Estudo in silico da interação da albumina de soro humano com o ibuprofeno

Currently, computational methods have been increasingly used to aid in the characterization of molecular biological systems, especially when they relevant to human health. Ibuprofen is a nonsteroidal antiinflammatory or broadband use in the clinic. Once in the bloodstream, most of ibuprofen is linked to human serum albumin, the major protein of blood plasma, decreasing its bioavailability and requiring larger doses to produce its antiinflamatory action. This study aimes to characterize, through the interaction energy, how is the binding of ibuprofen to albumin and to establish what are the main amino acids and molecular interactions involved in the process. For this purpouse, it was conducted an in silico study, by using quantum mechanical calculations based on Density Functional Theory (DFT), with Generalized Gradient approximation (GGA) to describe the effects of exchange and correlation. The interaction energy of each amino acid belonging to the binding site to the ligand was calculated the using the method of molecular fragmentation with conjugated caps (MFCC). Besides energy, we calculated the distances, types of molecular interactions and atomic groups involved. The theoretical models used were satisfactory and show a more accurate description when the dielectric constant ε = 40 was used. The findings corroborate the literature in which the Sudlow site I (I-FA3) is the primary binding site and the site I-FA6 as secondary site. However, it differs in identifying the most important amino acids, which by interaction energy, in order of decreasing energy, are: Arg410, Lys414, Ser 489, Leu453 and Tyr411 to the I-Site FA3 and Leu481, Ser480, Lys351, Val482 and Arg209 to the site I-FA6. The quantification of interaction energy and description of the most important amino acids opens new avenues for studies aiming at manipulating the structure of ibuprofen, in order to decrease its interaction with albumin, and consequently increase its distribution

Floração precoce em cana-de-açúcar - um estudo utilizando ferramentas de análise in silico e proteômica

Sugarcane is one of the most important products of the world and Brazil is responsible for 25 % of the world production. One problem of this culture at northeast of Brazil is the early flowering. In our laboratory, it has been made before four subtractive libraries using early and late flowering genotypes in order to identify messages related to the flowering process. In this work, two cDNAs were chosen to make in silico analysis and overexpression constructs. Another approach to understand the flowering process in sugarcane was to use proteomic tools. First, the protocol for protein extraction using apical meristem was set up. After that, these proteins were separated on two bidimensional gels. It was possible to observe some difference for some regions of these gels as well as some proteins that can be found in all conditions. The next step, spots will be isolated and sequence on MS spectrometry in order to understand this physiological process in sugarcane

Estudos in silico da proteína AlkB e prospecção de bactérias alcanotróficas em solos da bacia petrolífera potiguar

Some microorganisms from virgin ecosystems are able to use petroleum it as source of carbon and energy. The knowledge of microbial biodiversity can help to reveal new metabolic systems for utilization alkanes with biotechnological importance. The aim of this study is: i) Accomplish an in silico study of the AlkB protein aimed to understand the probable mechanism involved on selectivity of alkanes in Gram positive and Gram negative bactéria. ii) prospect and analyze the response of the microbial alkanotrophics communities in soil and mangrove sediments of BPP RN and soil of Atlantic forest in the Horto Dois Irmãos Reserve area/PE using the molecular biomarker, gene alkB; with the PCR and PCR-DGGE approach

Highly polymorphic in silico-derived microsatellite loci in the potato-infecting fungal pathogen Rhizoctonia solani anastomosis group 3 from the Colombian Andes

Fourteen polymorphic microsatellite DNA markers derived from the draft genome sequence of Rhizoctonia solani anastomosis group 3 (AG-3), strain Rhs 1AP, were designed and characterized from the potato-infecting soil fungus R. solani AG-3. All loci were polymorphic in two field populations collected from Solanum tuberosum and S. phureja in the Colombian Andes. The total number of alleles per locus ranged from two to seven, while gene diversity (expected heterozygosity) varied from 0.11 to 0.81. Considering the variable levels of genetic diversity observed, these markers should be useful for population genetic analyses of this important dikaryotic fungal pathogen on a global scale.

In silico network topology-based prediction of gene essentiality

The identification of genes essential for survival is important for the understanding of the minimal requirements for cellular life and for drug design. As experimental studies with the purpose of building a catalog of essential genes for a given organism are time-consuming and laborious, a computational approach which could predict gene essentiality with high accuracy would be of great value. We present here a novel computational approach, called NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on the network topology features of a gene to estimate its essentiality. The first step of NTPGE is to construct the integrated molecular network for a given organism comprising protein physical, metabolic and transcriptional regulation interactions. The second step consists in training a decision-tree-based machine-learning algorithm on known essential and non-essential genes of the organism of interest, considering as learning attributes the network topology information for each of these genes. Finally, the decision-tree classifier generated is applied to the set of genes of this organism to estimate essentiality for each gene. We applied the NTPGE approach for discovering the essential genes in Escherichia coli and then assessed its performance. (C) 2007 Elsevier B.V. All rights reserved.

Boron transport in Eucalyptus. 2. Identification in silico of a putative boron transporter for xylem loading in eucalypt

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

In silico evaluation of the Eucalyptus transcriptome

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The Development of a Universal In Silico Predictor of Protein-Protein Interactions

Protein-protein interactions (PPIs) are essential for understanding the function of biological systems and have been characterized using a vast array of experimental techniques. These techniques detect only a small proportion of all PPIs and are labor intensive and time consuming. Therefore, the development of computational methods capable of predicting PPIs accelerates the pace of discovery of new interactions. This paper reports a machine learning-based prediction model, the Universal In Silico Predictor of Protein-Protein Interactions (UNISPPI), which is a decision tree model that can reliably predict PPIs for all species (including proteins from parasite-host associations) using only 20 combinations of amino acids frequencies from interacting and non-interacting proteins as learning features. UNISPPI was able to correctly classify 79.4% and 72.6% of experimentally supported interactions and non-interacting protein pairs, respectively, from an independent test set. Moreover, UNISPPI suggests that the frequencies of the amino acids asparagine, cysteine and isoleucine are important features for distinguishing between interacting and non-interacting protein pairs. We envisage that UNISPPI can be a useful tool for prioritizing interactions for experimental validation. © 2013 Valente et al.

Análise in silico de um novo “cluster” de PKS II Metagenômico

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Detecção in silico, isolamento e caracterização estrutural dos constitutintes micromoleculares antimaláricos e antioxidantes em galhosmdemGarcina gardneriana (Clusiaceae)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Detecção in silico dos constituintes majoritários de Strychnos brasiliensis e S. pseudoquina (Loganiaceae) usando CLAE-DAD/EMAR

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estudo de Jatropha gossypifolia e J. multifida (Euphorbiaceae) aplicando métodos analíticos in silico e de desreplicação, visando a detecção e elucidação in situ dos constituintes micromoleculares com atividade acetilcolinesterásicas e antioxidante

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Detecção in silico e caracterização estrutural dos constituintes micromoleculares majoritários presentes no fungo endofitico Phomopsis stipata isolado de folhas de Styrax camporum Pohl (Styracaceae) usando CLAE-DAD/EMAR e CG-MS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Detecção in silico e caracterização dos constituintes micromoleculares majoritários do fungo endofítico Colletotrichum gloeosporioides isolado de folhas de Garcinia xanthochymus usando HPLC-DAD-HRMS e GC-MS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)