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)

Antifungal activity of flavonoids from Heteropterys byrsonimifolia and a commercial source against Aspergillus ochraceus: In silico interactions of these compounds with a protein kinase

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

INSEL: an in silico method for optimizing and exploring biorecognition assays

A practical in silico method for optimizing and exploring biointeraction-based events is developed.

Análise in silico de uma pirofosfatase e de uma tiosterase de uma biblioteca metagenômica de solo de Eucalipto spp

Pós-graduação em Microbiologia Agropecuária - FCAV

MetaPPase by in silico analyses predicting the novel gene operate as H+ pumps.

The lastyears declined the discovery of compounds to use in industrial and naturaldiversity has been the best supplier for novel genes, enzymes and compounds inhigh demand by the biotechnology industry. We know immense diversity of microorganisms,yet most remains unexplored. For these reason we use the metagenômica approach toinvestigate the potential of uncultured microorganisms. With this purpose weused the metagenomic library of from Eucalyptus spp. arboretum (EAA), wedid screening to found positive clone and them was submitted to the process of shotgun,the data obtained was submitted a bioinformatics analyses. Our results showsthe hypothesis of high unexplored microbial diversity of soil are able to foundnovel genes and metagenomic approach is and allowed to isolate novel genes and insilico analyses are essential part to identify a novel Inorganicpyrophosphatase (PPase) prediction indicated the novel gene operate as H+ pumps. Thissuggests that a special feature, our work in situ will be cloning thegene expression vector for subsequent kinetic characterization and crystallization.

In silico infrared and Raman spectroscopy under pressure: The case of CaSnO3 perovskite

The CaSnO3 perovskite is investigated under geochemical pressure, up to 25 GPa, by means of periodic ab initio calculations performed at B3LYP level with local Gaussian-type orbital basis sets. Structural, elastic, and spectroscopic (phonon wave-numbers, infrared and Raman intensities) properties are fully characterized and discussed. The evolution of the Raman spectrum of CaSnO3 under pressure is reported to remarkably agree with a recent experimental determination [J. Kung, Y. J. Lin, and C. M. Lin, J. Chem. Phys. 135, 224507 (2011)] as regards both wave-number shifts and intensity changes. All phonon modes are symmetry-labeled and bands assigned. The single-crystal total spectrum is symmetry-decomposed into the six directional spectra related to the components of the polarizability tensor. The infrared spectrum at increasing pressure is reported for the first time and its main features discussed. All calculations are performed using the CRYSTAL14 program, taking advantage of the new implementation of analytical infrared and Raman intensities for crystalline materials. (C) 2015 AIP Publishing LLC.