ReviewBiomolecules2021
A Bittersweet Computational Journey among Glycosaminoglycans.
Review in Biomolecules, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
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.
Who cites it
12 citing papers in PubMed, 17 citations in OpenAlex.
- Glycosaminoglycans in tissue regeneration: Insights into glycobiology and their biomedical application.Bioactive materials · 2026Review
- Glycocalyx at the host-virus interface: a double-edged sword in virus infection and tissue damage.Frontiers in molecular biosciences · 2026Review
- Decrypting Glycosaminoglycan "sulfation code" with Computational Approaches.Handbook of experimental pharmacology · 2025Review
- Designing a CXCL8-hsa chimera as potential immunmodulator of the tumor micro-environment.Frontiers in immunology · 2025Article
- Developing and Benchmarking Sulfate and Sulfamate Force Field Parameters via Ab Initio Molecular Dynamics Simulations To Accurately Model Glycosaminoglycan Electrostatic Interactions.Journal of chemical information and modeling · 2024Article
- Structural Insights into Endostatin-Heparan Sulfate Interactions Using Modeling Approaches.Molecules (Basel, Switzerland) · 2024Article
- Glycosaminoglycans: What Remains To Be Deciphered?JACS Au · 2023Review
- HS, an Ancient Molecular Recognition and Information Storage Glycosaminoglycan, Equips HS-Proteoglycans with Diverse Matrix and Cell-Interactive Properties Operative in Tissue Development and Tissue Function in Health and Disease.International journal of molecular sciences · 2023Review
- Molecular dynamics simulations to understand glycosaminoglycan interactions in the free- and protein-bound states.Current opinion in structural biology · 2022Review
- HIV-1 Tat and Heparan Sulfate Proteoglycans Orchestrate the Setup ofMolecules (Basel, Switzerland) · 2021Article
- From Cancer to COVID-19: A Perspective on Targeting Heparan Sulfate-Protein Interactions.Chemical record (New York, N.Y.) · 2021Review
- Advanced Molecular Dynamics Approaches to Model a Tertiary Complex APRIL/TACI with Long Glycosaminoglycans.Biomolecules · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
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.