Dataset Information

Characterization of coacervation behavior between whey protein isolate and propylene glycol alginate: A morphology, spectroscopy, and thermodynamics study.

ABSTRACT: The interactions between whey protein isolate (WPI) and propylene glycol alginate (PGA) were investigated as a function of pH and the mass ratio. The results showed that WPI and PGA formed a soluble and uniform complex at a mass ratio of 2:1 and pH 4.0 through forces such as electrostatic attraction and hydrogen bonding. Isothermal titration calorimetry confirmed that the contribution of positive enthalpy (ΔH) and entropy (ΔS) were the beneficial indicator in the process of combining WPI and PGA under the same mass ratio but different pH. Fourier transform infrared spectroscopy, fluorescence spectroscopy and circular dichroism confirmed that hydrogen bonding was also one of the interaction forces in addition to electrostatic interactions between WPI-PGA complex. The freeze-dried WPI-PGA complex showed the same amorphous structure as WPI. These formed WPI-PGA complexes provided insights for interaction mechanism of proteins and polysaccharides as well as a theoretical basis for the food industry.

SUBMITTER: Xi C

PROVIDER: S-EPMC9532732 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Characterization of coacervation behavior between whey protein isolate and propylene glycol alginate: A morphology, spectroscopy, and thermodynamics study.

Xi Chunyu C Sun Zhengwei Z Chen Xing X Ding Xuan X Zhang Tiehua T

Food chemistry: X 20220726

The interactions between whey protein isolate (WPI) and propylene glycol alginate (PGA) were investigated as a function of pH and the mass ratio. The results showed that WPI and PGA formed a soluble and uniform complex at a mass ratio of 2:1 and pH 4.0 through forces such as electrostatic attraction and hydrogen bonding. Isothermal titration calorimetry confirmed that the contribution of positive enthalpy (ΔH) and entropy (ΔS) were the beneficial indicator in the process of combining WPI and PGA ...[more]

PMID: 36211725

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Project description:BackgroundEtomidate is a preferred drug for the induction of general anesthesia in cardiovascular risk patients. As with propofol and other perioperatively used anesthetics, the application of aqueous etomidate formulations causes an intensive burning pain upon injection. Such algogenic properties of etomidate have been attributed to the solubilizer propylene glycol which represents 35% of the solution administered clinically. The aim of this study was to investigate the underlying molecular mechanisms which lead to injection pain of aqueous etomidate formulations.ResultsActivation of the nociceptive transient receptor potential (TRP) ion channels TRPA1 and TRPV1 was studied in a transfected HEK293t cell line by whole-cell voltage clamp recordings of induced inward ion currents. Calcium influx in sensory neurons of wild-type and trp knockout mice was ratiometrically measured by Fura2-AM staining. Stimulated calcitonin gene-related peptide release from mouse sciatic nerves was detected by enzyme immunoassay. Painfulness of different etomidate formulations was tested in a translational human pain model. Etomidate as well as propylene glycol proved to be effective agonists of TRPA1 and TRPV1 ion channels at clinically relevant concentrations. Etomidate consistently activated TRPA1, but there was also evidence for a contribution of TRPV1 in dependence of drug concentration ranges and species specificities. Distinct N-terminal cysteine and lysine residues seemed to mediate gating of TRPA1, although the electrophile scavenger N-acetyl-L-cysteine did not prevent its activation by etomidate. Propylene glycol-induced activation of TRPA1 and TRPV1 appeared independent of the concomitant high osmolarity. Intradermal injections of etomidate as well as propylene glycol evoked severe burning pain in the human pain model that was absent with emulsification of etomidate.ConclusionsData in our study provided evidence that pain upon injection of clinical aqueous etomidate formulations is not an unspecific effect of hyperosmolarity but rather due to a specific action mediated by activated nociceptive TRPA1 and TRPV1 ion channels in sensory neurons.

Project description:Macromolecules and their complexes remain interesting topics in various fields, such as targeted drug delivery and tissue regeneration. The complex chemical structure of such substances can be studied with a combination of Raman spectroscopy and machine learning. The complex of whey protein isolate (WPI) and hyaluronic acid (HA) is beneficial in terms of drug delivery. It provides HA properties with the stability obtained from WPI. However, differences between WPI-HA and WPI solutions can be difficult to detect by Raman spectroscopy. Especially when the low HA (0.1, 0.25, 0.5% w/v) and the constant WPI (5% w/v) concentrations are used. Before applying the machine learning techniques, all the collected data were divided into training and test sets in a ratio of 3:1. The performances of two ensemble methods, random forest (RF) and gradient boosting (GB), were evaluated on the Raman data, depending on the type of problem (regression or classification). The impact of noise reduction using principal component analysis (PCA) on the performance of the two machine learning methods was assessed. This procedure allowed us to reduce the number of features while retaining 95% of the explained variance in the data. Another application of these machine learning methods was to identify the WPI Raman bands that changed the most with the addition of HA. Both the RF and GB could provide feature importance data that could be plotted in conjunction with the actual Raman spectra of the samples. The results show that the addition of HA to WPI led to changes mainly around 1003 cm-1 (correspond to ring breath of phenylalanine) and 1400 cm-1, as demonstrated by the regression and classification models. For selected Raman bands, where the feature importance was greater than 1%, a direct evaluation of the effect of the amount of HA on the Raman intensities was performed but was found not to be informative. Thus, applying the RF or GB estimators to the Raman data with feature importance evaluation could detect and highlight small differences in the spectra of substances that arose from changes in the chemical structure; using PCA to filter out noise in the Raman data could improve the performance of both the RF and GB. The demonstrated results will make it possible to analyze changes in chemical bonds during various processes, for example, conjugation, to study complex mixtures of substances, even with small additions of the components of interest.

Dataset Information

Characterization of coacervation behavior between whey protein isolate and propylene glycol alginate: A morphology, spectroscopy, and thermodynamics study.

Publications

Characterization of coacervation behavior between whey protein isolate and propylene glycol alginate: A morphology, spectroscopy, and thermodynamics study.

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