First insights into the binding mechanism and colour effect of the interaction of grape seed 11S globulin with malvidin 3-O-glucoside by fluorescence spectroscopy, differential colorimetry and molecular modelling

Conformational alterations and functional changes of pepsin induced by a novel food supplement tetrahydrocurcumin: Multispectral techniques and computer simulations

Tetrahydrocurcumin (THC), as a novel food supplement, has generated significant interests for its potential impact on health and nutrition. Pepsin serves as the primary enzyme involved in the digestive mechanism. This research investigated the conformational and functional alterations of pepsin induced by THC using multispectral techniques and computer simulations. The results showed that THC enters the cavity of pepsin, in which hydrophobic forces play a major role. The binding constant is 1.044 × 104 M-1 at 310 K. The upregulation or downregulation effect of THC on pepsin activity depends on its concentration. Molecular docking outcomes indicated that THC was encapsulated by various amino acids and established H-bonds with Tyr189 and Ser294, revealing that hydrogen bonds also contribute to maintaining the stability of THC-pepsin complex. In addition, the altered activity of pepsin may be related to the interaction between THC and the amino acids at the active site (Asp32) according to energy contribution results. 3D fluorescence spectroscopy, CD spectra and molecular dynamic simulations show that THC causes conformational changes in pepsin. The existence of THC makes pepsin structure to be less dense, leading to the decrease of energy traps. This suggests that pepsin becomes conformationally more suitable to bind to THC.

Lactobionic acid matrix supramolecular complexes with enhanced bioavailability and clinical efficacy as an optimal CP system

Despite the biological activity of lactobionic acid (LBA), its low bioavailability remains a challenge in response to complex clinical needs. Aided by computer high-throughput screening and ab initio analysis, we selected betaine and mandelic acid as the right arms to synthesize supramolecular lactobionic acid (SLBA) through a proton exchange reaction, which significantly and comprehensively improved the bioavailability of LBA. Density functional theory and physicochemical characterization revealed the supramolecular characteristics and chemical stability of this coupling. The resulting SLBA has shown significant advantages over LBA in cellular, animal, and clinical trials and demonstrated enormous potential in anti-aging beauty, clinical treatment, biomedicine, and food preservation.

New approaches for screening grape seed peptides as colourimetric modulators by malvidin-3-O-glucoside stabilisation

The colour of red wine is due to the presence of anthocyanins and their derived pigments, with malvidin-3-O-glucoside being the most predominant. Due to their chemical conformation, anthocyanins are susceptible to several conditions and have limited stability. Through copigmentation processes, anthocyanins can interact non-covalently with other molecules to enhance their stability. As a natural source of proteins and peptides, grape seeds are of particular interest because they may be of significant techno-functional value in the modulation of wine quality characteristics, such as acting as copigments to enhance colour stability. The proposed methodology allowed predicting in-depth insights into the molecular-level nature of interaction between the identified peptides when complexed with malvidin 3-O-glucoside and their colour stabilising properties. Thereby, allowing a prior screening in silico to facilitate their future application in experimental assays, such as obtaining the tested peptides with the characteristics already studied by means of grape seed meal directed hydrolysis.

Integrative genomics reveals the polygenic basis of seedlessness in grapevine

Seedlessness is a crucial quality trait in table grape (Vitis vinifera L.) breeding. However, the development of seeds involved intricate regulations, and the polygenic basis of seed abortion remains unclear. Here, we combine comparative genomics, population genetics, quantitative genetics, and integrative genomics to unravel the evolution and polygenic basis of seedlessness in grapes. We generated the haplotype-resolved genomes for two seedless grape cultivars, "Thompson Seedless" (TS, syn. "Sultania") and "Black Monukka" (BM). Comparative genomics identified a ∼4.25 Mb hemizygous inversion on Chr10 specific in seedless cultivars, with seedless-associated genes VvTT16 and VvSUS2 located at breakpoints. Population genomic analyses of 548 grapevine accessions revealed two distinct clusters of seedless cultivars, and the identity-by-descent (IBD) results indicated that the origin of the seedlessness trait could be traced back to "Sultania." Introgression, rather than convergent selection, shaped the evolutionary history of seedlessness in grape improvement. Genome-wide association study (GWAS) analysis identified 110 quantitative trait loci (QTLs) associated with 634 candidate genes, including previously unidentified candidate genes, such as three 11S GLOBULIN SEED STORAGE PROTEIN and two CYTOCHROME P450 genes, and well-known genes like VviAGL11. Integrative genomic analyses resulted in 339 core candidate genes categorized into 13 functional categories related to seed development. Machine learning-based genomic selection achieved a remarkable prediction accuracy of 97% for seedlessness in grapevines. Our findings highlight the polygenic nature of seedlessness and provide candidate genes for molecular genetics and an effective prediction for seedlessness in grape genomic breeding.

Application of the molecular dynamics simulation GROMACS in food science

Food comprises proteins, lipids, sugars and various other molecules that constitute a multicomponent biological system. It is challenging to investigate microscopic changes in food systems solely by performing conventional experiments. Molecular dynamics (MD) simulation serves as a crucial bridge in addressing this research gap. The Groningen Machine for Chemical Simulations (GROMACS) is an open-source, high-performing molecular dynamics simulation software that plays a significant role in food science research owing to its high flexibility and powerful functionality; it has been used to explore the molecular conformations and the mechanisms of interaction between food molecules at the microcosmic level and to analyze their properties and functions. This review presents the workflow of the GROMACS software and emphasizes the recent developments and achievements in its applications in food science research, thus providing important theoretical guidance and technical support for obtaining an in-depth understanding of the properties and functions of food.

Cellulose nanocrystals derived from chicory plant: an un-competitive inhibitor of aromatase in breast cancer cells via PI3K/AKT/mTOP signalling pathway

A significant contributing factor in the development of breast cancer is the estrogens. The synthesis of estrogens is primarily facilitated by aromatase (CYP19), a cytochrome P450 enzyme. Notably, aromatase is expressed at a higher level in human breast cancer tissue compared with the normal breast tissue. Therefore, inhibiting aromatase activity is a potential strategy in hormone receptor-positive breast cancer treatment. In this study, Cellulose Nanocrystals (CNCs) were obtained from Chicory plant waste through a sulfuric acid hydrolysis method with the objective of investigating that whether the obtained CNCs could act as an inhibitor of aromatase enzyme, and prevent the conversion of androgens to estrogens. Structural analysis of CNCs was carried out using Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD), while morphological results were obtained using AFM, TEM, and FE-SEM. Furthermore, the nano-particles were found to be spherical in shape with a diameter range of 35-37 nm and displayed a reasonable negative surface charge. Stable transfection of MCF-7 cells with CYP19 has demonstrated the ability of CNCs to inhibit aromatase activities and prevent cell growth by interfering with the enzyme activities. Spectroscopic results revealed the binding constant of CYP19-CNCs and (CYP19-Androstenedione)-CNCs complexes to be 2.07 × 103 L/gr and 2.06 × 104 L/gr, respectively. Conductometry and CD data reported different interaction behaviors among CYP19 and CYP19-Androstenedione complexes at the presence of CNCs in the system. Moreover, the addition of CNCs to the solution in a successive manner resulted in the enhancement of the secondary structure of the CYP19-androstenedione complex. Additionally, CNCs showed a marked reduction in the viability of cancer cells compared to normal cells by enhancing the expression of Bax and p53 at protein and mRNA levels, and by decreasing mRNA levels of PI3K, AKT, and mTOP, as well as protein levels of PI3Kg-P110 and P-mTOP, in MCF-7 cells after incubation with CNCs at IC50 concentration. These findings confirm the decrease in proliferation of breast cancer cells associated with induction of apoptosis through down-regulation of the PI3K/AKT/mTOP signaling pathway. According to the provided data, the obtained CNCs are capable of inhibiting aromatase enzyme activity, which has significant implications for the treatment of cancer.Communicated by Ramaswamy H. Sarma.

Probing the interaction mechanism of SDBS with AtPrxQ from Arabidopsis thaliana: Insight into the molecular toxicity to plants

As the most universally used anionic surfactant, ubiquitous existence and accumulation of sodium dodecyl benzene sulfonate (SDBS) in the environment has inevitably imposed the associated harmful impacts to plants due to producing excessive reactive oxygen species. However, the underlying hazardous mechanism of the SDBS-induced oxidative stress to plants at molecular level has never been reported. Here, the molecular interaction of AtPrxQ with SDBS was explored for the first time. The intrinsic fluorescence of AtPrxQ was quenched based on static quenching, and a single binding site of AtPrxQ towards SDBS and the potential interaction forces driven by hydrophobic interactions were predicted from thermodynamic parameters and molecular docking results. Besides, the interaction pattern of AtPrxQ and SDBS was also confirmed by the bio-layer interferometry with moderate binding affinity. Moreover, the structural changes of AtPrxQ along with the destructions of the protein framework and the hydrophobic enhancement around aromatic amino acids were observed upon binding with SDBS. At last, the toxic effects produced by SDBS on peroxidase activities and Arabidopsis seedlings growth were also characterized. Thus this work may provide insights on the molecular interactions of AtPrxQ with SDBS and assessments on the biological hazards of SDBS to plants even for the agriculture.

Molecular simulation for food protein-ligand interactions: A comprehensive review on principles, current applications, and emerging trends

In recent years, investigations on molecular interaction mechanisms between food proteins and ligands have attracted much interest. The interaction mechanisms can supply much useful information for many fields in the food industry, including nutrient delivery, food processing, auxiliary detection, and others. Molecular simulation has offered extraordinary insights into the interaction mechanisms. It can reflect binding conformation, interaction forces, binding affinity, key residues, and other information that physicochemical experiments cannot reveal in a fast and detailed manner. The simulation results have proven to be consistent with the results of physicochemical experiments. Molecular simulation holds great potential for future applications in the field of food protein-ligand interactions. This review elaborates on the principles of molecular docking and molecular dynamics simulation. Besides, their applications in food protein-ligand interactions are summarized. Furthermore, challenges, perspectives, and trends in molecular simulation of food protein-ligand interactions are proposed. Based on the results of molecular simulation, the mechanisms of interfacial behavior, enzyme-substrate binding, and structural changes during food processing can be reflected, and strategies for hazardous substance detection and food flavor adjustment can be generated. Moreover, molecular simulation can accelerate food development and reduce animal experiments. However, there are still several challenges to applying molecular simulation to food protein-ligand interaction research. The future trends will be a combination of international cooperation and data sharing, quantum mechanics/molecular mechanics, advanced computational techniques, and machine learning, which contribute to promoting food protein-ligand interaction simulation. Overall, the use of molecular simulation to study food protein-ligand interactions has a promising prospect.