The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation.
Structural genomics efforts have led to increasing numbers of novel, uncharacterized protein structures with low sequence identity to known proteins, resulting in a growing need for structure-based function recognition tools. Our method, SeqFEATURE, robustly models protein functions described by sequence motifs using a structural representation. We built a library of models that shows good performance compared to other methods. In particular, SeqFEATURE demonstrates significant improvement over other methods when sequence and structural similarity are low.
Wu
Shirley
S
Program in Biomedical Informatics, Stanford University, Stanford, CA, 94305 USA.
Liang
Mike P
MP
Altman
Russ B
RB
D000595:Amino Acid Sequence; D030562:Databases, Protein; D008722:Methods; D011506:Proteins / Q000737:chemistry* / Q000502:physiology; D040681:Structural Homology, Protein
D011506:Proteins