981 resultados para QSAR-2D
Resumo:
This paper presents the synthesis of the coordination polymers ∞[Ln(DPA)(HDPA)] (DPA=2,6-pyridinedicarboxylate; Ln= Tb and Gd), their structural and spectroscopic properties. The structural study reveals that the ∞[Ln(DPA)(HDPA)] has a single Ln+3 ion coordinated with two H2DPA ligands in tridentade coordination mode, while two others H2DPA establish a syn-bridge with a symmetry-related Ln3+, forming a two-dimensional structure. The spectroscopic studies show that ∞[Tb(DPA)(HDPA)] compound has high quantum yield (q x≈ 50.0%), due to the large contribution of radiative decay rate. Moreover triplet level is localized sufficiently over the emitter level 5D4 of theTb3+ ion, avoiding a retrotransference process between these states.
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Alzheimer's disease (AD) is considered the main cause of cognitive decline in adults. The available therapies for AD treatment seek to maintain the activity of cholinergic system through the inhibition of the enzyme acetylcholinesterase. However, butyrylcholinesterase (BuChE) can be considered an alternative target for AD treatment. Aiming at developing new BuChE inhibitors, robust QSAR 3D models with high predictive power were developed. The best model presents a good fit (r²=0.82, q²=0.76, with two PCs) and high predictive power (r²predict=0.88). Analysis of regression vector shows that steric properties have considerable importance to the inhibition of the BuChE.
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Descriptors in multivariate image analysis applied to quantitative structure-activity relationship (MIA-QSAR) are pixels of bidimensional images of chemical structures (drawings), which were used to model the trichomonicidal activities of a series of benzimidazole derivatives. The MIA-QSAR model showed good predictive ability, with r², q² and r val. ext.² of 0.853, 0.519 and 0.778, respectively, which are comparable to the best values obtained by CoMFA e CoMSIA for the same series. A MIA-based analysis was also performed by using images of alphabetic letters with the corresponding numeric ordering as dependent variables, but no correlation was found, supporting that MIA-QSAR is not arbitrary.
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QSAR modeling is a novel computer program developed to generate and validate QSAR or QSPR (quantitative structure- activity or property relationships) models. With QSAR modeling, users can build partial least squares (PLS) regression models, perform variable selection with the ordered predictors selection (OPS) algorithm, and validate models by using y-randomization and leave-N-out cross validation. An additional new feature is outlier detection carried out by simultaneous comparison of sample leverage with the respective Studentized residuals. The program was developed using Java version 6, and runs on any operating system that supports Java Runtime Environment version 6. The use of the program is illustrated. This program is available for download at lqta.iqm.unicamp.br.
Resumo:
Ultrafast 2D NMR is a powerful methodology that allows recording of a 2D NMR spectrum in a fraction of second. However, due to the numerous non-conventional parameters involved in this methodology its implementation is no trivial task. Here, an optimized experimental protocol is carefully described to ensure efficient implementation of ultrafast NMR. The ultrafast spectra resulting from this implementation are presented based on the example of two widely used 2D NMR experiments, COSY and HSQC, obtained in 0.2 s and 41 s, respectively.
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Imide compounds have shown biological activity. These compounds can be easily synthesized with good yields. The objective of this paper was the rational planning of imides and sulfonamides with antinociceptive activity using the 3D-QSAR/CoMFA approach. The studies were performed using two data sets. The first set consisted of 39 cyclic imides while the second set consisted of 39 imides and 15 sulfonamides. The 3D- QSAR/CoMFA models have shown that the steric effect is important for the antinociceptive activity of imide and sulphonamide compounds. Ten new compounds with improved potential antinociceptive activity have been proposed by de novo design leapfrog simulations.
Resumo:
Microscopic visualization, especially in transparent micromodels, can provide valuable information to understand the transport phenomena at pore scale in different process occurring in porous materials (food, timber, soils, etc.). Micromodels studies focus mainly on the observation of multi-phase flow, which presents a greater proximity to reality. The aim of this study was to study the process of flexography and its application in the manufacture of polyester resin transparent micromodels and its application to carrots. Materials used to implement a flexo station for micromodels construction were thermoregulated water bath, exposure chamber to UV light, photosensitive substance (photopolymer), RTV silicone polyester resin, and glass plates. In this paper, data on size distribution of a particular kind of carrot we used, and a transparent micromodel with square cross-section as well as a Log-normal pore size distribution with pore radii ranging from 10 to 110 µm (average of 22 µm and micromodel size of 10 × 10 cm) were built. Finally, it stresses that it has successfully implemented the protocol processing 2D polyester resin transparent micromodels.
Resumo:
Rindfleisch (Daniel). Album amicorum (1590-1591)
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Solid state nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for studying structural and dynamical properties of disordered and partially ordered materials, such as glasses, polymers, liquid crystals, and biological materials. In particular, twodimensional( 2D) NMR methods such as ^^C-^^C correlation spectroscopy under the magicangle- spinning (MAS) conditions have been used to measure structural constraints on the secondary structure of proteins and polypeptides. Amyloid fibrils implicated in a broad class of diseases such as Alzheimer's are known to contain a particular repeating structural motif, called a /5-sheet. However, the details of such structures are poorly understood, primarily because the structural constraints extracted from the 2D NMR data in the form of the so-called Ramachandran (backbone torsion) angle distributions, g{^,'4)), are strongly model-dependent. Inverse theory methods are used to extract Ramachandran angle distributions from a set of 2D MAS and constant-time double-quantum-filtered dipolar recoupling (CTDQFD) data. This is a vastly underdetermined problem, and the stability of the inverse mapping is problematic. Tikhonov regularization is a well-known method of improving the stability of the inverse; in this work it is extended to use a new regularization functional based on the Laplacian rather than on the norm of the function itself. In this way, one makes use of the inherently two-dimensional nature of the underlying Ramachandran maps. In addition, a modification of the existing numerical procedure is performed, as appropriate for an underdetermined inverse problem. Stability of the algorithm with respect to the signal-to-noise (S/N) ratio is examined using a simulated data set. The results show excellent convergence to the true angle distribution function g{(j),ii) for the S/N ratio above 100.