Protein content and amino acid composition of some varieties of grain sorghum

Determination of the protein content and lysine levels of a number of nonhybrid varieties of grain sorghum indicates large variations in the protein content. Statistical analysis of data on amounts of lysine shows that a negative correlation exists between per cent lysine in the protein and per cent protein in the seed. The proportion of various protein fractions in endosperm of five varieties of grain sorghum of both low- and high-protein type has been determined. Results show that prolamine and glutelin are the principal protein fractions, and increased protein levels in sorghum varieties are correlated with an increase mainly in the prolamine fraction. Nine high- and low-protein varieties of grain sorghum have been analyzed for their amino acid composition by ion exchange procedures. One of the high-protein genetic varieties of sorghum has a high concentration of lysine in the seed. Amino acid composition of the protein fractions of two varieties is also reported. These data permit an evaluation of the nutritional quality of sorghum protein and factors that influence the quality of the protein.

Nutritive value of fish of Lake Tanganyika [part] I: Amino acid composition

The amino acid composition was determined of three economic important fish species of Lake Tanganyika, representing 95% of the tolal catch:Stolothrissa tanganicae Regan, Limnothrissa miodon Boulenger and Luciolates stapersii Boulenger. The analysis of the whole sun dried fish indicate that, compared with Tilapia macrochir, beef and the whole hen's egg, the fish is of a very high nutritive value. The free amino acids in the dried fish count for an average of 11 %, indicating the degree of auteolysis.

Amino acid composition of processed fish silage using different raw materials

The objective was to evaluate amino acid composition of silages produced from three raw materials. Commercial marine fish waste, commercial freshwater fish waste, and tilapia filleting residue were used to produce fish silage by acid digestion (20 ml/kg formic acid and 20 ml/kg sulfuric acid) and anaerobic fermentation (50 g/kg Lactobacillus plantarum, 150 g/kg sugar cane molasses). Protein content and amino acid composition were determined for raw materials and silage. Marine fish waste had higher crude protein content (776.7 g/kg) compared to freshwater fish waste (496.2 g/kg) and tilapia filleting residue (429.9 g/kg). All silages lacked up to three amino acids for each product according to FAO standards for essential amino acids. However, considering as the limiting factor only the amino acids below the 30% minimum requirement for fish in general, all products were satisfactory with respect to essential amino acids. Therefore, the results suggest that all products investigated are appropriate for use in balanced fish diets. (C) 2003 Elsevier B.V. B.V. All rights reserved.

Mycorrhization alters foliar soluble amino acid composition and influences tolerance to Pb in Calopogonium mucunoides

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Amino acid composition of the proteins of the serum lipoproteins /

Unclassified Health and Biology.

The amino acid composition of proteins and foods; analytical methods and results,

Bibliography: p. 311-350.

Identification of DNA-binding proteins by incorporating evolutionary information into pseudo amino acid composition via the top-n-gram approach

DNA-binding proteins are crucial for various cellular processes and hence have become an important target for both basic research and drug development. With the avalanche of protein sequences generated in the postgenomic age, it is highly desired to establish an automated method for rapidly and accurately identifying DNA-binding proteins based on their sequence information alone. Owing to the fact that all biological species have developed beginning from a very limited number of ancestral species, it is important to take into account the evolutionary information in developing such a high-throughput tool. In view of this, a new predictor was proposed by incorporating the evolutionary information into the general form of pseudo amino acid composition via the top-n-gram approach. It was observed by comparing the new predictor with the existing methods via both jackknife test and independent data-set test that the new predictor outperformed its counterparts. It is anticipated that the new predictor may become a useful vehicle for identifying DNA-binding proteins. It has not escaped our notice that the novel approach to extract evolutionary information into the formulation of statistical samples can be used to identify many other protein attributes as well.

Amino acid composition of processed fish silage using different raw materials

The objective was to evaluate amino acid composition of silages produced from three raw materials. Commercial marine fish waste, commercial freshwater fish waste, and tilapia filleting residue were used to produce fish silage by acid digestion (20 ml/kg formic acid and 20 ml/kg sulfuric acid) and anaerobic fermentation (50 g/kg Lactobacillus plantarum, 150 g/kg sugar cane molasses). Protein content and amino acid composition were determined for raw materials and silage. Marine fish waste had higher crude protein content (776.7 g/kg) compared to freshwater fish waste (496.2 g/kg) and tilapia filleting residue (429.9 g/kg). All silages lacked up to three amino acids for each product according to FAO standards for essential amino acids. However, considering as the limiting factor only the amino acids below the 30% minimum requirement for fish in general, all products were satisfactory with respect to essential amino acids. Therefore, the results suggest that all products investigated are appropriate for use in balanced fish diets. (C) 2003 Elsevier B.V. B.V. All rights reserved.

Composition and amino acid content of meal from some commercially less important fishes of Maharashtra

Details are given of the yield and composition of dried waste from the filleting wastes of 3 commercially less utilized fish of the Maharashtra coast (Saurida tumbil, Caranx sexfasciatus and Sphyraena jello). The amino acid composition after acid hydrolysis is detailed for the three species.

Analysis and prediction of major blood proteins based on their amino acid and dipeptide composition

A method has been developed for predicting blood proteins using the SVM based machine learning approach. In this prediction method a two-step strategy was deployed to predict blood proteins and their subclasses. We have developed models of blood proteins and achieved the maximum accuracies of 90.57% and 91.39% with Matthews correlation coefficient (MCC) of 0.89 and 0.90 using single amino acid and dipeptide composition respectively. Furthermore, the method is able to predict major subclasses of blood proteins; developed based on amino acid (AC) and dipeptide composition (DC) with a maximum accuracy 90.38%, 92.83%, 87.41%, 92.52% and 85.27%, 89.07%, 94.82%, 86.31 for albumin, globulin, fibrinogen, and regulatory proteins respectively. All modules were trained, tested, and evaluated using the five-fold cross-validation technique.

STUDIES ON THE PATTERNS OF NUCLEOTIDE AND AMINO ACID SUBSTITUTION (ELECTROPHORESIS, MUTATION RATE, SELECTION, BASE, COMPOSITION)

Theoretical and empirical studies were conducted on the pattern of nucleotide and amino acid substitution in evolution, taking into account the effects of mutation at the nucleotide level and purifying selection at the amino acid level. A theoretical model for predicting the evolutionary change in electrophoretic mobility of a protein was also developed by using information on the pattern of amino acid substitution. The specific problems studied and the main results obtained are as follows: (1) Estimation of the pattern of nucleotide substitution in DNA nuclear genomes. The pattern of point mutations and nucleotide substitutions among the four different nucleotides are inferred from the evolutionary changes of pseudogenes and functional genes, respectively. Both patterns are non-random, the rate of change varying considerably with nucleotide pair, and that in both cases transitions occur somewhat more frequently than transversions. In protein evolution, substitution occurs more often between amino acids with similar physico-chemical properties than between dissimilar amino acids. (2) Estimation of the pattern of nucleotide substitution in RNA genomes. The majority of mutations in retroviruses accumulate at the reverse transcription stage. Selection at the amino acid level is very weak, and almost non-existent between synonymous codons. The pattern of mutation is very different from that in DNA genomes. Nevertheless, the pattern of purifying selection at the amino acid level is similar to that in DNA genomes, although selection intensity is much weaker. (3) Evaluation of the determinants of molecular evolutionary rates in protein-coding genes. Based on rates of nucleotide substitution for mammalian genes, the rate of amino acid substitution of a protein is determined by its amino acid composition. The content of glycine is shown to correlate strongly and negatively with the rate of substitution. Empirical formulae, called indices of mutability, are developed in order to predict the rate of molecular evolution of a protein from data on its amino acid sequence. (4) Studies on the evolutionary patterns of electrophoretic mobility of proteins. A theoretical model was constructed that predicts the electric charge of a protein at any given pH and its isoelectric point from data on its primary and quaternary structures. Using this model, the evolutionary change in electrophoretic mobilities of different proteins and the expected amount of electrophoretically hidden genetic variation were studied. In the absence of selection for the pI value, proteins will on the average evolve toward a mildly basic pI. (Abstract shortened with permission of author.) ^

A two-stage SVM method to predict membrane protein types by incorporating amino acid classifications and physicochemical properties into a general form of Chou's PseAAC

Membrane proteins play important roles in many biochemical processes and are also attractive targets of drug discovery for various diseases. The elucidation of membrane protein types provides clues for understanding the structure and function of proteins. Recently we developed a novel system for predicting protein subnuclear localizations. In this paper, we propose a simplified version of our system for predicting membrane protein types directly from primary protein structures, which incorporates amino acid classifications and physicochemical properties into a general form of pseudo-amino acid composition. In this simplified system, we will design a two-stage multi-class support vector machine combined with a two-step optimal feature selection process, which proves very effective in our experiments. The performance of the present method is evaluated on two benchmark datasets consisting of five types of membrane proteins. The overall accuracies of prediction for five types are 93.25% and 96.61% via the jackknife test and independent dataset test, respectively. These results indicate that our method is effective and valuable for predicting membrane protein types. A web server for the proposed method is available at http://www.juemengt.com/jcc/memty_page.php