Detailed information about the relationships between structures and properties/activities of peptides as drugs and nutrients is useful in the development of drugs and functional foods containing peptides as active compounds. The bitterness of the peptides is an undesirable property which should be reduced during drug/nutrient production, and quantitative structure bitter taste relationship (QSBR) studies can help researchers to design less bitter peptides with higher target efficiency. Calculated structural parameters were used to develop three different QSBR models (i.e., multiple linear regression, support vector machine, and artificial neural network) to predict the bitterness of 229 peptides (containing 2–12 amino acids, obtained from the literature). The developed models were validated using internal and external validation methods, and the prediction errors were checked using mean percentage deviation and absolute average error values. All developed models predicted the activities successfully (with prediction errors less than experimental error values), whereas the prediction errors for nonlinear methods were less than those for linear methods. The selected structural descriptors successfully differentiated between bitter and nonbitter peptides.
Lineweaver-Burk plot analysis is the most widely used method to determine enzyme kinetic parameters. In the spectrophotometric determination of enzyme activity using the Lineweaver-Burk plot, it is necessary to find a wavelength at which only the substrate or the product has absorbance without any spectroscopic interference of the other reaction components. Moreover, in this method, different initial concentrations of the substrate should be used to obtain the initial velocities required for Lineweaver-Burk plot analysis. In the present work, a multi-wavelength model-based method has been developed and validated to determine Michaelis-Menten constants for some enzyme reactions. In this method, a selective wavelength region and several experiments with different initial concentrations of the substrate are not required. The absorbance data of the kinetic assays are fitted by non-linear regression coupled to the numeric integration of the related differential equation. To indicate the applicability of the proposed method, the Michaelis-Menten constants for the oxidation of phenanthridine, 6-deoxypenciclovir and xanthine by molybdenum hydroxylases were determined using only a single initial concentration of the substrate, regardless of any spectral overlap.
Simultaneous spectrophotometric determination of three neonicotinoid insecticides (acetamiprid, imidacloprid, and thiamethoxam) by a novel method named generalized net analyte signal standard addition method (GNASSAM) in some binary and ternary synthetic mixtures was investigated. For this purpose, standard addition was performed using a single standard solution consisting of a mixture of standards of all analytes. Savings in time and amount of used materials are some of the advantages of this method. All determinations showed appropriate applicability of this method with less than 5% error. This method may be applied for linearly dependent data in the presence of known interferents. The GNASSAM combines the advantages of both the generalized standard addition method and net analyte signal; therefore, it may be a proper alternative for some other multivariate methods.
Differential pulse polarography was used for simultaneous determination of Sn 2+ and Pb 2+ . But there is a problem for simultaneous determination and it is high overlapped DPPs of mentioned cations that their determination is impossible in the presence of each other, so multivariate calibration methods as chemomatrics methods were used for this determination. There are some disadvantageous for multivariate calibration methods that can be solved by a new and simple method called net analyte signal standard addition method. This method has some advantages, such as: the use of a full voltammogram, realization in a single step, therefore it does not require calibration and prediction steps and only a few measurements are required for the determination.Keywords: Net analyte signal standard addition method; Simultaneous determination; Differential pulse polarography; Lead; Tin. INTRODUCTIONThe impact of the effects of trace chemical species in the environmental and industrial samples on man's health has fostered development of analytical techniques and instrumentation capable of addressing these issues. 1,2 Different analytical methods were used for simultaneous determination of trace metals like atomic absorption spectrometry, 3,4 high performance liquid chromatography, 5 inductively coupled plasma-mass spectrometry 6 and neutron activation analysis 7 and electrochemical methods. 1,2 Between these methods, one of the reliable, accurate methods that gives qualitative and quantitative information of electroactive species in a sample as a well-known analytical tools with high sensivity and selectivity, coupled with convenience and economy are required. Differential pulse polarography (DPP) has been recognized as a powerful tool for multiel-ement trace metal detection. 2,8,9 In spite of it's high sensivity, this method drawback is the low selectivity. This problem is considerable when our purpose is simultaneous determination of metals and their oxidation and/or reduction potentials are close to each other so there are sever overlapped peaks. In these cases chemomatrics methods are used for analysis of voltamograms and polarograms.
The net analyte preprocessing/classical least-squares (NAP/CLS) method is a simple chemometric method that has been used for the simultaneous spectrophotometric determination of benzoic acid, sorbic acid, and ascorbic acid. The obtained results indicated that the performances of the NAP/CLS and partial least-squares methods were almost identical. The net analyte signal (NAS) concept was also used to calculate multivariate analytical figures of merit, such as LOD, selectivity, and sensitivity. Wavelength selection was applied based on the concept of NAS regression, and improved the method performance in samples containing nonmodeled interferences. The method afforded recoveries in the range of 98105. The proposed method was successfully applied to determination of the analytes in an Iranian soft drink.
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