ReviewHandbook of experimental pharmacology2025
Decrypting Glycosaminoglycan "sulfation code" with Computational Approaches.
Review in Handbook of experimental pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
2 authors.
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Abstract
Glycosaminoglycans (GAGs), linear anionic periodic polysaccharides, play pivotal roles in various biologically relevant processes within the extracellular matrix (ECM). These processes encompass cell development, proliferation, signaling, ECM assembly, coagulation, and angiogenesis. GAGs perform their functions through their interactions with specific protein partners, rendering them attractive targets for regenerative medicine and drug design. However, the molecular mechanisms governing protein-GAG interactions remain unclear. Classical structure determination techniques face significant challenges when dealing with protein-GAG complexes. This is due to GAGs' unique properties, including their extensive length, flexibility, periodicity, symmetry, multipose binding, and the high heterogeneity of their sulfation patterns constituting the "sulfation code." Consequently, only a limited number of experimental protein-GAG structures have been elucidated. Hence, theoretical approaches are particularly promising in deciphering the code for understanding the structure-function relationship of these complex molecules. In this chapter, we focus on the particularities, challenges, and advances of computational methods such as molecular docking, molecular dynamics, and free-energy calculations when applied to GAG-containing systems. These computational approaches offer valuable insights into the enigmatic world of protein-GAG interactions, paving the way for their enhanced understanding and potential therapeutic applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.