Evidence map›Paper›PMID 40167758›Full record

ReviewHandbook of experimental pharmacology2025

Decrypting Glycosaminoglycan "sulfation code" with Computational Approaches.

Sergey A Samsonov, Mateusz P Marcisz

Abstract readReview
PubMed Publisher
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Sergey A SamsonovFaculty of Chemistry, University of Gdańsk, Gdańsk, Poland. sergey.samsonov@ug.edu.pl.ORCID https://orcid.org/0000-0002-5166-4849
Mateusz P MarciszFaculty of Chemistry, University of Gdańsk, Gdańsk, Poland.ORCID https://orcid.org/0000-0003-2043-6875

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

GlycosaminoglycansAnimalsHumansMolecular Docking SimulationMolecular Dynamics SimulationGlycosaminoglycans

Identifiers

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.