Tetracycline residues induce carbonylation of milk proteins and alter their solubility and digestibility

3D-MPEA: A Graph Attention Model-Guided Computational Approach for Annotating Unknown Metabolites in Interactomics via Mass Spectrometry-Focused Multilayer Molecular Networking

The spectral matching strategy of MS2 fragment spectrograms serves as a ubiquitous method for compound characterization within the matrix. Nevertheless, challenges arise due to the deficiency of distinctions in spectra across instruments caused by coelution peak-derived fragments and incompleteness of the current spectral reference database, leading to dilemma of multidimensional omics annotation. The graph attention model embedded with long short-term memory was proposed as an optimized approach involving integrating similar MS2 spectra into molecular networks according to the isotopic ion peak cluster spacing features to collapse diverse ion species and expand the spectral reference library, which efficiently evaluated the substance capture capacity to 123.1% than classic substance perception tactics. The versatility and utility of the established annotation procedure were showcased in a study on the stimulation of pork mediated by 2,2-bis(4-hydroxyphenyl)propane and enabled the global metabolite annotation from knowns to unknowns at metabolite-lipid-protein level. On the spectra for which in silico extended spectral library search provided a group truth, 83.5-117.1% accuracy surpassed 1.2-14.3% precision after manual validation. β-Ala-His dipeptidase was first evidenced as the critical node related to the transformation of α-helical (36.57 to 35.74%) to random coil (41.53 to 42.36%) mediated by 2,2-bis(4-hydroxyphenyl)propane, ultimately triggering an augment of catalytic performance, inducing a series of oxidative stress, and further intervening in the availability of animal-derived substrates. The integration of ionic fragment feature networks and long short-term memory models allows the effective annotation of recurrent unknowns in organisms and the deciphering of unacquainted matter in multiomics.

Characterization of the interaction between boscalid and tannic acid and its effect on the antioxidant properties of tannic acid

The binding of pesticide residues and fruit components may have a profound impact on pesticide dissipation and the functional characteristics of the corresponding components. Therefore, the interaction between boscalid and tannic acid (TA, a representative phenolic in fruit) was systematically investigated using spectroscopic, thermodynamic, and computational chemistry methods. A separable system was designed to obtain the boscalid-TA complex. Fourier transform infrared and ¹ H-NMR spectroscopies indicated the formation of hydrogen bonds in the complex. Isothermal titration calorimetry showed that the complex bound spontaneously through hydrophobic interactions (ΔG < 0, ΔH > 0, ΔS > 0), with a binding constant of 6.0 × 10⁵  M^-1 at 298 K. The molecular docking results further confirmed the formation of hydrogen bonds and hydrophobic interactions in the complex at the molecular level, with a binding energy of -8.43 kcal mol^-1 . In addition, the binding of boscalid to TA significantly decreased the antioxidant activity of TA. The binding of boscalid residue to TA was characterized at the molecular level, which significantly reduced the in vitro antioxidant properties of TA. PRACTICAL APPLICATION: This study provides a reference for the molecular mechanisms of the interaction between pesticide residues and food matrices, as well as a basis for regulating bound-state pesticide residues in food.