Glycan Reader: Automated Sugar Identification and Simulation Preparation for Carbohydrates and Glycoproteins
Song, Kevin C.
MacKerell, Alexander D., Jr.
Scholarly/refereed, author accepted manuscript
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Understanding how glycosylation affects protein structure, dynamics, and function is an emerging and challenging problem in biology. As a first step toward glycan modeling in the context of structural glycobiology, we have developed Glycan Reader and integrated it into the CHARMMGUI, http://www.charmm-gui.org/input/glycan. Glycan Reader greatly simplifies the reading of PDB structure files containing glycans through (i) detection of carbohydrate molecules, (ii) automatic annotation of carbohydrates based on their three-dimensional structures, (iii) recognition of glycosidic linkages between carbohydrates as well as N-/O-glycosidic linkages to proteins, and (iv) generation of inputs for the biomolecular simulation program CHARMM with the proper glycosidic linkage setup. In addition, Glycan Reader is linked to other functional modules in CHARMM-GUI, allowing users to easily generate carbohydrate or glycoprotein molecular simulation systems in solution or membrane environments and visualize the electrostatic potential on glycoprotein surfaces. These tools are useful for studying the impact of glycosylation on protein structure and dynamics.
This is the peer reviewed version of the following article: Jo, S., Song, K. C., Desaire, H., MacKerell, A. D., & Im, W. (2011). Glycan Reader: Automated Sugar Identification and Simulation Preparation for Carbohydrates and Glycoproteins. Journal of Computational Chemistry, 32(14), 3135–3141. http://doi.org/10.1002/jcc.21886, which has been published in final form at http://doi.org/10.1002/jcc.21886. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Jo, S., Song, K. C., Desaire, H., MacKerell, A. D., & Im, W. (2011). Glycan Reader: Automated Sugar Identification and Simulation Preparation for Carbohydrates and Glycoproteins. Journal of Computational Chemistry, 32(14), 3135–3141. http://doi.org/10.1002/jcc.21886
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