Carbohydrates decorate proteins and cell surfaces serving as recognition entities for disease and immune processes, are implicated in cell aging and are used as biological signal carriers. One reason they are useful in so many ways is that they can adopt a staggering variety of shapes. Partly because of their importance to biological systems, and partly because of their structural complexity, it is critical that scientists, especially those studying their biological roles, be able easily to generate accurate and useful 3D models of them and their complexes with proteins. However, because of the structural complexity of carbohydrates, generation of these models is very difficult. Even researchers who are comfortable with computer modeling of biological systems can find the task daunting. It is not sufficient, however, only to facilitate accurate modeling for computational specialists. In order to overcome the barrier to adoption of such methods by a broad base of researchers, it is important that the software be intuitive and provides guidance in appropriate use. The GLYCAM-Web suite of online tools (www.glycam.org) has been making steps toward this goal for a number of years. Six years ago, it began as an in-house tool for the Woods carbohydrate modeling research group. Shortly thereafter it was released publically as an online utility free of charge. Site statistics have been gathered for approximately 5 years, and typically averages 400-500 visits each month. Based on support requests, solicited user letters, and references to the site found in academic journals, it is primarily used by persons engaged in biological research. The site was not initially designed with the anticipation of such expansion, nor was it initially intended for such a wide base of researchers. The purpose of this project is to update and transform the GLYCAM-Web suite of modeling tools into a stable, robust, informative and intuitive utility that is capable of meeting the current and future needs of glycobiology research. To achieve these goals, the site's software will be restructured so that it is built of self-contained, well-tested modules that are easy to maintain and modify. Its data structure will facilitate the addition of new functionality. To enable external researchers to use the software locally and modify it to meet their needs, the command-line interface on which the site is built will be released to the public. Submissions and corrections from the user community will be encouraged. To make the site usable by a wider variety of researchers, notably that are not primarily computer scientists, several features will be added or enhanced and site documentation will be greatly expanded based on user requests. Among the features to be added or enhanced are smarter error- checking, simplified builds of complex structures, an increased number of supported file formats, and interfaces with external web sites.

Public Health Relevance

Carbohydrates serve many roles in human health, being involved in processes such as immune response and cell aging in addition to their better-known roles in nutrition. However, unlike proteins, carbohydrates form highly branched and heterogeneous structures, making their experimental analysis uniquely challenging. Computational methods have an opportunity to help in understanding their 3D properties by providing reliable models. The goal of this project is to improve existing software already shown to facilitate carbohydrate modeling, making it more stable, extensible and usable by scientists doing health-related research but who are not necessarily computer modeling experts.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM100058-02
Application #
8458934
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Brazhnik, Paul
Project Start
2012-05-01
Project End
2016-02-29
Budget Start
2013-03-01
Budget End
2014-02-28
Support Year
2
Fiscal Year
2013
Total Cost
$269,583
Indirect Cost
$81,408
Name
University of Georgia
Department
Type
Organized Research Units
DUNS #
004315578
City
Athens
State
GA
Country
United States
Zip Code
30602
Xie, Boer; Sood, Amika; Woods, Robert J et al. (2017) Quantitative Protein Topography Measurements by High Resolution Hydroxyl Radical Protein Footprinting Enable Accurate Molecular Model Selection. Sci Rep 7:4552
Li, Xiaoyan; Grant, Oliver C; Ito, Keigo et al. (2017) Structural Analysis of the Glycosylated Intact HIV-1 gp120-b12 Antibody Complex Using Hydroxyl Radical Protein Footprinting. Biochemistry 56:957-970
de Vries, Robert P; Peng, Wenjie; Grant, Oliver C et al. (2017) Three mutations switch H7N9 influenza to human-type receptor specificity. PLoS Pathog 13:e1006390
Wang, Xiaocong; Woods, Robert J (2016) Insights into furanose solution conformations: beyond the two-state model. J Biomol NMR 64:291-305
Khatri, Kshitij; Klein, Joshua A; White, Mitchell R et al. (2016) Integrated Omics and Computational Glycobiology Reveal Structural Basis for Influenza A Virus Glycan Microheterogeneity and Host Interactions. Mol Cell Proteomics 15:1895-912
Chalmers, G; Glushka, J N; Foley, B L et al. (2016) Direct NOE simulation from long MD trajectories. J Magn Reson 265:1-9
Nivedha, Anita K; Thieker, David F; Makeneni, Spandana et al. (2016) Vina-Carb: Improving Glycosidic Angles during Carbohydrate Docking. J Chem Theory Comput 12:892-901
Singh, Arunima; Tessier, Matthew B; Pederson, Kari et al. (2016) Extension and validation of the GLYCAM force field parameters for modeling glycosaminoglycans. Can J Chem 94:927-935
Grant, Oliver C; Tessier, Matthew B; Meche, Lawrence et al. (2016) Combining 3D structure with glycan array data provides insight into the origin of glycan specificity. Glycobiology 26:772-783
Hsu, Che-Hsiung; Park, Sangho; Mortenson, David E et al. (2016) The Dependence of Carbohydrate-Aromatic Interaction Strengths on the Structure of the Carbohydrate. J Am Chem Soc 138:7636-48

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