José Gilberto Jardine

Desidratação osmótica de abacaxi aplicada à tecnologia de métodos combinados

O objetivo deste trabalho foi a otimizacao do processo de desidratacao osmotica de abacaxi, visando a obtencao de um produto com maxima perda de agua e minima incorporacao de solidos. O processo foi aplicado a Tecnologia de Metodos Combinados, em que a reducao na atividade de agua foi combinada a reducao no pH e uso de conservantes, todos aplicados em baixos niveis, a fim de se obter um produto similar a fruta fresca. O experimento foi dividido em 3 tratamentos, a saber: pedacos de abacaxi nao revestidos (A), revestidos com cobertura de alginato (B) e revestidos com cobertura de pectina de baixa metoxilacao (C). O processo envolveu as etapas principais: inativacao enzimatica de pedacos da fruta; para os tratamentos B e C, revestimento da fruta com as respectivas coberturas; e desidratacao osmotica em solucao de sacarose contendo sorbato de potassio e acido citrico. As condicoes otimas do processo, determinadas a partir da Metodologia de Superficie de Resposta, foram as seguintes: desidratacao da fruta revestida com alginato, a temperaturas na faixa de 42 a 47° C, em xarope de sacarose a 66-69° Brix, por 220 a 270 minutos. Os resultados indicaram que as coberturas afetaram significativamente as transferencias de massa do processo, reduzindo a incorporacao de solidos e aumentando a perda de umidade, com consequente aumento na perda de massa e aumento na relacao de performance (perda de umidade: incorporacao de solidos); a atividade de agua final do produto nao foi afetada de forma marcante pela presenca das coberturas. O produto obtido sob condicoes otimizadas foi submetido a avaliacao sensorial de aceitacao, tendo apresentado boa aceitacao geral. Uma avaliacao da estabilidade microbiologica do produto, feita por meio de contagem de bolores e leveduras, mostrou boa estabilidade do produto por pelo menos 60 dias a 30oC.

Influência da época de corte sobre o teor de açúcares de colmos de sorgo sacarino

High energy sorghum (Sorghum bicolor (L.) Moench) cultivars have been recently developed for grain and biomass production. Whole plant utilization is the target of this concept. The objective of this study was to identify the relationship between the harvest date and biomass yield. Experimental trials were conducted with the cultivar BR 505 in the years 1984/85, 1985/86 and 1986/87 to determine its performance as a high energy crop. High biomass and sugar yields were obtained at the physiological maturity stage of the plants. Sucrose and total sugars of the plant increased continually from the visible spikelet stage to the physiological maturity. However, reducing sugar level showed a fall over the same period. In the years 1984/85 and 1985/86 the total biomass yield was 38.9 and 52.0 t/ha respectively. Late sowing date which occurred in the year 1986/87 and the elimination of the supplementary N fertilization reduced significantly the biomass yield as well as the sugar level in the stalks. Grain production of the complementary N fertilization was not affected significantly.

Utilização do sorgo sacarino como matéria-prima complementar à cana-de-açúcar para obtenção de etanol em microdestilaria

Sweet Sorghum has been evaluated as a complementary source of raw material for ethanol production in microdistillery. Sorghum culms can be processed in the same installation utilized for the production of ethanol from sugar cane, giving an ample fiber residue (bagasse) to generate enough steam for industrial operation. The results obtained in a two years experimental work showed that sweet sorghum cultivar Br 505 could be a recommendable alternate crop to complement sugar cane in the production of ethanol in microdistillery. The total reducing sugar content of the culms was not significantly different when compared to those of sugar cane earlier harvested. The culms presented a total reducing sugar content of 33 to 40%, on dry basis. In this case the utilization of sweet sorghum culms between the sugar cane harvesting season can reduce the microdistillery inactive period. Besides the grains, the distillery residues and by-products can be used in other activities directed to food production in the rural property. The utilization of the two crops as raw material for alcohol production in microdistillery can provide a better use of sugar cane after reaching complete maturity present high sugar content in the culms.

Improving Predictions of Protein-Protein Interfaces by Combining Amino Acid-Specific Classifiers Based on Structural and Physicochemical Descriptors with Their Weighted Neighbor Averages

Protein-protein interactions are involved in nearly all regulatory processes in the cell and are considered one of the most important issues in molecular biology and pharmaceutical sciences but are still not fully understood. Structural and computational biology contributed greatly to the elucidation of the mechanism of protein interactions. In this paper, we present a collection of the physicochemical and structural characteristics that distinguish interface-forming residues (IFR) from free surface residues (FSR). We formulated a linear discriminative analysis (LDA) classifier to assess whether chosen descriptors from the BlueStar STING database (http://www.cbi.cnptia.embrapa.br/SMS/) are suitable for such a task. Receiver operating characteristic (ROC) analysis indicates that the particular physicochemical and structural descriptors used for building the linear classifier perform much better than a random classifier and in fact, successfully outperform some of the previously published procedures, whose performance indicators were recently compared by other research groups. The results presented here show that the selected set of descriptors can be utilized to predict IFRs, even when homologue proteins are missing (particularly important for orphan proteins where no homologue is available for comparative analysis/indication) or, when certain conformational changes accompany interface formation. The development of amino acid type specific classifiers is shown to increase IFR classification performance. Also, we found that the addition of an amino acid conservation attribute did not improve the classification prediction. This result indicates that the increase in predictive power associated with amino acid conservation is exhausted by adequate use of an extensive list of independent physicochemical and structural parameters that, by themselves, fully describe the nano-environment at protein-protein interfaces. The IFR classifier developed in this study is now integrated into the BlueStar STING suite of programs. Consequently, the prediction of protein-protein interfaces for all proteins available in the PDB is possible through STING_interfaces module, accessible at the following website: (http://www.cbi.cnptia.embrapa.br/SMS/predictions/index.html).

Efeito da adição de solutos e ácidos em poupa de goiaba

The capacities of added sucrose, glucose, invert sugar and glycerol to decrease water activity (aw) of guava pulp (15° Brix) were compared. Added fosforic, citric and lactic acids were also assessed for their effects in pH reduction as well as in increasing titritable acidity in pulp. Theoretical, experimental and calculated aw values were compared as a function of solute addition. Norrish model was used to determine theoretical aw values and Ross equation to generate calculated aw values using experimental ones. Acidity and pH curves were determined according to titrimetric and potentiometric assays, respectively. Glycerol exhibited the strongest capacity regarding aw reduction, followed by glucose, sucrose and invert sugar. In concentrations up to 1% w/w, all tested acids showed similar effects in decreasing pH and increasing titritable acidity of guava pulp.

Study of specific nanoenvironments containing [alfa]-helices in all-[alfa] and ([alfa]+[beta])+([alfa]/[beta]) proteins.

Protein secondary structure elements (PSSEs) such as α-helices, β-strands, and turns are the primary building blocks of the tertiary protein structure. Our primary interest here is to reveal the characteristics of the nanoenvironment formed by both PSSEs and their surrounding amino acid residues (AARs), which might contribute to the general understanding of how proteins fold. The characteristics of such nanoenvironments must be specific to each secondary structure element, and we have set our goal here to gather the fullest possible description of the α-helical nanoenvironment. In general, this postulate (the existence of specific nanoenvironments for specific protein substructures/neighbourhoods/regions with distinct functionality) was already successfully explored and confirmed for some protein regions, such as protein-protein interfaces and enzyme catalytic sites. Consequently, PSSEs were the obvious next choice for additional work for further evidence showing that specific nanoenvironments (having characteristics fully describable by means of structural and physical chemical descriptors) do exist for the corresponding and determined intraprotein regions. The nanoenvironment of α-helices (nEoαH) is defined as any region of the protein where this secondary structure element type is detected. The nEoαH, therefore, includes not only the α-helix amino acid residues but also the residues immediately around the α-helix. The hypothesis that motivated this work is that it might in fact be possible to detect a postulated “signal” or “signature” that distinguishes the specific location of α-helices. This “signal” must be discernible by tracking differences in the values of physical, chemical, physicochemical, structural and geometric descriptors immediately before (or after) the PSSE from those in the region along the α-helices. The search for this specific nanoenvironment “signal” was made possible by aligning previously selected α-helices of equal length. Afterward, we calculated the average value, standard deviation and mean square error at each aligned residue position for each selected descriptor. We applied Student’s t-test, the Kolmogorov-Smirnov test and MANOVA statistical tests to the dataset constructed as described above, and the results confirmed that the hypothesized “signal”/“signature” is both existing/identifiable and capable of distinguishing the presence of an α-helix inside the specific nanoenvironment, contextualized as a specific region within the whole protein. However, such conclusion might rarely be reached if only one descriptor is considered at a time. A more accurate signal with broader coverage is achieved only if one applies multivariate analysis, which means that several descriptors (usually approximately 10 descriptors) should be considered at the same time. To a limited extent (up to a maximum of 15% of cases), such conclusion is also possible with only a single descriptor, and the conclusion is also possible in general for up to 50–80% of cases when no less than 5 nonlinear descriptors are selected and considered. Using all the descriptors considered in this work, provided all assumptions about data characteristics for this analysis are met, multivariate analysis regularly reached a coverage and accuracy above 90%. Understanding how secondary structure elements are formed and maintained within a protein structure could enable a more detailed understanding of how proteins reach their final 3D structure and consequently, their function. Likewise, this knowledge may also improve the tools used to determine how good a structure is by means of comparing the “signal” around a selected PSSE with the one obtained from the best (resolution and quality wise) protein structures available.

Multiple structure single parameter: analysis of a single protein nano environment descriptor characterizing a shared loci on structurally aligned proteins.

MOTIVATION A graphical representation of physicochemical and structural descriptors attributed to amino acid residues occupying the same topological position in different, structurally aligned proteins can provide a more intuitive way to associate possible functional implications to identified variations in structural characteristics. This could be achieved by observing selected characteristics of amino acids and of their corresponding nano environments, described by the numerical value of matching descriptor. For this purpose, a web-based tool called multiple structure single parameter (MSSP) was developed and here presented. RESULTS MSSP produces a two-dimensional plot of a single protein descriptor for a number of structurally aligned protein chains. From a total of 150 protein descriptors available in MSSP, selected of >1500 parameters stored in the STING database, it is possible to create easily readable and highly informative XY-plots, where X-axis contains the amino acid position in the multiple structural alignment, and Y-axis contains the descriptors numerical values for each aligned structure. To illustrate one of possible MSSP contributions to the investigation of changes in physicochemical and structural properties of mutants, comparing them with the cognate wild-type structure, the oncogenic mutation of M918T in RET kinase is presented. The comparative analysis of wild-type and mutant structures shows great changes in their electrostatic potential. These variations are easily depicted at the MSSP-generated XY-plot. AVAILABILITY AND IMPLEMENTATION The web server is freely available at http://www.cbi.cnptia.embrapa.br/SMS/STINGm/MPA/index.html Web server implemented in Perl, Java and JavaScript and JMol or Protein Viewer as structure visualizers. CONTACT goran.neshich@embrapa.br or gneshich@gmail.com SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Using Structural and Physical–Chemical Parameters to Identify, Classify, and Predict Functional Districts in Proteins—The Role of Electrostatic Potential

In this chapter, we will overview the role of the local protein structure environment (which we will call here: nano-environment) in maintaining the functional purpose of different protein districts (defined as protein structure sites delimited by their functional objectives). Namely, we suggest that the local environment at each protein point and/or region reflects, not only its constitutional/structural role, but also its contribution to providing necessary and required characteristics for the functional objective that such particular site is supposed to have. For instance, protein–protein communication is executed through protein interfaces, and amino acid residues belonging to that site must have some specific characteristics which do not only differentiate them from the free surface residues, but also make possible that two very specific proteins may engage, bind and by doing so, perform their function. Similarly, enzyme function is normally related to activity of its catalytic site residues (CSRs). Obviously, these very peculiar residues are embedded in a very specific nano-environment (defined also by the contribution of CSR). Consequently, the enzyme function could be described in terms of characteristics of the CSRs and their surroundings. Based on the above considerations, and assuming that the local nano-environment is not only defining the protein district function, but it is also a concept for which we can design specific metrics to quantify it, and a specific set of properties to describe it, we studied the role of different descriptors and found that, together with hydrophobicity, electrostatic potential is of fundamental importance. As we will better detail in the course of this work, the electrostatic potential might not always be the top ranked property defining the nano-environment of interest, but it is, however, always present, contributing significantly in carving proper protein district characteristics for specific structure/function purposes.