AMPK Methods and Protocols

(K|R|H)(L|V|M|I|A|F)(K|R|H)...(S|T)...(I|L|V|M|A|F)", proteomehuman)]

8. Remove any duplicated hits by running the following code at
   the console in RStudio:

humanduprm<- myhitshuman[!duplicated(myhitshuman),]

9. Compile the protein sequences containing an AMPK consen-
   sus sequence to individual strings by running the following
   code at the console in RStudio:

seq<- NULL;

for (z in 1:length(humanduprm)){;

seq[z]<- toString(humanduprm[z])};

Sequence<- data.table(sequence=seq)

10. Compile protein IDs by running the following code at the
    console in RStudio:

accession<- data.table(longname=humanduprm@ranges@NAMES);
accession[,ensembl_peptide_id:= word(longname)];
accession$longname<- NULL;
accession$ensembl_peptide_id<- sub("\cr..*", "", accession$ensembl_peptide_id)

11. Download gene symbols IDs by running the following code at
    the console in RStudio:

Keys<- accession$ensembl_peptide_id
mymarthuman<- useMart("ENSEMBL_MART_ENSEMBL",
host="www.ensembl.org");
mymarthuman
useMart("ENSEMBL_MART_ENSEMBL",dataset="hsapiens_gene_ensembl",
host="www.ensembl.org");
myhitshuman_genename<- getBM(attributes=c("ensembl_peptide_id",
"external_gene_name"), values = Keys, mart = mymarthuman)

12. Create a data table by running the following code at the
    console in RStudio:

myhitshuman<- cbind(Sequence, accession);

myhitshuman<- merge(myhitshuman, myhitshuman_genename, by =

"ensembl_peptide_id")

13. The data table can then be written out to an Excel workbook
    by running the following code at the console in RStudio (see
    Notes 11and 12 ):

write.table(myhitshuman, file = "AMPK consensus sequence containing proteins.xls",
sep = "\t", quote = FALSE, row.names = FALSE)

Identification and Validation of Novel Targets 103