Bioanalytical methods for the metalloproteomics study of bovine longissimus thoracis muscle tissue with different grades of meat tenderness in the Nellore breed (Bos indicus)

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

Structural characterization of novel chemotactic and mastoparan peptides from the venom of the social wasp Agelaia pallipes pallipes by high-performance liquid chromatography/electrospray ionization tandem mass spectrometry

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Análise de inflamassoma induzido por urato monossódico em monócitos de gestantes portadoras de pré-eclampsia

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

Purificação, imobilização e caracterização bioquímica de lipase produzida por Penicillium sect. Gracilenta CBMAI 1583 em cultivo submerso

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Peptide fingerprinting of the neurotoxic fractions isolated from the secretions of sea anemones Stichodactyla helianthus and Bunodosoma granulifera. New members of the APETx-like family identified by a 454 pyrosequencing approach

Sea anemones are known to contain a wide diversity of biologically active peptides, mostly unexplored according to recent peptidomic and transcriptomic studies. In the present work, the neurotoxic fractions from the exudates of Stichodactyla helianthus and Bunodosoma granulifera were analyzed by reversed-phase chromatography and mass spectrometry. The first peptide fingerprints of these sea anemones were assessed, revealing the largest number of peptide components (156) so far found in sea anemone species, as well as the richer peptide diversity of B. granulifera in relation to S. helianthus. The transcriptomic analysis of B. granulifera, performed by massive cDNA sequencing with 454 pyrosequencing approach allowed the discovery of five new APETx-like peptides (U-AITX-Bg1a-e - including the full sequences of their precursors for four of them), which together with type 1 sea anemone sodium channel toxins constitute a very distinguishable feature of studied sea anemone species belonging to genus Bunodosoma. The molecular modeling of these new APETx-like peptides showed a distribution of positively charged and aromatic residues in putative contact surfaces as observed in other animal toxins. On the other hand, they also showed variable electrostatic potentials, thus suggesting a docking onto their targeted channels in different spatial orientations. Moreover several crab paralyzing toxins (other than U-AITX-Bg1a-e), which induce a variety of symptoms in crabs, were isolated. Some of them presumably belong to new classes of crab-paralyzing peptide toxins, especially those with molecular masses below 2 kDa, which represent the smallest peptide toxins found in sea anemones. (C) 2011 Elsevier Inc. All rights reserved.

The Diversity of Polyketide Synthase Genes from Sugarcane-Derived Fungi

The chemical ecology and biotechnological potential of metabolites from endophytic and rhizosphere fungi are receiving much attention. A collection of 17 sugarcane-derived fungi were identified and assessed by PCR for the presence of polyketide synthase (PKS) genes. The fungi were all various genera of ascomycetes, the genomes of which encoded 36 putative PKS sequences, 26 shared sequence homology with beta-ketoacyl synthase domains, while 10 sequences showed homology to known fungal C-methyltransferase domains. A neighbour-joining phylogenetic analysis of the translated sequences could group the domains into previously established chemistry-based clades that represented non-reducing, partially reducing and highly reducing fungal PKSs. We observed that, in many cases, the membership of each clade also reflected the taxonomy of the fungal isolates. The functional assignment of the domains was further confirmed by in silico secondary and tertiary protein structure predictions. This genome mining study reveals, for the first time, the genetic potential of specific taxonomic groups of sugarcane-derived fungi to produce specific types of polyketides. Future work will focus on isolating these compounds with a view to understanding their chemical ecology and likely biotechnological potential.

Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction

In protein databases there is a substantial number of proteins structurally determined but without function annotation. Understanding the relationship between function and structure can be useful to predict function on a large scale. We have analyzed the similarities in global physicochemical parameters for a set of enzymes which were classified according to the four Enzyme Commission (EC) hierarchical levels. Using relevance theory we introduced a distance between proteins in the space of physicochemical characteristics. This was done by minimizing a cost function of the metric tensor built to reflect the EC classification system. Using an unsupervised clustering method on a set of 1025 enzymes, we obtained no relevant clustering formation compatible with EC classification. The distance distributions between enzymes from the same EC group and from different EC groups were compared by histograms. Such analysis was also performed using sequence alignment similarity as a distance. Our results suggest that global structure parameters are not sufficient to segregate enzymes according to EC hierarchy. This indicates that features essential for function are rather local than global. Consequently, methods for predicting function based on global attributes should not obtain high accuracy in main EC classes prediction without relying on similarities between enzymes from training and validation datasets. Furthermore, these results are consistent with a substantial number of studies suggesting that function evolves fundamentally by recruitment, i.e., a same protein motif or fold can be used to perform different enzymatic functions and a few specific amino acids (AAs) are actually responsible for enzyme activity. These essential amino acids should belong to active sites and an effective method for predicting function should be able to recognize them. (C) 2012 Elsevier Ltd. All rights reserved.

The leishmanicidal flavonols quercetin and quercitrin target Leishmania (Leishmania) amazonensis arginase

Polyamine biosynthesis enzymes are promising drug targets for the treatment of leishmaniasis, Chagas' disease and African sleeping sickness. Arginase, which is a metallohydrolase, is the first enzyme involved in polyamine biosynthesis and converts arginine into ornithine and urea. Ornithine is used in the polyamine pathway that is essential for cell proliferation and ROS detoxification by trypanothione. The flavonols quercetin and quercitrin have been described as antitrypanosomal and antileishmanial compounds, and their ability to inhibit arginase was tested in this work. We characterized the inhibition of recombinant arginase from Leishmania (Leishmania) amazonensis by quercetin, quercitrin and isoquercitrin. The IC50 values for quercetin, quercitrin and isoquercitrin were estimated to be 3.8, 10 and 4.3 mu M, respectively. Quercetin is a mixed inhibitor, whereas quercitrin and isoquercitrin are uncompetitive inhibitors of L. (L.) amazonensis arginase. Quercetin interacts with the substrate L-arginine and the cofactor Mn2+ at pH 9.6, whereas quercitrin and isoquercitrin do not interact with the enzyme's cofactor or substrate. Docking analysis of these flavonols suggests that the cathecol group of the three compounds interact with Asp129, which is involved in metal bridge formation for the cofactors Mn-A(2+) and Mn-B(2+) in the active site of arginase. These results help to elucidate the mechanism of action of leishmanicidal flavonols and offer new perspectives for drug design against Leishmania infection based on interactions between arginase and flavones. (C) 2012 Elsevier Inc. All rights reserved.

Calcium Binding to Leptospira Outer Membrane Antigen LipL32 Is Not Necessary for Its Interaction with Plasma Fibronectin, Collagen Type IV, and Plasminogen

LipL32 is the most abundant outer membrane protein from pathogenic Leptospira and has been shown to bind extracellular matrix (ECM) proteins as well as Ca2+. Recent crystal structures have been obtained for the protein in the apo-and Ca2+-bound forms. In this work, we produced three LipL32 mutants (D163-168A, Q67A, and S247A) and evaluated their ability to interact with Ca2+ and with ECM glycoproteins and human plasminogen. The D163-168A mutant modifies aspartate residues involved in Ca2+ binding, whereas the other two modify residues in a cavity on the other side of the protein structure. Loss of calcium binding in the D163-D168A mutant was confirmed using intrinsic tryptophan fluorescence, circular dichroism, and thermal denaturation whereas the Q67A and S247A mutants presented the same Ca2+ affinity as the wild-type protein. We then evaluated if Ca2+ binding to LipL32 would be crucial for its interaction with collagen type IV and plasma proteins fibronectin and plasminogen. Surprisingly, the wild-type protein and all three mutants, including the D163-168A variant, bound to these ECM proteins with very similar affinities, both in the presence and absence of Ca2+ ions. In conclusion, calcium binding to LipL32 may be important to stabilize the protein, but is not necessary to mediate interaction with host extracellular matrix proteins.

Mutation Spectrum in the Large GTPase Dynamin 2, and Genotype-Phenotype Correlation in Autosomal Dominant Centronuclear Myopathy

Centronuclear myopathy (CNM) is a genetically heterogeneous disorder associated with general skeletal muscle weakness, type I fiber predominance and atrophy, and abnormally centralized nuclei. Autosomal dominant CNM is due to mutations in the large GTPase dynamin 2 (DNM2), a mechanochemical enzyme regulating cytoskeleton and membrane trafficking in cells. To date, 40 families with CNM-related DNM2 mutations have been described, and here we report 60 additional families encompassing a broad genotypic and phenotypic spectrum. In total, 18 different mutations are reported in 100 families and our cohort harbors nine known and four new mutations, including the first splice-site mutation. Genotype-phenotype correlation hypotheses are drawn from the published and new data, and allow an efficient screening strategy for molecular diagnosis. In addition to CNM, dissimilar DNM2 mutations are associated with Charcot-Marie-Tooth (CMT) peripheral neuropathy (CMTD1B and CMT2M), suggesting a tissue-specific impact of the mutations. In this study, we discuss the possible clinical overlap of CNM and CMT, and the biological significance of the respective mutations based on the known functions of dynamin 2 and its protein structure. Defects in membrane trafficking due to DNM2 mutations potentially represent a common pathological mechanism in CNM and CMT. Hum Mutat 33: 949-959, 2012. (C) 2012 Wiley Periodicals, Inc.

Algoritmos evolutivos e modelo HP para predição de estruturas de proteínas

Predição de estruturas de proteínas (PSP) é um problema computacionalmente complexo. Modelos simplificados da molécula proteica (como o Modelo HP) e o uso de Algoritmos Evolutivos (AEs) estão entre as principais técnicas investigadas para PSP. Entretanto, a avaliação de uma estrutura representada pelo Modelo HP considera apenas o número de contatos hidrofóbicos, não possibilitando distinguir entre estruturas com o mesmo número de contatos hidrofóbicos. Neste trabalho, é apresentada uma nova formulação multiobjetivo para PSP em Modelo HP. Duas métricas são avaliadas: o número de contatos hidrofóbicos e a distância entre os aminoácidos hidrofóbicos, as quais são tratados pelo AE Multiobjetivo em Tabelas (AEMT). O algoritmo mostrou-se rápido e robusto.

Mechanical Alterations in airway smooth muscle after interaction with indoor pollutant – A mathematical model.

The viscoelasticity of mammalian lung is determined by the mechanical properties and structural regulation of the airway smooth muscle (ASM). The exposure to polluted air may deteriorate these properties with harmful consequences to individual health. Formaldehyde (FA) is an important indoor pollutant found among volatile organic compounds. This pollutant permeates through the smooth muscle tissue forming covalent bonds between proteins in the extracellular matrix and intracellular protein structure changing mechanical properties of ASM and inducing asthma symptoms, such as airway hyperresponsiveness, even at low concentrations. In the experimental scenario, the mechanical effect of FA is the stiffening of the tissue, but the mechanism behind this effect is not fully understood. Thus, the aim of this study is to reproduce the mechanical behavior of the ASM, such as contraction and stretching, under FA action or not. For this, it was created a two-dimensional viscoelastic network model based on Voronoi tessellation solved using Runge-Kutta method of fourth order. The equilibrium configuration was reached when the forces in different parts of the network were equal. This model simulates the mechanical behavior of ASM through of a network of dashpots and springs. This dashpot-spring mechanical coupling mimics the composition of the actomyosin machinery of ASM through the contraction of springs to a minimum length. We hypothesized that formation of covalent bonds, due to the FA action, can be represented in the model by a simple change in the elastic constant of the springs, while the action of methacholine (MCh) reduce the equilibrium length of the spring. A sigmoid curve of tension as a function of MCh doses was obtained, showing increased tension when the muscle strip was exposed to FA. Our simulations suggest that FA, at a concentration of 0.1 ppm, can affect the elastic properties of the smooth muscle ¯bers by a factor of 120%. We also analyze the dynamic mechanical properties, observing the viscous and elastic behavior of the network. Finally, the proposed model, although simple, incorporates the phenomenology of both MCh and FA and reproduces experimental results observed with in vitro exposure of smooth muscle to FA. Thus, this new mechanical approach incorporates several well know features of the contractile system of the cells in a tissue level model. The model can also be used in different biological scales.

Mechanical alterations in airway smooth muscle after interaction with indoor pollutant - A mathematical model

The viscoelasticity of mammalian lung is determined by the mechanical properties and structural regulation of the airway smooth muscle (ASM). The exposure to polluted air may deteriorate these properties with harmful consequences to individual health. Formaldehyde (FA) is an important indoor pollutant found among volatile organic compounds. This pollutant permeates through the smooth muscle tissue forming covalent bonds between proteins in the extracellular matrix and intracellular protein structure changing mechanical properties of ASM and inducing asthma symptoms, such as airway hyperresponsiveness, even at low concentrations. In the experimental scenario, the mechanical effect of FA is the stiffening of the tissue, but the mechanism behind this effect is not fully w1derstood. Thus, the aim of this study is to reproduce the mechanical behavior of the ASM, such as contraction and stretching, under FA action or not. For this, it was created a two-dimensional viscoelastic network model based on Voronoi tessellation solved using Runge-Kutta method of fourth order. The equilibrium configuration was reached when the forces in different parts of the network were equal. This model simulates the mechanical behavior of ASM through of a network of dashpots and springs. This dashpot-spring mechanical coupling mimics the composition of the actomyosin machinery of ASM through the contraction of springs to a minimum length. We hypothesized that formation of covalent bonds, due to the FA action, can be represented in the model by a simple change in the elastic constant of the springs, while the action of methacholinc (MCh) reduce the equilibrium length of the spring. A sigmoid curve of tension as a function of MCh doses was obtained, showing increased tension when the muscle strip was exposed to FA. Our simulations suggest that FA, at a concentration of 0.1 ppm, can affect the elastic properties of the smooth muscle fibers by a factor of 120%. We also analyze the dynamic mechanical properties, observing the viscous and elastic behavior of the network. Finally, the proposed model, although simple, ir1corporates the phenomenology of both MCh and FA and reproduces experirnental results observed with ir1 vitro exposure of smooth muscle to .FA. Thus, this new mechanical approach incorporates several well know features of the contractile system of the cells ir1 a tissue level model. The model can also be used in different biological scales.

Machine learning methods for prediction of disulphide bonding states of cysteine residues in proteins

The goal of this thesis work is to develop a computational method based on machine learning techniques for predicting disulfide-bonding states of cysteine residues in proteins, which is a sub-problem of a bigger and yet unsolved problem of protein structure prediction. Improvement in the prediction of disulfide bonding states of cysteine residues will help in putting a constraint in the three dimensional (3D) space of the respective protein structure, and thus will eventually help in the prediction of 3D structure of proteins. Results of this work will have direct implications in site-directed mutational studies of proteins, proteins engineering and the problem of protein folding. We have used a combination of Artificial Neural Network (ANN) and Hidden Markov Model (HMM), the so-called Hidden Neural Network (HNN) as a machine learning technique to develop our prediction method. By using different global and local features of proteins (specifically profiles, parity of cysteine residues, average cysteine conservation, correlated mutation, sub-cellular localization, and signal peptide) as inputs and considering Eukaryotes and Prokaryotes separately we have reached to a remarkable accuracy of 94% on cysteine basis for both Eukaryotic and Prokaryotic datasets, and an accuracy of 90% and 93% on protein basis for Eukaryotic dataset and Prokaryotic dataset respectively. These accuracies are best so far ever reached by any existing prediction methods, and thus our prediction method has outperformed all the previously developed approaches and therefore is more reliable. Most interesting part of this thesis work is the differences in the prediction performances of Eukaryotes and Prokaryotes at the basic level of input coding when ‘profile’ information was given as input to our prediction method. And one of the reasons for this we discover is the difference in the amino acid composition of the local environment of bonded and free cysteine residues in Eukaryotes and Prokaryotes. Eukaryotic bonded cysteine examples have a ‘symmetric-cysteine-rich’ environment, where as Prokaryotic bonded examples lack it.

Molecular architecture of fur binding to iron-induced and - repressed genes in Helicobacter pylori

The ferric uptake regulator protein Fur regulates iron-dependent gene expression in bacteria. In the human pathogen Helicobacter pylori, Fur has been shown to regulate iron-induced and iron-repressed genes. Herein we investigate the molecular mechanisms that control this differential iron-responsive Fur regulation. Hydroxyl radical footprinting showed that Fur has different binding architectures, which characterize distinct operator typologies. On operators recognized with higher affinity by holo-Fur, the protein binds to a continuous AT-rich stretch of about 20 bp, displaying an extended protection pattern. This is indicative of protein wrapping around the DNA helix. DNA binding interference assays with the minor groove binding drug distamycin A, point out that the recognition of the holo-operators occurs through the minor groove of the DNA. By contrast, on the apo-operators, Fur binds primarily to thymine dimers within a newly identified TCATTn10TT consensus element, indicative of Fur binding to one side of the DNA, in the major groove of the double helix. Reconstitution of the TCATTn10TT motif within a holo-operator results in a feature binding swap from an holo-Fur- to an apo-Fur-recognized operator, affecting both affinity and binding architecture of Fur, and conferring apo-Fur repression features in vivo. Size exclusion chromatography indicated that Fur is a dimer in solution. However, in the presence of divalent metal ions the protein is able to multimerize. Accordingly, apo-Fur binds DNA as a dimer in gel shift assays, while in presence of iron, higher order complexes are formed. Stoichiometric Ferguson analysis indicates that these complexes correspond to one or two Fur tetramers, each bound to an operator element. Together these data suggest that the apo- and holo-Fur repression mechanisms apparently rely on two distinctive modes of operator-recognition, involving respectively the readout of a specific nucleotide consensus motif in the major groove for apo-operators, and the recognition of AT-rich stretches in the minor groove for holo-operators, whereas the iron-responsive binding affinity is controlled through metal-dependent shaping of the protein structure in order to match preferentially the major or the minor groove.