997 resultados para 3d-qsar


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Three-dimensional QSAR studies for N-4-arylacryloylpiperazin-1-yl-phenyl-oxazolidinones were conducted using TSAR 3.3. The in vitro activities (MICs) of the compounds against Staphylococcus aureus ATCC 25923 exhibited a strong correlation with the prediction made by the model developed in the present study.

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Three-dimensional QSAR studies for substituted aryloxazolidinones 3–9 were conducted using TSAR 3.3. The in vitro activities (MICs) of the compounds against Staphylococcus aureus and Enterococcus faecalis exhibited a good correlation with the prediction made by the model using heat of formation and LUMO energies.

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To understand pharmacophore properties of pyranmycin derivatives and to design novel inhibitors of 16S rRNA A site, comparative molecular field analysis (CoMFA) approach was applied to analyze three-dimensional quantitative structure-activity relationship (3D-QSAR) of 17 compounds. AutoDock 3.0.5 program was employed to locate the orientations and conformations of the inhibitors interacting with 16S rRNA A site. The interaction mode was demonstrated in the aspects of inhibitor conformation, hydrogen bonding and electrostatic interaction. Similar binding conformations of these inhibitors and good correlations between the calculated binding free energies and experimental biological activities suggest that the binding conformations of these inhibitors derived from docking procedure were reasonable. Robust and predictive 3D-QSAR model was obtained by CoMFA with q(2) values of 0.723 and 0.993 for cross-validated and noncross-validated, respectively. The 3D-QSAR model built here will provide clear guidelines for novel inhibitors design based on the Pyranmycin derivatives against 16S rRNA A site. (c) 2005 Elsevier B.V. All rights reserved.

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Steroid derivatives show a complex interaction with P-glycoprotein (Pgp). To determine the essential structural requirements of a series of structurally related and functionally diverse steroids for Pgp-mediated transport or inhibition, a three-dimensional quantitative structure activity relationship study was performed by comparative similarity index analysis modeling. Twelve models have been explored to well correlate the physiochemical features with their biological functions with Pgp on basis of substrate and inhibitor datasets, in which the best predictive model for substrate gave cross-validated q(2) = 0.720, non-cross-validated r(2) = 0.998, standard error of estimate SEE = 0.012, F = 257.955, and the best predictive model for inhibitor gave q(2) = 0.536, r(2) = 0.950, SEE = 1.761 and F = 45.800. The predictive ability of all models was validated by a set of compounds that were not included in the training set. The physiochemical similarities and differences of steroids as Pgp substrate and inhibitor, respectively, were analyzed to be helpful in developing new steroid-like compounds. (C) 2004 Elsevier B.V. All rights reserved.

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用比较力场分析研究了 3 ,4 二甲基 4 ( 3 羟基苯基 )哌啶及其衍生物类吗啡拮抗物的结构与抑食活性的关系 ,考察了网格结构和探针原子的影响 .结果表明 ,立体效应和静电作用场是描述其抑食活性和进行结构性能关系研究的最重要的结构参数

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研究了甾族化合物的结构与抗炎活性相关性的三维构效关系,采用比较分子力场分析法(CoMFA)寻找结构与活性的关系,建立了一个可靠的构效关系模型,为活性分子的进一步修饰和改造提供了信息。

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A comparative molecular field analysis (CoMFA) of alkanoic acid 3-oxo-cyclohex-1-enyl ester and 2-acylcyclohexane-1,3-dione derivatives of 4-hydroxyphenylpyruvate dioxygenase inhibitors has been performed to determine the factors required for the activity of these compounds. The substrate's conformation abstracted from dynamic modeling of the enzyme-substrate complex was used to build the initial structures of the inhibitors. Satisfactory results were obtained after an all-space searching procedure, performing a leave-one out (LOO) cross-validation study with cross-validation q(2) and conventional r(2) values of 0.779 and 0.989, respectively. The results provide the tools for predicting the affinity of related compounds, and for guiding the design and synthesis of new HPPD ligands with predetermined affinities.

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Three-dimensional quantitative structure-activity relationships (3D-QSAR) were performed for a series of analgesic cyclic imides using the CoMFA and CoMSIA methods. Significant correlation coefficients ( CoMFA, r(2) = 0.95 and q(2) = 0.72; CoMSIA, r(2) = 0.96 and q(2) = 0.76) were obtained, and the generated models were externally validated using test sets. The final QSAR models as well as the information gathered from 3D contour maps should be useful for the design of novel cyclic imides having improved analgesic activity.

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The glycolytic enzyme glyceraldehyde-3 -phosphate dehydrogenase (GAPDH) is as an attractive target for the development of novel antitrypanosomatid agents. In the present work, comparative molecular field analysis and comparative molecular similarity index analysis were conducted on a large series of selective inhibitors of trypanosomatid GAPDH. Four statistically significant models were obtained (r(2) > 0.90 and q(2) > 0.70), indicating their predictive ability for untested compounds. The models were then used to predict the potency of an external test set, and the predicted values were in good agreement with the experimental results. Molecular modeling studies provided further insight into the structural basis for selective inhibition of trypanosomatid GAPDH.

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5-HT(1A) receptor antagonists have been employed to treat depression, but the lack of structural information on this receptor hampers the design of specific and selective ligands. In this study, we have performed CoMFA studies on a training set of arylpiperazines (high affinity 5-HT(1A) receptor ligands) and to produce an effective alignment of the data set, a pharmacophore model was produced using Galahad. A statistically significant model was obtained, indicating a good internal consistency and predictive ability for untested compounds. The information gathered from our receptor-independent pharmacophore hypothesis is in good agreement with results from independent studies using different approaches. Therefore, this work provides important insights on the chemical and structural basis involved in the molecular recognition of these compounds. (C) 2010 Elsevier Masson SAS. All rights reserved.

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Trypanothione reductase has long been investigated as a promising target for chemotherapeutic intervention in Chagas disease, since it is an enzyme of a unique metabolic pathway that is exclusively present in the pathogen but not in the human host, which has the analog Glutathione reductase. In spite of the present data-set includes a small number of compounds, a combined use of flexible docking, pharmacophore perception, ligand binding site prediction, and Grid-Independent Descriptors GRIND2-based 3D-Quantitative Structure-Activity Relationships (QSAR) procedures allowed us to rationalize the different biological activities of a series of 11 aryl beta-aminocarbonyl derivatives, which are inhibitors of Trypanosoma cruzi trypanothione reductase (TcTR). Three QSAR models were built and validated using different alignments, which are based on docking with the TcTR crystal structure, pharmacophore, and molecular interaction fields. The high statistical significance of the models thus obtained assures the robustness of this second generation of GRIND descriptors here used, which were able to detect the most important residues of such enzyme for binding the aryl beta-aminocarbonyl derivatives, besides to rationalize distances among them. Finally, a revised binding mode has been proposed for our inhibitors and independently supported by the different methodologies here used, allowing further optimization of the lead compounds with such combined structure- and ligand-based approaches in the fight against the Chagas disease.

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Nuclear hormone receptors, such as the ecdysone receptor, often display a large amount of induced fit to ligands. The size and shape of the binding pocket in the EcR subunit changes markedly on ligand binding, making modelling methods such as docking extremely challenging. It is, however, possible to generate excellent 3D QSAR models for a given type of ligand, suggesting that the receptor adopts a relatively restricted number of binding site configurations or [`]attractors'. We describe the synthesis, in vitro binding and selected in vivo toxicity data for [gamma]-methylene [gamma]-lactams, a new class of high-affinity ligands for ecdysone receptors from Bovicola ovis (Phthiraptera) and Lucilia cuprina (Diptera). The results of a 3D QSAR study of the binding of methylene lactams to recombinant ecdysone receptor protein suggest that this class of ligands is indeed recognized by a single conformation of the EcR binding pocket.

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Most physiological effects of thyroid hormones are mediated by the two thyroid hormone receptor subtypes, TR alpha and TR beta. Several pharmacological effects mediated by TR beta might be beneficial in important medical conditions such as obesity, hypercholesterolemia and diabetes, and selective TR beta activation may elicit these effects while maintaining an acceptable safety profile, To understand the molecular determinants of affinity and subtype selectivity of TR ligands, we have successfully employed a ligand- and structure-guided pharmacophore-based approach to obtain the molecular alignment of a large series of thyromimetics. Statistically reliable three-dimensional quantitative structure-activity relationship (3D-QSAR) and three-dimensional quantitative structure-selectivity relationship (3D-QSSR) models were obtained using the comparative molecular field analysis (CoMFA) method, and the visual analyses of the contour maps drew attention to a number of possible opportunities for the development of analogs with improved affinity and selectivity. Furthermore, the 3D-QSSR analysis allowed the identification of a novel and previously unmentioned halogen bond, bringing new insights to the mechanism of activity and selectivity of thyromimetics.

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PPAR delta is a nuclear receptor that, when activated, regulates the metabolism of carbohydrates and lipids and is related to metabolic syndrome and type 2 diabetes. To understand the main interactions between ligands and PPAR delta, we have constructed 2D and 3D QSAR models and compared them with HOMO, LUMO and electrostatic potential maps of the compounds studied, as well as docking results. All QSAR models showed good statistical parameters and prediction outcomes. The QSAR models were used to predict the biological activity of an external test set, and the predicted values are in good agreement with the experimental results. Furthermore, we employed all maps to evaluate the possible interactions between the ligands and PPAR delta. These predictive QSAR models, along with the HOMO, LUMO and MEP maps, can provide insights into the structural and chemical properties that are needed in the design of new PPAR delta ligands that have improved biological activity and can be employed to treat metabolic diseases.

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Breast cancer is the most common cancer in women in Western countries. In the early stages of development most breast cancers are hormone-dependent, and estrogens, especially estradiol, have a pivotal role in their development and progression. One approach to the treatment of hormone-dependent breast cancers is to block the formation of the active estrogens by inhibiting the action of the steroid metabolising enzymes. 17beta-Hydroxysteroid dehydrogenase type 1 (17beta-HSD1) is a key enzyme in the biosynthesis of estradiol, the most potent female sex hormone. The 17beta-HSD1 enzyme catalyses the final step and converts estrone into the biologically active estradiol. Blocking 17beta-HSD1 activity with a specific enzyme inhibitor could provide a means to reduce circulating and tumour estradiol levels and thus promote tumour regression. In recent years 17beta-HSD1 has been recognised as an important drug target. Some inhibitors of 17beta-HSD1 have been reported, however, there are no inhibitors on the market nor have clinical trials been announced. The majority of known 17beta-HSD1 inhibitors are based on steroidal structures, while relatively little has been reported on non-steroidal inhibitors. As compared with 17beta-HSD1 inhibitors based on steroidal structures, non-steroidal compounds could have advantages of synthetic accessibility, drug-likeness, selectivity and non-estrogenicity. This study describes the synthesis of large group of novel 17beta-HSD1 inhibitors based on a non-steroidal thieno[2,3-d]pyrimidin-4(3H)-one core. An efficient synthesis route was developed for the lead compound and subsequently employed in the synthesis of thieno[2,3-d]pyrimidin-4(3H)-one based molecule library. The biological activities and binding of these inhibitors to 17beta-HSD1 and, finally, the quantitative structure activity relationship (QSAR) model are also reported. In this study, several potent and selective 17beta-HSD1 inhibitors without estrogenic activity were identified. This establishment of a novel class of inhibitors is a progressive achievement in 17beta-HSD1 inhibitor development. Furthermore, the 3D-QSAR model, constructed on the basis of this study, offers a powerful tool for future 17beta-HSD1 inhibitor development. As part of the fundamental science underpinning this research, the chemical reactivity of fused (di)cycloalkeno thieno[2,3-d]pyrimidin-4(3H)-ones with electrophilic reagents, i.e. Vilsmeier reagent and dimethylformamide dimethylacetal, was investigated. These findings resulted in a revision of the reaction mechanism of Vilsmeier haloformylation and further contributed to understanding the chemical reactivity of this compound class. This study revealed that the reactivity is dependent upon a stereoelectronic effect arising from different ring conformations.