98%
921
2 minutes
20
There is an increasing interest in using S-glycosylation as a replacement for the more commonly occurring O-glycosylation, aiming to enhance the resistance of glycans against chemical hydrolysis and enzymatic degradation. However, previous studies have demonstrated that these two types of glycosylation exert distinct effects on protein properties and functions. In order to elucidate the structural basis behind the observed differences, we conducted a systematic and comparative analysis of 6 differently glycosylated forms of a model glycoprotein, CBM, using NMR spectroscopy and molecular dynamic simulations. Our findings revealed that the different stabilizing effects of S- and O-glycosylation could be attributed to altered hydrogen-bonding capability between the glycan and the polypeptide chain, and their diverse impacts on binding affinity could be elucidated by examining the interactions and motion dynamics of glycans in substrate-bound states. Overall, this study underscores the pivotal role of the glycosidic linkage in shaping the function of glycosylation and advises caution when switching glycosylation types in protein glycoengineering.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.ijbiomac.2023.126649 | DOI Listing |
JMIR Hum Factors
September 2025
Seidenberg School of Computer Science and Information Systems, Pace University, New York City, NY, United States.
Background: As information and communication technologies and artificial intelligence (AI) become deeply integrated into daily life, the focus on users' digital well-being has grown across academic and industrial fields. However, fragmented perspectives and approaches to digital well-being in AI-powered systems hinder a holistic understanding, leaving researchers and practitioners struggling to design truly human-centered AI systems.
Objective: This paper aims to address the fragmentation by synthesizing diverse perspectives and approaches to digital well-being through a systematic literature review.
J Med Internet Res
September 2025
School of Nursing, University of Minho, Braga, Portugal.
Background: The spread of misinformation on social media poses significant risks to public health and individual decision-making. Despite growing recognition of these threats, instruments that assess resilience to misinformation on social media, particularly among families who are central to making decisions on behalf of children, remain scarce.
Objective: This study aimed to develop and evaluate the psychometric properties of a novel instrument that measures resilience to misinformation in the context of social media among parents of school-age children.
J Phys Chem Lett
September 2025
Department of Chemistry, Oregon State University, 153 Gilbert Hall, Corvallis, Oregon 97331, United States.
Carbon dots (CDs) represent a new class of nontoxic and sustainable nanomaterials with increasing applications. Among them, bright and large Stokes-shift CDs are highly desirable for display and imaging, yet the emission mechanisms remain unclear. We obtained structural signatures for the recently engineered green and red CDs by ground-state femtosecond stimulated Raman spectroscopy (FSRS), then synthesized orange CDs with similar size but much higher nitrogen dopants than red CDs.
View Article and Find Full Text PDFCereb Cortex
August 2025
Section on Functional Imaging Methods & Functional MRI Core Facility, National Institute of Mental Health, 10 Center Drive, Rm 1D80, Bethesda, MD 20892, United States.
Statistical Parametric Mapping (SPM) has been profoundly influential to neuroimaging as it has fostered rigorous, statistically grounded structure for model-based inferences that have led to mechanistic insights about the human brain over the past 30 years. The statistical constructs shared with the world through SPM have been instrumental for deriving meaning from neuroimaging data; however, they require simplifying assumptions which can provide results that, while statistically sound, may not accurately reflect the mechanisms of brain function. A platform that fosters the exploration of the rich and varying neuronal and physiologic underpinnings of the measured signals and their associations to behavior and physiologic measures needs a different set of tools.
View Article and Find Full Text PDFMol Divers
September 2025
Department of Biotechnology, National Institute of Technology Raipur, Raipur, Chhattisgarh, 492001, India.
Traditional drug discovery methods like high-throughput screening and molecular docking are slow and costly. This study introduces a machine learning framework to predict bioactivity (pIC₅₀) and identify key molecular properties and structural features for targeting Trypanothione reductase (TR), Protein kinase C theta (PKC-θ), and Cannabinoid receptor 1 (CB1) using data from the ChEMBL database. Molecular fingerprints, generated via PaDEL-Descriptor and RDKit, encoded structural features as binary vectors.
View Article and Find Full Text PDF