Tuning the amino acid sequence of minimalist peptides to present biological signals via charge neutralised self assembly

Nanofibrous materials yielded by the self-assembly of peptides are rich in potential; particularly for the formation of scaffolds that mimic the landscape of the host environment of the cell. Here, we report a novel methodology to direct the formation of supramolecular structures presenting desirable amino acid sequences by the self-assembly of minimalist peptides which cannot otherwise yield the desired scaffold structures under biologically relevant conditions. Through the rational modification of the pK?, we were able to optimise ordered charge neutralised assembly towards in vivo conditions.

Binding affinities of amino acid analogues at the charged aqueous titania interface : implications for titania-binding peptides

Despite the extensive utilization of biomolecule-titania interfaces, biomolecular recognition and interactions at the aqueous titania interface remain far from being fully understood. Here, atomistic molecular dynamics simulations, in partnership with metadynamics, are used to calculate the free energy of adsorption of different amino acid side chain analogues at the negatively-charged aqueous rutile TiO2 (110) interface, under conditions corresponding with neutral pH. Our calculations predict that charged amino acid analogues have a relatively high affinity to the titania surface, with the arginine analogue predicted to be the strongest binder. Interactions between uncharged amino acid analogues and titania are found to be repulsive or weak at best. All of the residues that bound to the negatively-charged interface show a relatively stronger adsorption compared with the charge-neutral interface, including the negatively-charged analogue. Of the analogues that are found to bind to the titania surface, the rank ordering of the binding affinities is predicted to be "arginine" > "lysine" ≈ aspartic acid > "serine". This is the same ordering as was found previously for the charge-neutral aqueous titania interface. Our results show very good agreement with available experimental data and can provide a baseline for the interpretation of peptide-TiO2 adsorption data.

Structural classification of proteins through amino acid sequence using interval type-2 fuzzy logic system

This paper introduces a new multi-output interval type-2 fuzzy logic system (MOIT2FLS) that is automatically constructed from unsupervised data clustering method and trained using heuristic genetic algorithm for a protein secondary structure classification. Three structure classes are distinguished including helix, strand (sheet) and coil which correspond to three outputs of the MOIT2FLS. Quantitative properties of amino acids are used to characterize the twenty amino acids rather than the widely used computationally expensive binary encoding scheme. Amino acid sequences are parsed into learnable patterns using a local moving window strategy. Three clustering tasks are performed using the adaptive vector quantization method to derive an equal number of initial rules for each type of secondary structure. Genetic algorithm is applied to optimally adjust parameters of the MOIT2FLS with the purpose of maximizing the Q3 measure. Comprehensive experimental results demonstrate the strong superiority of the proposed approach over the traditional methods including Chou-Fasman method, Garnier-Osguthorpe-Robson method, and artificial neural network models.

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.

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.

Antibacterial and antiparasitic effects of Bothrops marajoensis venom and its fractions: Phospholipase A(2) and L-amino acid oxidase

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Ingredient classification according to the digestible amino acid profile: an exploratory analysis

This study aimed: 1) to classify ingredients according to the digestible amino acid (AA) profile; 2) to determine ingredients with AA profile closer to the ideal for broiler chickens; and 3) to compare digestible AA profiles from simulated diets with the ideal protein profile. The digestible AA levels of 30 ingredients were compiled from the literature and presented as percentages of lysine according to the ideal protein concept. Cluster and principal component analyses (exploratory analyses) were used to compose and describe groups of ingredients according to AA profiles. Four ingredient groups were identified by cluster analysis, and the classification of the ingredients within each of these groups was obtained from a principal component analysis, showing 11 classes of ingredients with similar digestible AA profiles. The ingredients with AA profiles closer to the ideal protein were meat and bone meal 45, fish meal 60 and wheat germ meal, all of them constituting Class 1; the ingredients from the other classes gradually diverged from the ideal protein. Soybean meal, which is the main protein source for poultry, showed good AA balance since it was included in Class 3. on the contrary, corn, which is the main energy source in poultry diets, was classified in Class 8. Dietary AA profiles were improved when corn and/or soybean meal were partially or totally replaced in the simulations by ingredients with better AA balance.

Pearl millet utilization in ccommercial laying hen diets formulated on a total or digestible amino acid basis

An experiment was carried out to evaluate the effect of replacing corn with pearl millet in commercial layer diets, formulated according to the minimal requirements for total and digestible amino acids. Two hundred and forty Lohmann LSL laying hens with 25 weeks of age were distributed in a completely randomized experimental design according to a 2 x 5 factorial arrangement with 3 replicates of 8 birds. Feed was formulated on two amino acid basis (total or digestible) according to Rostagno et al. (2000) and there were five pearl millet inclusion levels (0%, 25%, 50%, 75%, and 100%). Performance and egg quality were evaluated during five periods of 21 days.At the end of each period, feed intake, egg production, egg weight and feed conversion were evaluated. In the last three days of each period, the following egg quality parameters were evaluated: Haugh Unit, yolk pigmentation index, egg specific weight, shell percentage and shell thickness. Digestible amino acid requirements resulted in decreased feed intake (p<0.01) and increased production costs per mass of eggs (kg) or per dozen eggs (p<0.01) compared to total amino acid requirements. There was a linear reduction in feed intake, egg production, egg weight and yolk pigmentation index with increasing inclusion levels of pearl millet. Therefore, increasing levels of replacement of corn by pearl millet affected bird performance negatively. Besides, production costs were higher with increasing pearl millet levels.

Cell cycle arrest evidence, parasiticidal and bactericidal properties induced by L-amino acid oxidase from Bothrops atrox snake venom

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

Platelet aggregation and antibacterial effects of an L-amino acid oxidase purified from Bothrops alternatus snake venom

The isolation and biochemical/enzymatic characterization of an L-amino acid oxidase, Balt-LAAO-I, from Bothrops alternates snake venom, is described. Balt-LAAO-I is an acidic glycoprotein, pI similar to 5.37, homodimeric, M-r similar to 123, 000, whose Nterminal sequence is ADVRNPLE EFRETDYEVL. It displays a high specificity toward hydrophobic and basic amino acids, while deglycosylation does not alter its enzymatic activity. Bait-LAAO-I induces platelet aggregation and shows bactericidal activity against Escherichia coli and Staphylococcus aureus. In addition, this enzyme is slightly hemorrhagic and induces edema in the mouse paw. Bait-LAAO-I is a multifunctional enzyme with promising relevant biotechnological and medical applications. (C) 2004 Elsevier Ltd. All rights reserved.