Experimental Oncology and Immunology, Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy.
Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies, Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany.
Biomolecules. 2021 May 15;11(5):739. doi: 10.3390/biom11050739.
Glycosaminoglycans (GAGs) are linear polysaccharides. In proteoglycans (PGs), they are attached to a core protein. GAGs and PGs can be found as free molecules, associated with the extracellular matrix or expressed on the cell membrane. They play a role in the regulation of a wide array of physiological and pathological processes by binding to different proteins, thus modulating their structure and function, and their concentration and availability in the microenvironment. Unfortunately, the enormous structural diversity of GAGs/PGs has hampered the development of dedicated analytical technologies and experimental models. Similarly, computational approaches (in particular, molecular modeling, docking and dynamics simulations) have not been fully exploited in glycobiology, despite their potential to demystify the complexity of GAGs/PGs at a structural and functional level. Here, we review the state-of-the art of computational approaches to studying GAGs/PGs with the aim of pointing out the "bitter" and "sweet" aspects of this field of research. Furthermore, we attempt to bridge the gap between bioinformatics and glycobiology, which have so far been kept apart by conceptual and technical differences. For this purpose, we provide computational scientists and glycobiologists with the fundamentals of these two fields of research, with the aim of creating opportunities for their combined exploitation, and thereby contributing to a substantial improvement in scientific knowledge.
糖胺聚糖（GAGs）是线性多糖。在蛋白聚糖（PGs）中，它们与核心蛋白相连。GAGs 和 PGs 可以作为游离分子存在，与细胞外基质相关联或表达在细胞膜上。它们通过与不同的蛋白质结合，从而调节其结构和功能，以及在微环境中的浓度和可用性，在广泛的生理和病理过程的调节中发挥作用。不幸的是，GAGs/PGs 的巨大结构多样性阻碍了专用分析技术和实验模型的发展。同样，计算方法（特别是分子建模、对接和动力学模拟）在糖生物学中尚未得到充分利用，尽管它们有可能在结构和功能水平上揭示 GAGs/PGs 的复杂性。在这里，我们回顾了研究 GAGs/PGs 的计算方法的最新进展，旨在指出该研究领域的“苦”与“甜”。此外，我们试图弥合生物信息学和糖生物学之间的差距，这两个领域迄今为止由于概念和技术上的差异而被分开。为此，我们为计算科学家和糖生物学家提供了这两个研究领域的基础知识，旨在为它们的联合利用创造机会，从而为科学知识的实质性提高做出贡献。
