MFS - protein meta-functional signature indicating functional importance of each residue
- Wang K, Horst, J, Cheng G, Nickle D, Samudrala R. Protein
meta-functional signatures from combining sequence, structure, evolution
and amino acid property information. PLoS Computational Biology 4:e1000181,
2008.
- Cheng G, Qian B, Samudrala R, Baker D.
Improvement in protein functional site prediction by distinguishing
structural and functional constraints on protein family evolution
using computational design. Nucleic Acids Research
33: 5861-5867, 2005.
- Wang K, Samudrala R. FSSA:
A novel method for identifying functional signatures from structural
alignments. Bioinformatics 21: 2969-2977, 2005.
This module is under active development and is being currently
tested.
Given either a protein structure in PDB format or a protein
sequence, the MFS server module will return a prediction of
meta-functional signature: a score for each residue in the structure
or sequence indicating its relative functional importance. In
addition, for submitted structure, a new structure file with the
temperature factor field replaced by meta-functional signature scores
will be created to enable visual inspection of functionally important
regions using molecular graphics software.
Download the MFS as a standalone application.
Protinfo ||
Bioverse ||
Samudrala Computational Biology Research Group ||
protinfo@compbio.washington.edu