141 resultados para 3390
em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"
Resumo:
BjVIII is a new myotoxic Lys49-PLA2 isolated from Bothrops jararacussu venom that exhibits atypical effects on human platelet aggregation. To better understand the mode of action of BjVIII, crystallographic studies were initiated. Two crystal forms were obtained, both containing two molecules in the asymmetric unit (ASU). Synchrotron radiation diffraction data were collected to 2.0 angstrom resolution and 1.9 angstrom resolution for crystals belonging to the space group P2(1)2(1)2(1) (a = 48.4 angstrom, b = 65.3 angstrom, c = 84.3 angstrom) and space group P3(1)21 (a = b = 55.7 angstrom, c = 127.9 angstrom), respectively. Refinement is currently in progress and the refined structures are expected to shed light on the unusual platelet aggregation activity observed for BjVIII.
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Resumo:
Recently, World Health Organization ( WHO) and Medicins San Frontieres (MSF) proposed a classification of diseases as global, neglected and extremely neglected. Global diseases, such as cancer, cardiovascular and mental (CNS) diseases represent the targets of the majority of the R&D efforts of pharmaceutical companies. Neglected diseases affect millions of people in the world yet existing drug therapy is limited and often inappropriate. Furthermore, extremely neglected diseases affect people living under miserable conditions who barely have access to the bare necessities for survival. Most of these diseases are excluded from the goals of the R&D programs in the pharmaceutical industry and therefore fall outside the pharmaceutical market. About 14 million people, mainly in developing countries, die each year from infectious diseases. From 1975 to 1999, 1393 new drugs were approved yet only 1% were for the treatment of neglected diseases [ 3]. These numbers have not changed until now, so in those countries there is an urgent need for the design and synthesis of new drugs and in this area the prodrug approach is a very interesting field. It provides, among other effects, activity improvements and toxicity decreases for current and new drugs, improving market availability. It is worth noting that it is essential in drug design to save time and money, and prodrug approaches can be considered of high interest in this respect. The present review covers 20 years of research on the design of prodrugs for the treatment of neglected and extremely neglected diseases such as Chagas' disease ( American trypanosomiasis), sleeping sickness ( African trypanosomiasis), malaria, sickle cell disease, tuberculosis, leishmaniasis and schistosomiasis.
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
The study of function approximation is motivated by the human limitation and inability to register and manipulate with exact precision the behavior variations of the physical nature of a phenomenon. These variations are referred to as signals or signal functions. Many real world problem can be formulated as function approximation problems and from the viewpoint of artificial neural networks these can be seen as the problem of searching for a mapping that establishes a relationship from an input space to an output space through a process of network learning. Several paradigms of artificial neural networks (ANN) exist. Here we will be investigated a comparative of the ANN study of RBF with radial Polynomial Power of Sigmoids (PPS) in function approximation problems. Radial PPS are functions generated by linear combination of powers of sigmoids functions. The main objective of this paper is to show the advantages of the use of the radial PPS functions in relationship traditional RBF, through adaptive training and ridge regression techniques.