HCV Database
HCV sequence database
 



To our users Please note that the HCV database site is no longer funded. We try to keep the database updated and the tools running, but unfortunately, we cannot guarantee we can provide help for using this site. Data won't be manually curated either.


N-GlycoSite

Purpose: Highlight and tally predicted N-linked glycosylation sites (Nx[ST] patterns, where x can be any amino acid).

Input
Paste your input here
or upload your file

Option
Exclude NP[ST] pattern
Group sequences Do not group
Summarize results by grouped sequences according to:
first character(s) in sequence names
the column in field of sequence names delimited by
paste or upload grouped sequence names (see example below)

Details:
During glycosylation, an oligosaccharide chain is attached to asparagine (N) occurring in the tripeptide sequence N-X-S or N-X-T, where X can be any amino acid except Pro. This sequence is called a glycosylation sequon. The N-GlycoSite tool marks and tallies the locations where this pattern occurs.

The likelihood of N-linked glycosylation of a particular site can be influenced by the context in which it is embedded, and could be expanded to a 4-amino acid NX[ST]Z pattern, where the amino acid in the X or Z position can be important determinants of glycosylation efficiency. For example, a proline in position X or Z strongly disfavors N-linked glycosylation.

O-linked glycosylation signals are more difficult predict, but one can estimate their positions using the NetPhos program at Center for Biological Sequence Analysis.

Input:
Input can be one amino acid sequence, or an alignment of amino acid sequences. If you just want to tally the number of N-glycosylation sites, the protein sequences do not need to be aligned. Standard sequence alignment formats are recognized.

Exclude NP[ST] pattern:
A second position proline (site pattern NP[ST]) is strongly disfavored for glycosylation. Thus the default option excludes these patterns. You may uncheck the box to include them.

Grouped Sequence Names:
If you are analyzing multiple sequences, you can choose how to group them in the analysis. If you are analyzing a single sequence, or you do not want to group your sequences, just ignore these options. Your sequences can be grouped by the first character in the sequence names, or by a set of characters delimiting the sequence names, or by providing a list of groups.

Each sequence must be on a separate line, and groups are separated by an empty line. The first item ending in ':' in a group will be taken as the group name, but this line is optional. If group names are omitted, names will be assigned as Group-1, Group-2, etc. Sequences that are not present in any group will be named 'Others' and colored gray. This is useful for highlighting some groups of sequences out of a target set.

The following can be pasted in as the "grouped sequence names" for testing with the Sample Input:

North America:
1a.US.-.HCV-H
1a.US.-.RBPRESC2C4
1a.US.-.US5
1a.US.-.SCPRESC2C9
1a.US.-.BCS1C13
1a.US.78.FM_78
1a.US.-.HCV-PT
1a.US.81.HW_81
1a.US.-.RHPRESC2D
1a.US.-.RJPRESC2D
1a.US.77.JL_77

Other:
1a.-.-.H77
1a.IT.-.I21
1a.-.-.COLONEL
1a.-.-.HCT23
1a.-.-.PHCV-1/SF9_A
1a.-.-.HCT18
1a.-.-.LTD6-2-XF224

References:

  1. Zhang M et al., Glycobiology. 14(12):1229-46 (2004) -- please cite this reference if you use our tool in a publication.
  2. Marshall RD, Biochem Soc Symp. 40:17-26 (1974)
  3. Kasturi et al., Biochem J. 323 (Pt 2):415-9 (1997)
  4. Mellquist JL et al., Biochemistry. 37(19):6833-7 (1998)



Questions or comments? Contact us at hcv-info@lanl.gov