GCPred is a webserver for the prediction of functional guanylyl cyclase centers (GCCs) from amino acid sequence. GCC is a novel class of functional centers typically consisting of short 14 amino acids. GCPred is not valid for the prediction of canonical GC domains and transmembrane regions.

The software takes a single or multiple amino acid sequences and returns predicted GCCs each accompanied by GCC values 0-1. The results are available for download as excel sheet and are interpreted in graphs.

Please select the motif:
Mental iron binding?

Please enter single letter amino acid codes in FASTA format:
For example

>sp|Q8VYA3|WAKLJ_ARATH Wall-associated receptor kinase-like 10 OS=Arabidopsis thaliana GN=WAKL10 PE=2 SV=1
MSSNCSCSLLSLFSLLLIIDLTVASSCPKTCGGIDIPYPFGIGTGCYLEKWYEIICVNNSVPFLSIINREVVSISFSDMYRRFFNVGYGSIRIRNPIASKGCSSGGQEFGSLLNMTGYPFYLGDNNMLIAVGCNNTASLTNVEPSIVGCESTCST
NQDIPINDYLGVLYCNARYGDSEYCKNISIMNDTSCNGIGCCKASLPARYQQIIGVEIDDSNTESKGCKVAFITDEEYFLSNGSDPERLHANGYDTVDLRWFIHTANHSFIGSLGCKSIDEYTILRRDNREYGIGCLCDYNSTTTGYATCSCASG
FEGNPYIPGECKDINECVRGIDGNPVCTAGKCVNLLGGYTCEYTNHRPLVIGLSTSFSTLVFIGGIYWLYKFIRRQRRLNQKKKFFKRNGGLLLQQQLTTTEGNVDSTRVFNSRELEKATENFSLTRILGEGGQGTVYKGMLVDGRIVAVKKSKV
VDEDKLEEFINEVVILSQINHRNIVKLLGCCLETDVPILVYEFIPNGNLFEHLHDDSDDYTMTTWEVRLRIAVDIAGALSYLHSAASSPIYHRDIKSTNIMLDEKHRAKVSDFGTSRTVTVDHTHLTTVVSGTVGYMDPEYFQSSQFTDKSDVYS
FGVVLAELITGEKSVSFLRSQEYRTLATYFTLAMKENRLSDIIDARIRDGCKLNQVTAAAKIARKCLNMKGRKRPSMRQVSMELEKIRSYSEDMQPYEYASENEEEKKETLVDVNVESRNYVSVTAASSQYSIATTSSSRSDVEPLFPR





If you find GCPred useful for your work, please cite:

GCPred was built based on previous work published in:
Wheeler J, Wong A, Marondedze C, Arnoud G, Kwezi L et al. (2017). Plant J 91(4), 590-600
Wong A, Gehring C & Irving HR (2015). Front Bioeng Biotechnol 82, 1-8
Wong A & Gehring C (2013). Cell Commun Signal, 11(1), 48
Wong A & Gehring C (2013). Methods Mol Biol, 1016, 195-205, Humana Press
Ludidi N & Gehring C (2003). J Biol Chem 278(8), 6490-6494

This tool is still under development and the GCC values will be revised as new experimental data becomes available. Additional features and improvements are forthcoming.

Please contact us at alwong@kean.edu if you have any questions or comments.