ReviewCurrent opinion in structural biology2010
Computational glycoscience: characterizing the spatial and temporal properties of glycans and glycan-protein complexes.
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.
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
28 citing papers in PubMed.
- Article
- Structural Analysis of Oligosaccharides and Glycoconjugates Using NMR.Advances in neurobiology · 2023Article
- Development and Evaluation of GlycanDock: A Protein-Glycoligand Docking Refinement Algorithm in Rosetta.The journal of physical chemistry. B · 2021Article
- Computational prediction method to decipher receptor-glycoligand interactions in plant immunity.The Plant journal : for cell and molecular biology · 2021Article
- Glycans in Virus-Host Interactions: A Structural Perspective.Frontiers in molecular biosciences · 2021Review
- Three-Dimensional Structures of Carbohydrates and Where to Find Them.International journal of molecular sciences · 2020Review
- Dissecting the conformation of glycans and their interactions with proteins.Journal of biomedical science · 2020Review
- In-depth structural analysis of glycans in the gas phase.Chemical science · 2019Review
- Structural Analysis of the Glycosylated Intact HIV-1 gp120-b12 Antibody Complex Using Hydroxyl Radical Protein Footprinting.Biochemistry · 2017Article
- Article
- All-Atom Internal Coordinate Mechanics (ICM) Force Field for Hexopyranoses and Glycoproteins.Journal of chemical theory and computation · 2015Article
- Computational tools for epitope vaccine design and evaluation.Current opinion in virology · 2015Review
- Crystal structure of a fully glycosylated HIV-1 gp120 core reveals a stabilizing role for the glycan at Asn262.Proteins · 2015Article
- Revealing the Mechanisms of Protein Disorder and N-Glycosylation in CD44-Hyaluronan Binding Using Molecular Simulation.Frontiers in immunology · 2015Review
- Importance of ligand conformational energies in carbohydrate docking: Sorting the wheat from the chaff.Journal of computational chemistry · 2014Article
- Glyco-epitope Diversity: An Evolving Area of Glycomics Research and Biomarker Discovery.Journal of proteomics & bioinformatics · 2014Article
- Crossroads between Bacterial and Mammalian Glycosyltransferases.Frontiers in immunology · 2014Review
- Predicting the Origins of Anti-Blood Group Antibody Specificity: A Case Study of the ABO A- and B-Antigens.Frontiers in immunology · 2014Article
- Conference report: "Functional Glycomics in HIV Type 1 Vaccine Design" workshop report, Bethesda, Maryland, April 30-May 1, 2012.AIDS research and human retroviruses · 2013Article
- The influence of N-linked glycans on the molecular dynamics of the HIV-1 gp120 V3 loop.PloS one · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
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.
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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.