Molecular Interactions of β-(1→3)-Glucans with Their Receptors.

Molecules

Ecole Nationale Supérieure de Chimie de Rennes, CNRS, UMR 6226, 11 Allée de Beaulieu, CS 50837, 35708 Rennes Cedex 7, France.

Published: May 2015

β-(1→3)-Glucans can be found as structural polysaccharides in cereals, in algae or as exo-polysaccharides secreted on the surfaces of mushrooms or fungi. Research has now established that β-(1→3)-glucans can trigger different immune responses and act as efficient immunostimulating agents. They constitute prevalent sources of carbons for microorganisms after subsequent recognition by digesting enzymes. Nevertheless, mechanisms associated with both roles are not yet clearly understood. This review focuses on the variety of elucidated molecular interactions that involve these natural or synthetic polysaccharides and their receptors, i.e., Dectin-1, CR3, glycolipids, langerin and carbohydrate-binding modules.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6272582PMC
http://dx.doi.org/10.3390/molecules20069745DOI Listing

Publication Analysis

Top Keywords

molecular interactions
8
interactions β-1→3-glucans
4
β-1→3-glucans receptors
4
receptors β-1→3-glucans
4
β-1→3-glucans structural
4
structural polysaccharides
4
polysaccharides cereals
4
cereals algae
4
algae exo-polysaccharides
4
exo-polysaccharides secreted
4

Similar Publications

Isolation and characterization of quinoa antimicrobial peptides and its effect on the microbial diversity of fresh apple juice.

Food Chem

December 2024

Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi 830017, China. Electronic address:

This study developed antimicrobial peptides (AMPs) from quinoa with high antibacterial activity and stability by mixed-bacteria fermentation. Furthermore, among 9 peptide fractions purified by membrane separation and chromatography, F1 could effectively inhibit the growth and propagation of bacterial microorganisms in apple juice. Subsequently, F1 identified LC-MS/MS as 95 peptides, molecular weights 494.

View Article and Find Full Text PDF

Immunofluorescence is highly dependent on antibody-antigen interactions for accurate visualization of proteins and other biomolecules within cells. However, obtaining antibodies with high specificity and affinity for their target proteins can be challenging, especially for targets that are complex or naturally present at low levels. Therefore, we developed AptaFluorescence, a protocol that utilizes fluorescently labeled aptamers for in vitro biomolecule visualization.

View Article and Find Full Text PDF

The increasing utilization of deep learning models in drug repositioning has proven to be highly efficient and effective. In this study, we employed an integrated deep-learning model followed by traditional drug screening approach to screen a library of FDA-approved drugs, aiming to identify novel inhibitors targeting the TNF-α converting enzyme (TACE). TACE, also known as ADAM17, plays a crucial role in the inflammatory response by converting pro-TNF-α to its active soluble form and cleaving other inflammatory mediators, making it a promising target for therapeutic intervention in diseases such as rheumatoid arthritis.

View Article and Find Full Text PDF

Detection of Putative Ligand Dissociation Pathways in Proteins Using Site-Identification by Ligand Competitive Saturation.

J Chem Inf Model

December 2024

Computer-Aided Drug Design Center, Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland Baltimore, Baltimore, Maryland 21201, United States.

Drug efficacy often correlates better with dissociation kinetics than binding affinity alone. To study binding kinetics computationally, it is necessary to identify all of the possible ligand dissociation pathways. The site identification by ligand competitive saturation (SILCS) method involves the precomputation of a set of maps (FragMaps), which describe the free energy landscapes of typical chemical functionalities in and around a target protein or RNA.

View Article and Find Full Text PDF

Previously, we reported that α-synuclein (α-syn) clusters synaptic vesicles (SV) Diao et al., 2013, and neutral phospholipid lysophosphatidylcholine (LPC) can mediate this clustering Lai et al., 2023.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!