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Molecular Dynamics Simulation-Based Prediction of Glycosaminoglycan Interactions with Drug Molecules

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Computational Drug Discovery and Design

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2714))

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Abstract

Glycosaminoglycans (GAGs) are a class of long linear anionic periodic polysaccharides. Their biological activities are very broad including tissue remodeling, regulation of cell proliferation, cell migration, cell differentiation, participation in bacterial/viral infections, and immune response. They can interact with many important biomolecular partners in the extracellular matrix of the cell including small drug molecules. Recently, several GAG-bioactive small molecule complexes have been experimentally and theoretically studied. Some of these compounds in complexes with GAGs may potentially interfere with protein–GAG or peptide–GAG multimolecular systems affecting the processes of cellular differentiation or have anti-inflammatory, antiviral as well as antithrombotic effects. Although many studies have been conducted on GAG–drug complexes, the molecular mechanisms of the formation of such complexes are still poorly understood. At the same time, the complexity of their physicochemical properties renders the use of both experimental and computational methods to study these molecular systems challenging. Here, we present the molecular dynamics-based protocols successfully employed to in silico analyze GAG–small molecule interactions.

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Acknowledgments

This research was funded by the National Science Centre of Poland, grant number UMO-2018/30/E/ST4/00037.

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Correspondence to Sergey A. Samsonov .

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Maszota-Zieleniak, M., Samsonov, S.A. (2024). Molecular Dynamics Simulation-Based Prediction of Glycosaminoglycan Interactions with Drug Molecules. In: Gore, M., Jagtap, U.B. (eds) Computational Drug Discovery and Design. Methods in Molecular Biology, vol 2714. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3441-7_8

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  • DOI: https://doi.org/10.1007/978-1-0716-3441-7_8

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3440-0

  • Online ISBN: 978-1-0716-3441-7

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