997 resultados para Drug modeling
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Consistent in silico models for ADME properties are useful tools in early drug discovery. Here, we report the hologram QSAR modeling of human intestinal absorption using a dataset of 638 compounds with experimental data associated. The final validated models are consistent and robust for the consensus prediction of this important pharmacokinetic property and are suitable for virtual screening applications. (C) 2012 Elsevier Ltd. All rights reserved.
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Tuberculosis (TB) is a major infectious disease caused by Mycobacterium tuberculosis (Mtb). According to the World Health Organization (WHO), about 1.8 million people die from TB and 10 million new cases are recorded each year. Recently, a new series of naphthylchalcones has been identified as inhibitors of Mtb protein tyrosine phosphatases (PTPs). In this work, 100 chalcones were designed, synthesized, and investigated for their inhibitory properties against MtbPtps. Structure-activity relationships (SAR) were developed, leading to the discovery of new potent inhibitors with IC50 values in the low-micromolar range. Kinetic studies revealed competitive inhibition and high selectivity toward the Mtb enzymes. Molecular modeling investigations were carried out with the aim of revealing the most relevant structural requirements underlying the binding affinity and selectivity of this series of inhibitors as potential anti-TB drugs.
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Micelles composed of amphiphilic copolymers linked to a radioactive element are used in nuclear medicine predominantly as a diagnostic application. A relevant advantage of polymeric micelles in aqueous solution is their resulting particle size, which can vary from 10 to 100 nm in diameter. In this review, polymeric micelles labeled with radioisotopes including technetium (99mTc) and indium (111In), and their clinical applications for several diagnostic techniques, such as single photon emission computed tomography (SPECT), gamma-scintigraphy, and nuclear magnetic resonance (NMR), were discussed. Also, micelle use primarily for the diagnosis of lymphatic ducts and sentinel lymph nodes received special attention. Notably, the employment of these diagnostic techniques can be considered a significant tool for functionally exploring body systems as well as investigating molecular pathways involved in the disease process. The use of molecular modeling methodologies and computer-aided drug design strategies can also yield valuable information for the rational design and development of novel radiopharmaceuticals.
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Human African trypanosomiasis, also known as sleeping sickness, is a major cause of death in Africa, and for which there are no safe and effective treatments available. The enzyme aldolase from Trypanosoma brucei is an attractive, validated target for drug development. A series of alkyl‑glycolamido and alkyl-monoglycolate derivatives was studied employing a combination of drug design approaches. Three-dimensional quantitative structure-activity relationships (3D QSAR) models were generated using the comparative molecular field analysis (CoMFA). Significant results were obtained for the best QSAR model (r2 = 0.95, non-cross-validated correlation coefficient, and q2 = 0.80, cross-validated correlation coefficient), indicating its predictive ability for untested compounds. The model was then used to predict values of the dependent variables (pKi) of an external test set,the predicted values were in good agreement with the experimental results. The integration of 3D QSAR, molecular docking and molecular dynamics simulations provided further insight into the structural basis for selective inhibition of the target enzyme.
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Background: Sleeping sickness is a major cause of death in Africa. Since no secure treatment is available, the development of novel therapeutic agents is urgent. In this context, the enzyme trypanothione reductase (TR) is a prominent molecular target that has been investigated in drug design for sleeping sickness. Results: In this study, comparative molecular field analysis models were generated for a series of Trypanosoma brucei TR inhibitors. Statistically significant results were obtained and the models were applied to predict the activity of external test sets, with good correlation between predicted and experimental results. We have also investigated the structural requirements for the selective inhibition of the parasite's enzyme over the human glutathione reductase. Conclusion: The quantitative structure-activity relationship models provided valuable information regarding the essential molecular requirements for the inhibitory activity upon the target protein, providing important insights into the design of more potent and selective TR inhibitors.
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The hERG voltage-gated potassium channel mediates the cardiac I(Kr) current, which is crucial for the duration of the cardiac action potential. Undesired block of the channel by certain drugs may prolong the QT interval and increase the risk of malignant ventricular arrhythmias. Although the molecular determinants of hERG block have been intensively studied, not much is known about its stereoselectivity. Levo-(S)-bupivacaine was the first drug reported to have a higher affinity to block hERG than its enantiomer. This study strives to understand the principles underlying the stereoselectivity of bupivacaine block with the help of mutagenesis analyses and molecular modeling simulations. Electrophysiological measurements of mutated hERG channels allowed for the identification of residues involved in bupivacaine binding and stereoselectivity. Docking and molecular mechanics simulations for both enantiomers of bupivacaine and terfenadine (a non-stereoselective blocker) were performed inside an open-state model of the hERG channel. The predicted binding modes enabled a clear depiction of ligand-protein interactions. Estimated binding affinities for both enantiomers were consistent with electrophysiological measurements. A similar computational procedure was applied to bupivacaine enantiomers towards two mutated hERG channels (Tyr652Ala and Phe656Ala). This study confirmed, at the molecular level, that bupivacaine stereoselectively binds the hERG channel. These results help to lay the foundation for structural guidelines to optimize the cardiotoxic profile of drug candidates in silico.
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Drug hypersensitivity research has progressed enormously in recent years, and a greater understanding of mechanisms has contributed to improved drug safety. Progress has been made in genetics, enabling personalized medicine for certain drugs, and in understanding drug interactions with the immune system. In a recent meeting in Rome, the clinical, chemical, pharmacologic, immunologic, and genetic aspects of drug hypersensitivity were discussed, and certain aspects are briefly summarized here. Small chemicals, including drugs, can induce immune reactions by binding as a hapten to a carrier protein. Park (Liverpool, England) demonstrated (1) that drug haptens bind to protein in patients in a highly restricted manner and (2) that irreversibly modified carrier proteins are able to stimulate CD4(+) and CD8(+) T cells from hypersensitive patients. Drug haptens might also stimulate cells of the innate immune system, in particular dendritic cells, and thus give rise to a complex and complete immune reaction. Many drugs do not have hapten-like characteristics but might gain them on metabolism (so-called prohaptens). The group of Naisbitt found that the stimulation of dendritic cells and T cells can occur as a consequence of the transformation of a prohapten to a hapten in antigen-presenting cells and as such explain the immune-stimulatory capacity of prohaptens. The striking association between HLA-B alleles and the development of certain drug reactions was discussed in detail. Mallal (Perth, Australia) elegantly described a highly restricted HLA-B∗5701-specific T-cell response in abacavir-hypersensitive patients and healthy volunteers expressing HLA-B∗5701 but not closely related alleles. Expression of HLA-B∗1502 is a marker known to be necessary but not sufficient to predict carbamazepine-induced Stevens-Johnson syndrome/toxic epidermal necrolysis in Han Chinese. The group of Chen and Hong (Taiwan) described the possible "missing link" because they showed that the presence of certain T-cell receptor (TCR) clonotypes was necessary to elicit T-cell responses to carbamazepine. The role of TCRs in drug binding was also emphasized by Pichler (Bern, Switzerland). Following up on their "pharmacological interactions of drugs with immune receptors" concept (p-i concept), namely that drugs can bind directly to TCRs, MHC molecules, or both and thereby stimulate T cells, they looked for drug-binding sites for the drug sulfamethoxazole in drug-specific TCRs: modeling revealed up to 7 binding sites on the CDR3 and CDR2 regions of TCR Vα and Vβ. Among many other presentations, the important role of regulatory T cells in drug hypersensitivity was addressed.
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Drug release from a fluid-contacting biomaterial is simulated using a microfluidic device with channels defined by solute-loaded hydrogel. In order to mimic a drug delivery device, a solution of poly(ethylene glycol) diacrylate (PEG-DA), solute, and photoinitiator is cured inside a microfluidic device with a channel through the center ofthe hydrogel. As water is pumped through the channel, solute diffuses out of the hydrogel and into the water. Channel sizes within the devices range from 300 µm to 1000 µm to simulate vessels within the body. The properties of the PEG hydrogel were characterizedby the extent of crosslinking, the swelling ratio, and the mesh size of the gel. The structure of the hydrogel was related to the UV exposure dosage and the initial water and solute content in the PEG-DA solution.
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In recent years, the bio-conjugated nanostructured materials have emerged as a new class of materials for the bio-sensing and medical diagnostics applications. In spite of their multi-directional applications, interfacing nanomaterials with bio-molecules has been a challenge due to somewhat limited knowledge about the underlying physics and chemistry behind these interactions and also for the complexity of biomolecules. The main objective of this dissertation is to provide such a detailed knowledge on bioconjugated nanomaterials toward their applications in designing the next generation of sensing devices. Specifically, we investigate the changes in the electronic properties of a boron nitride nanotube (BNNT) due to the adsorption of different bio-molecules, ranging from neutral (DNA/RNA nucleobases) to polar (amino acid molecules). BNNT is a typical member of III-V compounds semiconductors with morphology similar to that of carbon nanotubes (CNTs) but with its own distinct properties. More specifically, the natural affinity of BNNTs toward living cells with no apparent toxicity instigates the applications of BNNTs in drug delivery and cell therapy. Our results predict that the adsorption of DNA/RNA nucleobases on BNNTs amounts to different degrees of modulation in the band gap of BNNTs, which can be exploited for distinguishing these nucleobases from each other. Interestingly, for the polar amino acid molecules, the nature of interaction appeared to vary ranging from Coulombic, van der Waals and covalent depending on the polarity of the individual molecules, each with a different binding strength and amount of charge transfer involved in the interaction. The strong binding of amino acid molecules on the BNNTs explains the observed protein wrapping onto BNNTs without any linkers, unlike carbon nanotubes (CNTs). Additionally, the widely varying binding energies corresponding to different amino acid molecules toward BNNTs indicate to the suitability of BNNTs for the biosensing applications, as compared to the metallic CNTs. The calculated I-V characteristics in these bioconjugated nanotubes predict notable changes in the conductivity of BNNTs due to the physisorption of DNA/RNA nucleobases. This is not the case with metallic CNTs whose transport properties remained unaltered in their conjugated systems with the nucleobases. Collectively, the bioconjugated BNNTs are found to be an excellent system for the next generation sensing devices.
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OBJECTIVE: Hierarchical modeling has been proposed as a solution to the multiple exposure problem. We estimate associations between metabolic syndrome and different components of antiretroviral therapy using both conventional and hierarchical models. STUDY DESIGN AND SETTING: We use discrete time survival analysis to estimate the association between metabolic syndrome and cumulative exposure to 16 antiretrovirals from four drug classes. We fit a hierarchical model where the drug class provides a prior model of the association between metabolic syndrome and exposure to each antiretroviral. RESULTS: One thousand two hundred and eighteen patients were followed for a median of 27 months, with 242 cases of metabolic syndrome (20%) at a rate of 7.5 cases per 100 patient years. Metabolic syndrome was more likely to develop in patients exposed to stavudine, but was less likely to develop in those exposed to atazanavir. The estimate for exposure to atazanavir increased from hazard ratio of 0.06 per 6 months' use in the conventional model to 0.37 in the hierarchical model (or from 0.57 to 0.81 when using spline-based covariate adjustment). CONCLUSION: These results are consistent with trials that show the disadvantage of stavudine and advantage of atazanavir relative to other drugs in their respective classes. The hierarchical model gave more plausible results than the equivalent conventional model.
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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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Cefepime is a broad-spectrum cephalosporin indicated for in-hospital treatment of severe infections. Acute neurotoxicity, an increasingly recognized adverse effect of this drug in an overdose, predominantly affects patients with reduced renal function. Although dialytic approaches have been advocated to treat this condition, their role in this indication remains unclear. We report the case of an 88-year-old female patient with impaired renal function who developed life-threatening neurologic symptoms during cefepime therapy. She was treated with two intermittent 3-hour high-flux, high-efficiency hemodialysis sessions. Serial pre-, post-, and peridialytic (pre- and postfilter) serum cefepime concentrations were measured. Pharmacokinetic modeling showed that this dialytic strategy allowed for serum cefepime concentrations to return to the estimated nontoxic range 15 hours earlier than would have been the case without an intervention. The patient made a full clinical recovery over the next 48 hours. We conclude that at least 1 session of intermittent hemodialysis may shorten the time to return to the nontoxic range in severe clinically patent intoxication. It should be considered early in its clinical course pending chemical confirmation, even in frail elderly patients. Careful dosage adjustment and a high index of suspicion are essential in this population.
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This study investigated the relative contribution of ion-trapping, microsomal binding, and distribution of unbound drug as determinants in the hepatic retention of basic drugs in the isolated perfused rat liver. The ionophore monensin was used to abolish the vesicular proton gradient and thus allow an estimation of ion-trapping by acidic hepatic vesicles of cationic drugs. In vitro microsomal studies were used to independently estimate microsomal binding and metabolism. Hepatic vesicular ion-trapping, intrinsic elimination clearance, permeability-surface area product, and intracellular binding were derived using a physiologically based pharmacokinetic model. Modeling showed that the ion-trapping was significantly lower after monensin treatment for atenolol and propranolol, but not for antipyrine. However, no changes induced by monensin treatment were observed in intrinsic clearance, permeability, or binding for the three model drugs. Monensin did not affect binding or metabolic activity in vitro for the drugs. The observed ion-trapping was similar to theoretical values estimated using the pHs and fractional volumes of the acidic vesicles and the pK(a) values of drugs. Lipophilicity and pK(a) determined hepatic drug retention: a drug with low pK(a) and low lipophilicity (e.g., antipyrine) distributes as unbound drug, a drug with high pK(a) and low lipophilicity (e.g., atenolol) by ion-trapping, and a drug with a high pK(a) and high lipophilicity (e.g., propranolol) is retained by ion-trapping and intracellular binding. In conclusion, monensin inhibits the ion-trapping of high pK(a) basic drugs, leading to a reduction in hepatic retention but with no effect on hepatic drug extraction.
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Schistosomiasis japonica is a zoonosis of major public health importance in southern China. We undertook a drug intervention to test the hypothesis that buffalo are major reservoirs for human infection in the marshlands/lake areas, where one million people are infected. We compared human and buffalo infection rates and intensity in an intervention village (Jishan), where humans and buffalo were treated with praziquantel, and a control village (Hexi), where only humans were treated, in the Poyang Lake region. Over the four-year study, human incidence in Jishan decreased but increased in Hexi. Adjustment of incidence by age, sex, water exposure, year, and village further confirmed the decreased human infection in Jishan. Chemotherapy for buffaloes resulted in a decrease in buffalo infection rates in Jishan, which coincided with the reduction in human infection rates there in the last two years of the study. Mathematical modeling predicted that buffalo are responsible for 75% of human transmission in Jishan. Copyright © 2006 by The American Society of Tropical Medicine and Hygiene.