Scans the indicated protein in search of methylation sites


me.scan(up_id, db = 'all')


up_id a character string corresponding to the UniProt ID.

db the database where to search. It should be one among ‘PSP’, ‘dbPTM’, ‘all’.


Returns a dataframe where each row corresponds to a modifiable residue.


Hornbeck et al. Nucleic Acids Res. 2019 47:D433-D441.
Huang et al. Nucleic Acids Res. 2019 47:D298-D308.

See Also

ac.scan(), meto.scan(), p.scan(), gl.scan(), ub.scan(), su.scan(), dis.scan(), sni.scan(), ni.scan(), ptm.scan(), reg.scan()

Protein methylation is a type of post-translational modification featuring the addition of methyl groups to proteins, that can occur on the nitrogen-containing side-chains of arginine and lysine. Methylation is known to have a regulatory role in many essential cellular processes that range from gene transcription to signal transduction.

The package ptm provides a function, me.scan(), that aims to integrate information from different PTM databases, and assist to identify methylation sites in a given protein. The UniProt ID of the protein of interest must be passed as argument. A second argument for this function is db, used to indicate the database to be searched. The databases accessible for this purpose are:

  • PSP: PhosphoSitePlus.
  • dbPTM: database of Post-Translational Modifications.

By default, me.scan() use all above databases to search for methylation sites. In this case, it should be noted that the same methylation site can appear twice if it is present in both databases. If we wish to get a list of unique methylation sites found, for instance, in the protein Histone H3.1t, we can proceed as follows:

First, you need to search for the UniProt ID. If the protein in question is found into MetOSite, you can search the ID:

id <- meto.list('Histone H3.1t')$prot_id

## [1] "Q16695"

Otherwise, go to the UniProt page to search for the ID.



##  [1] "K5-m1"   "K10-m3"  "K10-m1"  "K15-m3"  "K24-m1"  "K28-m3"  "K28-m2"  "K28-m1" 
##  [9] "K37-m2"  "K37-m3"  "K37-m1"  "K38-m1"  "K38-m2"  "K38-m3"  "R41-m1"  "R41-m2" 
## [17] "R43-m1"  "R50-m1"  "R64-m1"  "K65-m1"  "K80-m1"  "K80-m2"  "R84-m1"  "R129-m1"
## [25] "K5-me"   "K10-me"  "K15-me"  "K24-me"  "K28-me"  "K37-me"  "K38-me"  "R41-me" 
## [33] "K80-me"

Occasionally, it may be deirable to use more astringent criteria, and search only for sites that has been described as functionally relevant. To this end, we can use the function reg.scan() as follows:


##       up_id     organism modification database
## 5944 Q16695 Homo sapiens       K80-m2      PSP
## 7265 Q16695 Homo sapiens       K80-m1      PSP