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Designing “High-Affinity, High-Specificity” Glycosaminoglycan Sequences Through Computerized Modeling

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Glycosaminoglycans

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1229))

Abstract

The prediction of high-affinity and/or high-specificity protein–glycosaminoglycan (GAG) interactions is an inherently difficult task, due to several factors including the shallow nature of the typical GAG-binding site and the inherent size, flexibility, diversity, and polydisperse nature of the GAG molecules. Here, we present a generally applicable methodology termed Combinatorial Library Virtual Screening (CVLS) that can identify potential high-affinity, high-specificity protein–GAG interactions from very large GAG combinatorial libraries and a suitable GAG-binding protein. We describe the CVLS approach along with the rationale behind it and provide validation for the method using the well-known antithrombin–thrombin–heparin system.

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Acknowledgements

This work was supported by the grants HL090586 and HL107152 from the National Institutes of Health and by Award Number S10RR027411 from the National Center for Research Resources. 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 and Drug Discovery, Virginia Commonwealth University, 800 E. Leigh Street, Suite 212, Richmond, VA, 23298, USA

    Nehru Viji Sankaranarayanan, Aurijit Sarkar, Umesh R. Desai & Philip D. Mosier

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  1. Nehru Viji Sankaranarayanan
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  2. Aurijit Sarkar
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  3. Umesh R. Desai
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  4. Philip D. Mosier
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Corresponding author

Correspondence to Philip D. Mosier .

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Editors and Affiliations

  1. Department of Medicinal Chemistry, University of Utah, Salt Lake City, Utah, USA

    Kuberan Balagurunathan

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

    Hiroshi Nakato

  3. Department of Medicinal Chemistry, Virginia Commonwealth University, Richmond, Virginia, USA

    Umesh R. Desai

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Sankaranarayanan, N.V., Sarkar, A., Desai, U.R., Mosier, P.D. (2015). Designing “High-Affinity, High-Specificity” Glycosaminoglycan Sequences Through Computerized Modeling. In: Balagurunathan, K., Nakato, H., Desai, U. (eds) Glycosaminoglycans. Methods in Molecular Biology, vol 1229. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1714-3_24

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  • DOI: https://doi.org/10.1007/978-1-4939-1714-3_24

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-1713-6

  • Online ISBN: 978-1-4939-1714-3

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