Enzymatic inhibitory activity of hydroxycinnamates (HCs): in silico studies

Diabetes is a worldwide health issue that has been expanding mainly in developed countries. It is characterized by abnormal levels of blood sugar due to several factors. The most common are resistance to insulin and the production of defective insulin which exerts little or no effect. Its most common symptoms include tissue damage to several systems due to elevated levels of blood sugar. One of the key enzymes in hydrocarbon metabolism is α-glucosidase (EC 3.2.1.20). It catalyzes the breakdown of complex carbohydrates into their respective monomers (glucose) which allows them to be absorbed. In this work, caffeoyl quinic acids and their metabolites were analyzed as potential inhibitors for α-glucosidase. The search for the best inhibitor was conducted using molecular docking. The affinity of each compound was compared to the inhibitor present in the crystal structure of the protein. As no inhibitor with a similar affinity was´found, a new approach was used, in situ drug design. It was not possible to achieve an inhibitor capable of competing with the one present in the crystal structure of the enzyme, which is also its current commercial inhibitor. It is possible to draw some conclusions as to which functional groups interact best with certain residues of the active site. This work was divided into three main sections. The first section, Diabetes, serves as an introduction to what is Diabetes, its symptoms and/or side effects and how caffeoyl quinic acids could be used as a treatment. The second section, Caffeoylquinic acids and their metabolites as inhibitors for Alfa-glucosidase, corresponds to the search through molecular docking of caffeoyl quinic acids as inhibitors for α-glucosidase and what was possible to draw from this search. The last section, In situ design of an inhibitor for α-glucosidase (EC 3.2.1.20), corresponds to the in situ drug design study and what it achieved. The representation of each of the molecules used as a ligand can be found in the Annexes.

Construção de modelos de interação in silico e in vitro do inibidor do tipo Kunitz de Adenanthera pavonina L. para as enzimas cisteínicas e serínicas

Serines proteinases inhibitors (PIs) are widely distributed in nature and are able to inhibit both in vitro and in vivo enzymatic activites. Seed PIs in than leguminous are classified in seven families, Bowman-Birk and Kunitz type families that most studied representing an important role in the first line of defense toward insects pests. Some Kunitz type inhibitors possess activities serine and cysteine for proteinases named bifunctional inhibitor, as ApTKI the inhibitor isolate from seed of Adenanthera pavonina. The A. pavonina inhibitor presenting the uncommon property and was used for interaction studies between proteinases serine (trypsin) and cysteine (papain). In order to determinate the in vitro interaction of ApTKI against enzymes inhibitor purification was carried cut by using chromatographic techniques and inhibition assays. The 3D model of the bifunctional inhibitor ApTKI was constructed SWISS-MODEL program by homology modeling using soybean trypsin inhibitor (STI, pdb:1ba7), as template which presented 40% of identity to A. pavonina inhibitor. Model quality was evaluated by PROCHECK program. Moreover in silico analyzes of formed complex between the enzymes and ApTKI was evaluated by HEX 4.5 program. In vitro results confirmed the inhibitory assays, where the inhibitor presented the ability to simultaneously inhibit trypsin and papain. The residues encountered in the inhibitor model of folder structural three-dimensional that make contact to enzymes target coud explain the specificity pattern against serine and cysteine proteinases

Determinação de motivos de ligação à quitina em vicilinas de Canavalia ensiformis e Vigna unguiculata através de métodos in silico e relação com suas toxicidades para o bruquídeo Callosobruchus maculatus (Coleoptera:Bruchidae)

Chitin is an important structural component of the cellular wall of fungi and exoskeleton of many invertebrate plagues, such as insects and nematodes. In digestory systems of insects it forms a named matrix of peritrophic membrane. One of the most studied interaction models protein-carbohydrate is the model that involves chitin-binding proteins. Among the involved characterized domains already in this interaction if they detach the hevein domain (HD), from of Hevea brasiliensis (Rubber tree), the R&R consensus domain (R&R), found in cuticular proteins of insects, and the motif called in this study as conglicinin motif (CD), found in the cristallography structure of the β-conglicinin bounded with GlcNac. These three chitin-binding domains had been used to determine which of them could be involved in silico in the interaction of Canavalia ensiformis and Vigna unguiculata vicilins with chitin, as well as associate these results with the WD50 of these vicilins for Callosobruchus maculatus larvae. The technique of comparative modeling was used for construction of the model 3D of the vicilin of V. unguiculata, that was not found in the data bases. Using the ClustalW program it was gotten localization of these domains in the vicilins primary structure. The domains R&R and CD had been found with bigger homology in the vicilins primary sequences and had been target of interaction studies. Through program GRAMM models of interaction ( dockings ) of the vicilins with GlcNac had been gotten. The results had shown that, through analysis in silico, HD is not part of the vicilins structures, proving the result gotten with the alignment of the primary sequences; the R&R domain, although not to have structural similarity in the vicilins, probably it has a participation in the activity of interaction of these with GlcNac; whereas the CD domain participates directly in the interaction of the vicilins with GlcNac. These results in silico show that the amino acid number, the types and the amount of binding made for the CD motif with GlcNac seem to be directly associates to the deleterious power that these vicilins show for C. maculatus larvae. This can give an initial step in the briefing of as the vicilins interact with alive chitin in and exert its toxic power for insects that possess peritrophic membrane

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)

Use of reverse transcriptase polymerase chain reaction (RT-PCR) in molecular screening of Newcastle disease virus in poultry and free-living bird populations

The aim of this study was to evaluate a simple molecular method of reverse transcriptase polymerase chain reaction (RT-PCR) to differentiate Newcastle disease virus strains according to their pathogenicity, in order to use it in molecular screening of Newcastle disease virus in poultry and free-living bird populations. Specific primers were developed to differentiate LaSota-LS-(vaccine strain) and Sao Joao do Meriti-SJM-strain (highly pathogenic strain). Chickens and pigeons were experimentally vaccinated/infected for an in vivo study to determine virus shedding in feces. Validation of sensitivity and specificity of the primers (SJM and LS) by experimental models used in the present study and results obtained in the molecular analysis of the primers by BLAST made it possible to generalize results. The development of primers that differentiate the level of pathogenicity of NDV stains is very important, mainly in countries where real-time RT-PCR is still not used as a routine test. These primers were able to determine the presence of the agent and to differentiate it according to its pathogenicity. © 2012 Springer Science+Business Media B.V.

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)