Bioinformatics for Glycobiology and Glycomics 2009
DOI: 10.1002/9780470029619.ch9
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Prediction of Glycosylation Sites in Proteins

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Cited by 7 publications
(2 citation statements)
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“…When comparing antigen-specific plasmablast sequences, the SHM frequency full V-region was compared. N-glycan sites in the heavy and light chain variable regions were predicted by NetNGlyc 1.0 (76).…”
Section: Bioinformatic Analysis Of Ig Sequencesmentioning
confidence: 99%
“…When comparing antigen-specific plasmablast sequences, the SHM frequency full V-region was compared. N-glycan sites in the heavy and light chain variable regions were predicted by NetNGlyc 1.0 (76).…”
Section: Bioinformatic Analysis Of Ig Sequencesmentioning
confidence: 99%
“…The S Protein was mutated using PyMOL59 to the D614G and A372T S protein variants. After mutation, energy minimization was performed using the OPLS3e force field.To identify glycosylation propensity and predicted glycosylated residues of the WT S Protein and the A372T mutant, the NetNGlyc 1.0 Server60 and Schrödinger-Maestro's BioLuminate (v. 2020-2) Reactive Residue package was used58,[61][62][63] . Schrödinger-Maestro's (v. 2020-2) Workspace Operations was used for glycosylation of the Asn370 with mannose, to identify various Asn370-glycan rotamers, to analyzes the surface residue properties of the WT S Protein and A372T mutant.…”
mentioning
confidence: 99%