Biomedical subjects

Karl J Siebert

Publications and source records attributed to Karl J Siebert.

4 recordsLinked to original sources

PubMed2004

Quantitative structure-activity relationship modeling of alcohol, ester, aldehyde, and ketone flavor thresholds in beer from molecular features.

Three quantitative structure-activity relationship approaches-principal components regression, partial least-squares regression, and alternating conditional expectations-were used to investigate relationships between the flavor thresholds of 38 alcohols, 40 esters, 45 aldehydes, and 43 ketones in beer and their structures. Strong nonlinear relationships between the logarithm of the flavor threshold and four or five structure descriptors were found for each class of compounds (R2 = 0.920, 0.937, 0.920, and 0.928 for alcohols, esters, aldehydes, and ketones, respectively). Simple nonlinear relationships between the alcohol, ester, and aldehyde thresholds and the numbers of hydrogen atoms in the molecules were also demonstrated.

Alcohols↗

PubMed2003

Modeling protein functional properties from amino acid composition.

Physicochemical and functional properties of proteins were modeled as a function of the contributions of each of the 20 coded amino acids to three (z-scores) or five (extended z-scores) amino acid principal properties using partial least squares regression. The five term models were in all cases stronger in both fit and prediction than the three term models, indicating that useful information is contained in the fourth and fifth property scores. Models predicting protein hydrophobicity (R = 0.932), viscosity (R = 0.737), and foam capacity (R = 0.880) from amino acid composition rather than sequence were obtained. It is likely that additional functional and physicochemical properties of proteins can be modeled in this way.

Amino Acids↗

PubMed2003

Validation of bacterial growth inhibition models based on molecular properties of organic acids.

Organic acids occur naturally in foods and have been used in many food products as preservatives because they inhibit the growth of most microorganisms. The acids commonly found in foods differ greatly in both their structure and inhibitory effects for different bacteria. A way to represent relationships between different acids was previously described in which principal components analysis (PCA) was applied to 11 physical and chemical properties of 17 organic acids, to arrive at principal properties. These were used for development of regression models that related the minimum inhibitory concentrations (MICs) of organic acids to their principal properties. Separate MIC models were constructed for six different bacteria. The objective of the present study was to test the predictive capabilities of the organism models using different organic acids from the ones used to construct the original models. MIC predictions were made for three acids for each of the six bacteria for which models were previously constructed. MIC determinations for these acids were then carried out and compared with the predictions; these were in good agreement, thus validating the models. The new data were combined with that obtained previously to produce similar, but slightly stronger models. These had R(2) values between 0.861 and 0.992.

Acids↗

PubMed2002

Characterization of haze-active proteins in apple juice.

The nature of the haze-active protein (HAP) in apple juice was investigated. Heat treatment removed protein indiscriminately while polyvinylpolypyrrolidone (PVPP) treatment was fairly specific for proteins of 15 and 28 kDa. Presumably, the PVPP bound to polyphenols, which in turn were complexed with protein. Three candidate apple HAPs were isolated. Two were extracted from juice with acetone and fractionated by hydrophobic interaction chromatography and solid phase extraction with C18 (HAP I) or SAX (HAP II) material. Hydroxyproline-rich protein was extracted from apple tissue (HAP III). The order of haze formation with tannic acid was gliadin > HAP III > HAP II > HAP I > bovine serum albumin, which shows increasing haze formation with increasing proline content. The sizes of HAP I, II, and III were 28, 15, and 12 kDa; the first two corresponded to the sizes of proteins removed by PVPP treatment and are involved in juice haze formation.

Amino Acids↗