The aim of this work was to study the production of extracellular α-amylase by Kluyveromyces marxianus IF0 0288 using optimized nutritional and cultural conditions in a complex yeast medium under aerobic batch fermentation. By applying the conventional "one-variable-at-a-time" approach and the response surface methodology, the effect of four fermentation parameters (type of carbon source, initial culture pH, temperature, and incubation time) on the growth and α-amylase production was evaluated. The production of α-amylase during 60 h of fermentation increased 13-fold under optimized conditions (1% starch, pH 6.0, 30ºC) in comparison to the conventional optimization method. The initial pH value of 6.13 and temperature of 30.3ºC were optimal conditions by the response surface methodology, leading to further improvement (up to 13-fold) in the production of extracellular α-amylase. These results constituted first evidence that K. marxianus could be potentially used as an effective source of extracellular α-amylase.

This article reports a first contribution for the elucidation of catalytic mechanism of Lipase from porcine pancreas, type VI-s (PPL), in hydrolyzing an ester substrate in aqueous media. The conclusions were based on the pH-profiles of Michaelis-Menten parameters k cat/Km, k cat and Km, as well as on the absolute temperature profile of k cat/Km, obtained during the hydrolysis of p-nitrophenyl laurate by PPL. It was found that (a) PPL performs catalysis by means of ion pairs formed either as Ser152-Ο-/His263-Im+H and/or Carbonyl-Ο-/His263-Im+H, (b) the parameter k cat/Km equals to k1 and thus ES is formed and destroyed in the course of a series of consecutive reactions governed by the dynamic constant K S = k2/k1, and (c) the hydrolysis of substrate is assisted by a hydrogen bond developed between deprotonated Asp176 and the positively charged imidazole of His263 across a pKa-value 3.85, necessary for efficient catalysis.

Este trabalho constitui uma contribuição significativa para um uso mais eficiente de um programa de computador valioso do encaixe não-paramétrico de equações multiparamétricas não lineares aos dados experimentais. Entretanto, o pré-requisito neste contexto é a transformação de equações multiparamétricas não lineares em formulários lineares do hyperplano antes de sua incorporação dentro do programa de computador; este último é decisive e uma matéria da prática de programação apropriada. Nisto, nós relatamos uma série das equações extensamente usadas úteis em campos diferentes de processos químicos, em bioquímia e/ou em biotechnologia, junto com suas transformações apropriadas além a sustentação de programação apropriada.

This work constituted a significant contribution for more efficient use of a valuable computer program of non-parametric fitting of nonlinear multiparametric equations to experimental data. However, prerequisite in this context was the transformation of nonlinear multiparametric equations into linear hyperplane forms before their incorporation within the computer program; this latter was decisive and a matter of proper programming practice. Herein, a series of widely used equations useful in different fields of chemical processes, in biochemistry and/or in biotechnology, along with their suitable transformations as well as the appropriate programming support are being reported.

Neste trabalho, apresentamos um método não-paramétrico, e o programa de computação apropriado, para ajustar equações multiparamétricas não lineares para dados experimentais. Nosso método é seguido pelo cálculo dos limites de confiança dos parâmetros estimados. Seu desempenho tem sido testado em várias equações multiparamétricas, comuns nos campos da Bioquímica e Biotecnologia, e é uma expansão multiparamétrica do conceito proposto por outros, para equações que tenham mais de dois parâmetros. Obtivemos estimativas de parâmetros confiáveis sem um conhecimento prévio de parâmetros iniciais de valores esperados, e o programa de computação proposto converge rapidamente, em todos os casos examinados dentro deste trabalho.

In this work, we present a non-parametric method, and the appropriate computer program, for fitting nonlinear multiparametric equations to experimental data. Our method is followed by computation of confidence limits of the parameter estimates. Its performance has been tested on several multiparametric equations, common in the fields of Biochemistry and Biotechnology, and it is a multiparametric expansion of the concept proposed by others for equations having more than two parameters. Good parameter estimates were obtained without a previous knowledge of initial parameter guessing values, and the proposed computer program converges rapidly, in all cases examined within this work.

Neste estudo, o S1 - P1 e S3 - P3, interações entre papaina e quatro substratos sintéticos de pepetídios foram considerados importantes. Os valores de Km foram estimados e são praticamente idênticos entre esses substratos; Isso dá suporte as conclusões obtidas, considerando os valores parâmetros cinéticos estimados. No obstante, baseou na estimação parâmetros kcat e/ou k cat /Km dos substratos utilizados. Se pode concluir que um anel aromático na posição P3, e uma corrente carregada positivamente da cadeia do resíduo na posição P1 dos substratos sintéticos favoreceram interação com a papaina.

In this study, the S1 - P1 and S3 - P3 interactions between papain and four synthetic peptide substrates were found as to be important. The values of Km were estimated as to be practically identical between these substrates; this latter is supporting the conclusions obtained by considering the estimated values of other kinetic parameters. Nevertheless, based on the estimated kcat and/or k cat/Km parameters of the used substrates, we concluded that an aromatic ring at the P3 position, and a positively charged side chain of the residue at the P1 position of the synthetic substrates were favored considerably their interaction with papain.