Phenolic compounds can undergo auto-oxidation, especially at alkaline pH, forming reactive o -quinones that bind covalently to proteins and may affect the protein structure, solubility, and functional properties. Yet, it is still unclear how the phenolic compounds' structure and properties affect their reaction with proteins, and how they influence the resulting changes in protein structure and functionality. Therefore, the model protein β-lactoglobulin (BLG) was incubated with ten common phenolic compounds at pH 8.5 for 24 h at a phenolic-to-protein molar ratio of 5:1. RP-HPLC was used to screen for covalent modifications. Protein structural changes were investigated using MALDI-TOF-MS, OPA and Ellman's assays, ATR-FTIR, tryptophan fluorescence quenching, SDS-PAGE, and SEC. Protein functionality changes were determined by oil droplet size measurement after emulsion formation via high pressure homogenization. Only phenolic compounds with a di or-trihydroxybenzene moiety resulted in noteworthy BLG modification (>40 %), with an average of one phenolic compound bound per protein molecule, primarily on the thiol groups of the cysteine residues. Modification decreased the protein's α-helices and shifted the intramolecular β-sheets to higher wavelengths. Protein modification resulted in the formation of smaller oil droplets (from 1.38 to 2 μm) at low homogenization pressure. A positive relationship was found between the presence of a carboxyl group in the phenolic compounds, the unfolding of the protein's tertiary structure (R 2 = 0.95), and smaller oil droplet size. The insights from this study support the selection of phenolic compounds for targeted protein modifications or for avoiding undesired protein modifications. • Only phenolics with a catechol or pyrogallol moiety modify proteins at alkaline pH • At pH 8.5, phenolic compounds primarily bind at the free thiol groups of cysteines • Modification results in a decrease and shift in intramolecular β-sheets • Phenolic compounds with a carboxyl group induced protein tertiary structure changes • Protein tertiary structure changes lead to a decrease in emulsion droplet size

A molecular and cellular understanding of PFDA-exposure-associated outcomes on biological assemblies.

Influence of pulsed electric field on rheological and structural properties of frozen non-fermented dough by controlling ice crystal formation.

Recent advances in protein modification strategies to enhance their gel formation capability and stability: Principles, mechanisms, and techniques.

Proteomic landscape of crotonylation and acetylation in pig testes across male reproduction.

Electrochemical glucose sensing using an electrochemically reduced graphene oxide/poly-L-lysine composite electrode modified with glucose oxidase

An AI-based approach accelerates the discovery of protein-protein interaction modulators targeting NCS-1.

The functional performances are encoded by protein structures, and modified structure-based strategies for customizing food proteins have major implications for the food industry. The glycation reaction that typically occurs between food components is a promising strategy for protein modification due to its mild reaction conditions and natural occurrence during processing. However, the complexity and dynamic nature of glycation reactions hinder precise control, and there is a large imbalance between abundant structural data and function information. Artificial intelligence (AI), with its capacity for large-scale data integration and predictive modeling, offers transformative potential for elucidating glycation-structure-function relationships. This review therefore aims to (1) summarize advances in analytical strategies for glycated proteins, highlighting techniques for site localization, conformational analysis, and multi-source data mining; (2) elucidate how glycation-induced structural modifications alter protein functional performance, providing mechanistic insights into physicochemical properties and biological activities; and (3) discuss emerging AI-driven approaches, including deep learning and inverse design, for predicting and optimizing glycation patterns. These insights provide a systematic framework to accelerate rational development of functional proteins and promote innovative applications in the food industry.

Food-grade abalone muscle hydrolysates as affected by high-pressure homogenization: An in-depth investigation into air-water interfacial behavior of their proteins.

Proteomics-driven innovations in plant-based foods: Current advances, emerging technologies, and future perspectives.

Structural and techno-functional modifications of pea protein fractions by non-thermal technologies.

Chemical degradation of histidine residues and histidine as an excipient in protein-based biopharmaceuticals.

Naturally derived Erythrinin C targets γ-secretase signaling to suppress triple-negative breast cancer progression and reverse paclitaxel resistance.

Atomistic simulations identify the Tetrandrine as potent anti-malarial drug candidate against Plasmodium falciparum targeting Heme Detoxification Protein (HDP).

Structural and functional insights into glycosyltransferase from Nocardia asteroides NCTC11293 and structure-guided discovery of marine and phytochemical leads through pharmacokinetic screening and molecular dynamics studies.

The cerebellin (CBLN) family includes CBLN1, CBLN2, CBLN3, and CBLN4, which are important secreted glycoproteins that play roles in synaptogenesis and the maintenance and plasticity of synapses across various regions of the central nervous system (CNS). Generally known for their implications in cerebellar parallel fiber-Purkinje cell synapses, CBLNs also play a comprehensive role in synaptic regulation in the CNS. By forming trans-synaptic complexes with postsynaptic glutamate delta receptors (GluDs) and presynaptic neurexins (NRXNs), CBLNs significantly impact the synaptic specificity and potency. Each CBLN protein has its own expression signature and function. Current research points to a key role for CBLN1 in forming excitatory synapses, especially in the cerebellum, while CBLN2 is reported to regulate inhibitory synaptic transmission and serotonergic circuits. In addition, CBLN3 regulates synaptic stability and is associated with many neurodevelopmental problems. Apart from its role in the regulation of inhibitory synapse formation, CBLN4 is also linked to many neurodegenerative disorders. Dysfunction of pathways associated with CBLN signaling has been linked to several neuropsychiatric and neurological disorders, such as ataxia and schizophrenia. This review article compares existing data on the structure, expression, and functional properties of CBLN proteins, their roles in synapse organization, and their potential as therapeutic targets for neurological disease.

Modulating structure and gelation properties of mung bean protein via controlled enzymatic hydrolysis

Food texture is increasingly recognized as a determinant of nutritional safety, metabolic regulation, and overall health. However, conventional approaches to texture modification rely primarily on hydrocolloids, mechanical processing, or extrusion, which provide limited control over the molecular structures that govern swallowing behavior, digestibility, satiety, and nutrient release. Recent advances in CRISPR genome editing provide an opportunity to redesign texture at its biochemical foundation, enabling precise modification of starch architecture, gluten networks, and plant cell-wall components. This review synthesizes current evidence on CRISPR-enabled texture engineering and examines its relevance for vulnerable populations and chronic disease management. Gene edits that adjust amylose–amylopectin ratios or gluten epitope profiles influence glycemic responses, allergenicity, and dough quality. Modifications to cell-wall remodeling enzymes reshape firmness, hydration, and breakdown behavior in fruits and vegetables. These molecular interventions create new pathways for designing safer foods for dysphagia, tailored textures for clinical nutrition, and structured matrices that support glycemic control, satiety, or gut health. Beyond clinical contexts, CRISPR-guided texture design holds promise for sustainability, performance nutrition, and AI-driven precision diet formulation. These developments position texture as a programmable variable in next-generation functional foods. • CRISPR enables genetic control of texture-relevant starch, protein, and cell-wall structures. • Molecular texture design improves safety and nutrient delivery in dysphagia and clinical diets. • Gene-edited starch architectures support glycemic control and metabolic health strategies. • Reduced-epitope gluten edits lower immunoreactivity while preserving dough functionality. • Texture engineering aligns with sustainability, performance nutrition, and AI-guided diet design.

Domain insertion creates architectures where one domain interrupts another's sequence. Analysis across 2.7 million classified domains reveals that insertions occur in 20% of multidomain proteins, with 331 families exhibiting consistent architectural roles: 162 function exclusively as hosts, while 169 exclusively serve as inserted modules, such as zinc-binding dehydrogenases appearing as insertions across 450 events. The remaining 1116 families with sufficient insertion activity demonstrate versatile behavior, adopting different roles depending on partnership context. Size analysis shows inserted domains are consistently smaller than their hosts (median 115 vs. 199 residues), with role-consistent families exhibiting 1.7-fold size differences. Insertions frequently involve domains from different structural superfamilies: 31,925 events (65.8% of total) occur between families from different H-groups, such as P-loop hydrolases with tRNA modification domains. While most insertions are simple single-level architectures, insertion mechanisms can create complex organizations, including six-level nested structures in cyanobacterial RNA polymerase. This work provides a comprehensive dataset of 48,551 insertion events across 5701 families, with quantitative characterization of size relationships and partnership patterns that can inform structure prediction and protein design efforts.

Effects of protein structure and proteomics on the moisture migration in rice with milling degrees