SulfoSite is to computationally predict sulfation sites within given protein sequences. The sulfotransferase reaction relies on the co-substrate PAPS as sulfuryl donor.

The known sulfation sites are categorized by substrate sequences. Profile Hidden Markov Model (HMM) is applied for learning to each group of sequences surrounding to the sulfation residues.

Citation:
Tzong-Yi Lee, H.D. Huang (joint first authorship), J.H. Hung, Y.S. Yang, and T.H. Wang. (2006) "dbPTM: An Information Repository of Protein Post-Translational Modification" Nucleic Acids Research, Vol. 34, D622-D627.


Submission

Paste a single sequence or several sequences in FASTA format into the field below:

Submit a file in FASTA format directly from your local disk:

Predict on: Tyrosine(Y)      Kinase :

HMM bit score > by default

Bid Lab, Institute of Bioinformatics, National Chiao Tung University , Taiwan.
Contact us:bryan@mail.nctu.edu.tw with questions or comments.
Websites:http://SulfoSite.mbc.nctu.edu.tw/