3 resultados para Information structures

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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Alzheimer`s disease is an ultimately fatal neurodegenerative disease, and BACE-1 has become an attractive validated target for its therapy, with more than a hundred crystal structures deposited in the PDB. In the present study, we present a new methodology that integrates ligand-based methods with structural information derived from the receptor. 128 BACE-1 inhibitors recently disclosed by GlaxoSmithKline R&D were selected specifically because the crystal structures of 9 of these compounds complexed to BACE-1, as well as five closely related analogs, have been made available. A new fragment-guided approach was designed to incorporate this wealth of structural information into a CoMFA study, and the methodology was systematically compared to other popular approaches, such as docking, for generating a molecular alignment. The influence of the partial charges calculation method was also analyzed. Several consistent and predictive models are reported, including one with r (2) = 0.88, q (2) = 0.69 and r (pred) (2) = 0.72. The models obtained with the new methodology performed consistently better than those obtained by other methodologies, particularly in terms of external predictive power. The visual analyses of the contour maps in the context of the enzyme drew attention to a number of possible opportunities for the development of analogs with improved potency. These results suggest that 3D-QSAR studies may benefit from the additional structural information added by the presented methodology.

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PPAR gamma is a ligand regulated transcriptional factor that modulates the transcription of several genes involved in fat and sugar metabolism. Due to its easy bacterial expression and crystallization, several crystal structures of holo-PPAR gamma have been reported and deposited in the Protein Data Bank. Here, we investigated the three-dimensional electrostatic properties of 55 PPAR gamma ligands and used this information for clustering them through principal component analysis. We found out that, according to their electrostatic potential, these ligands can be separated in three groups, with different binding features. We also observed that non-selective and selective ligands show different 3D electrostatic properties and are separated in different clusters. The relevance of this analysis for the development of new binders is discussed. (C) 2010 Elsevier Masson SAS. All rights reserved.

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In this paper, a novel statistical test is introduced to compare two locally stationary time series. The proposed approach is a Wald test considering time-varying autoregressive modeling and function projections in adequate spaces. The covariance structure of the innovations may be also time- varying. In order to obtain function estimators for the time- varying autoregressive parameters, we consider function expansions in splines and wavelet bases. Simulation studies provide evidence that the proposed test has a good performance. We also assess its usefulness when applied to a financial time series.