Evidence map›Paper›PMID 20708922›Full record

ReviewCurrent opinion in structural biology2010

Computational glycoscience: characterizing the spatial and temporal properties of glycans and glycan-protein complexes.

Robert J Woods, Matthew B Tessier

Abstract readReview
In one paragraph

Review in Current opinion in structural biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Glycans in Virus-Host Interactions: A Structural Perspective.Frontiers in molecular biosciences · 2021
    Review
  6. Three-Dimensional Structures of Carbohydrates and Where to Find Them.International journal of molecular sciences · 2020
    Review
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
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.

Robert J WoodsComplex Carbohydrate Research Center, University of Georgia, 315 Riverbend Road, Athens, GA 30602, USA. rwoods@ccrc.uga.edu
Matthew B Tessier

Funding

ZINC DEFICIENCY &PROTEIN EXPRESSION IN RAT OLFACTORY BULBSP41RR005351 · NCRR · UNIVERSITY OF GEORGIA (UGA) · PI VENOT, ANDRE · 1989 to 2011
$18.4M
TR&D3. Approaches to Proteoglycan Function at Biochemical and Cellular LevelsP41GM103390 · NIGMS · UNIVERSITY OF GEORGIA · PI MOREMEN, KELLEY W. · 2012 to 2019
$14.5M
COMPUTATIONAL ANALYSIS OF CARBOHYDRATE ANTIGENICITYR01GM055230 · NIGMS · UNIVERSITY OF GEORGIA (UGA) · PI WOODS, ROBERT J · 2001 to 2010
$1.6M
COMPUTATIONAL ANALYSIS OF CARBOHYDRATE ANTIGENICITYR29GM055230 · NIGMS · UNIVERSITY OF GEORGIA (UGA) · PI WOODS, ROBERT J · 1997 to 2000
$101k
NCRR NIH HHS P41 RR005351NCRR NIH HHS RR005351NIGMS NIH HHS GM055230NIGMS NIH HHS P41 GM103390NIGMS NIH HHS R01 GM055230NIGMS NIH HHS R29 GM055230
6 · The paper itself

Abstract

Modern computational methods offer the tools to provide insight into the structural and dynamic properties of carbohydrate-protein complexes, beyond that provided by experimental structural biology. Dynamic properties such as the fluctuation of inter-molecular hydrogen bonds, the residency times of bound water molecules, side chain motions and ligand flexibility may be readily determined computationally. When taken with respect to the unliganded states, these calculations can also provide insight into the entropic and enthalpic changes in free energy associated with glycan binding. In addition, virtual ligand screening may be employed to predict the three dimensional (3D) structures of carbohydrate-protein complexes, given 3D structures for the components. In principle, the 3D structure of the protein may itself be derived by modeling, leading to the exciting--albeit high risk--realm of virtual structure prediction. This latter approach is appealing, given the difficulties associated with generating experimental 3D structures for some classes of glycan binding proteins; however, it is also the least robust. An unexpected outcome of the development of algorithms for modeling carbohydrate-protein interactions has been the discovery of errors in reported experimental 3D structures and a heightened awareness of the need for carbohydrate-specific computational tools for assisting in the refinement and curation of carbohydrate-containing crystal structures. Here we present a summary of the basic strategies associated with employing classical force field based modeling approaches to problems in glycoscience, with a focus on identifying typical pitfalls and limitations. This is not an exhaustive review of the current literature, but hopefully will provide a guide for the glycoscientist interested in modeling carbohydrates and carbohydrate-protein complexes, as well as the computational chemist contemplating such tasks.

Indexed as

Computer SimulationAnimalsHumansMolecular Dynamics SimulationPolysaccharidesProteinsTime FactorsPolysaccharidesProteins

Identifiers

PMID20708922
PMCPMC3936461

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.