COFACTOR is a structure, sequence, and protein-protein interaction (PPI) based
method for biological function annotation of protein molecules.
Starting from the 3D structural model,
COFACTOR will thread the query through the
BioLiP protein funtion database
by local and global structure matches to identify functional sites and
homologies.
Functional insights, including Gene Ontology (GO),
Enzyme Commission (EC), and ligand-binding sites, will be
derived from the best functional homology templates.
For GO, additional insights will be obtained from
UniProt-GOA by sequence and sequence-profile alignments
and from
STRING
by protein-protein interaction inferrals.
The COFACTOR algorithm (as "I-TASSER_FUNCTION") was ranked as the
best method for protein function prediction in the community-wide
CASP9 experiments.
Questions about the COFACTOR server can be posted at the
Service System Discussion Board.
For a given target structure, the output of COFACTOR includes
(
see an illustrative example):
- The top 10 closest structures in the PDB identified by TM-align
- GO terms and the directed acyclic graphs associated with the target protein
- EC numbers, active sites and the enzyme homolog structures of the target protein
- Ligand binding site on target protein and the ligand-protein complex structures
[
Example prediction]
[
Help]
[
Library]
[
Benchmark dataset]
[
Human uPE1 protein annotation]
[
Forum]
References:
- Chengxin Zhang, Peter L. Freddolino, and Yang Zhang.
COFACTOR: improved protein function prediction by combining structure, sequence and protein-protein interaction information.
Nucleic Acids Research, 45: W291-299 (2017).
[PDF]
[Supporting information]
- Ambrish Roy, Jianyi Yang, and Yang Zhang.
COFACTOR: an accurate comparative algorithm for structure-based protein function annotation.
Nucleic Acids Research, 40:W471-W477 (2012).
[PDF]
[Supporting information]
zhanggroup.org
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