respective species homologs. This interspecies variability in ligand efficacy introduces the possibility of species differences in receptor-mediated function, an important consideration when selecting animal models for preclinical drug testing. The finding that even single amino acid substitutions can significantly affect drug efficacy prompted us to examine ligand-induced signaling by a known naturally occurring human CCK-BR variant (glutamic acid replaced by lysine in position 288; 288E → K). When examined using the 288E → K receptor, the efficacies of both PD135,158 and L-740,093 (S) were markedly increased compared with values obtained with the wild-type human protein. These observations suggest that functional variability resulting from human receptor polymorphisms may contribute to interindividual differences in drug effects.

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The search for novel leads is a critical step in the drug discovery process. Computational approaches to identify new lead molecules have focused on discovering complete ligands by evaluating the binding affinity of a large number of candidates, a task of considerable complexity. A new computational method is introduced in this work based on the premise that the primary molecular recognition event in the protein binding site may be accomplished by small core fragments that serve as molecular anchors, providing a structurally stable platform that can be subsequently tailored into complete ligands. To fulfill its role, we show that an effective molecular anchor must meet both the thermodynamic requirement of relative energetic stability of a single binding mode and its consistent kinetic accessibility, which may be measured by the structural consensus of multiple docking simulations. From a large number of candidates, this technique is able to identify known core fragments responsible for primary recognition by the FK506 binding protein (FKBP-12), along with a diverse repertoire of novel molecular cores. By contrast, absolute energetic criteria for selecting molecular anchors are found to be promiscuous. A relationship between a minimum frustration principle of binding energy landscapes and receptor-specific molecular anchors in their role as "recognition nuclei" is established, thereby unraveling a mechanism of lead discovery and providing a practical route to receptor-biased computational combinatorial chemistry.