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Computerized Molecular Modeling for Discovering Promising Glycosaminoglycan Oligosaccharides that Modulate Protein Function

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Glycosaminoglycans

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2303))

Abstract

Glycosaminoglycans (GAGs) are a class of highly negatively charged polysaccharides that plays a major role in various biological processes through their interaction with hundreds of proteins. A major challenge in understanding the specific protein-GAG interaction is their structural diversity and complexity. Recently, computational approaches have been used extensively in addressing this challenge. In this chapter, we present a generally-applicable methodology termed Combinatorial Virtual Library Screening (CVLS) that can identify potential high-affinity, high-specificity sequence(s) binding to a suitable GAG-binding protein from large GAG combinatorial libraries of various lengths and structural patterns.

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Acknowledgments

This work was supported by the grants HL090586, HL107152 and CA241951 from the National Institutes of Health and by Award Number S10RR027411 from the National Center For Research Resources. We thank Drs. Philip Mosier (VCU) and Aurijit Sarkar (High Point University) for making Figs. 2, 3 and 5. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center For Research Resources or the National Institutes of Health.

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Authors and Affiliations

  1. Department of Medicinal Chemistry & Institute for Structural Biology, Drug Discovery and Development, Virginia Commonwealth University, Richmond, VA, USA

    Nehru Viji Sankaranarayanan & Umesh Desai

Authors
  1. Nehru Viji Sankaranarayanan
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  2. Umesh Desai
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Corresponding author

Correspondence to Nehru Viji Sankaranarayanan .

Editor information

Editors and Affiliations

  1. Departments of Biology, Bioengineering, and Medicinal Chemistry, University of Utah, Salt Lake City, UT, USA

    Kuberan Balagurunathan

  2. Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN, USA

    Hiroshi Nakato

  3. Department of Medicinal Chemistry and Institute for Structural Biology, Drug Discovery and Development, Virginia Commonwealth University, Richmond, VA, USA

    Umesh Desai

  4. Department of Neurobiology & Department of Nutrition & Integrative Physiology, University of Utah, Salt Lake City, UT, USA

    Yukio Saijoh

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Sankaranarayanan, N.V., Desai, U. (2022). Computerized Molecular Modeling for Discovering Promising Glycosaminoglycan Oligosaccharides that Modulate Protein Function. In: Balagurunathan, K., Nakato, H., Desai, U., Saijoh, Y. (eds) Glycosaminoglycans. Methods in Molecular Biology, vol 2303. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1398-6_41

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  • DOI: https://doi.org/10.1007/978-1-0716-1398-6_41

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1397-9

  • Online ISBN: 978-1-0716-1398-6

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