D-arabinose-[4-13C]

D-arabinose-[4-13C], a stable isotopically labeled sugar, finds diverse applications in research and industry. Here are the key applications of D-arabinose-[4-13C]:

Metabolic Flux Analysis: Essential for metabolic flux analysis, D-arabinose-[4-13C] serves as a pivotal tool for tracing carbon pathways in intricate metabolic networks. By introducing this labeled sugar into cellular systems, researchers unravel the intricate flow of carbon through diverse metabolic pathways. This knowledge plays a critical role in deciphering cellular metabolism intricacies and optimizing biotechnological processes through a lens of enriched understanding.

NMR Spectroscopy: Leveraged in nuclear magnetic resonance (NMR) spectroscopy, this isotopically labeled sugar enhances studies on the structure and dynamics of carbohydrates. The 13C labeling elevates sensitivity and resolution in NMR experiments, empowering researchers to delve deep into conformational changes, molecular interactions, and reaction mechanisms with unprecedented precision and depth.

Glycomics Studies: At the forefront of glycomics, D-arabinose-[4-13C] acts as a cornerstone for examining the composition and functions of carbohydrate molecules within cellular landscapes. By integrating this labeled sugar into glycan structures, scientists meticulously monitor synthesis, modification, and degradation processes. This in-depth analysis sheds light on the nuanced roles of specific glycans in cellular processes and diverse disease states, offering profound insights into cellular dynamics and function.

Drug Metabolism Research: Within the realm of drug metabolism research, D-arabinose-[4-13C] emerges as a potent agent for exploring pharmaceutical processing within the human body. By tracing the assimilation of this labeled sugar into metabolic pathways, researchers unravel the complex landscape of drug biotransformation and potential interactions. This comprehensive understanding not only aids in optimizing drug design but also facilitates accurate predictions of metabolic profiles, paving the way for enhanced drug development and personalized medicine initiatives.