Improvement in protein functional site prediction by distinguishing structural and functional constraints on protein family evolution using computational design.
The prediction of functional sites in newly solved protein structures is a challenge for computational structural biology. Most methods for approaching this problem use evolutionary conservation as the primary indicator of the location of functional sites. However, sequence conservation reflects not only evolutionary selection at functional sites to maintain protein function, but also selection throughout the protein to maintain the stability of the folded state. To disentangle sequence conservation due to protein functional constraints from sequence conservation due to protein structural constraints, we use all atom computational protein design methodology to predict sequence profiles expected under solely structural constraints, and to compute the free energy difference between the naturally occurring amino acid and the lowest free energy amino acid at each position. We show that functional sites are more likely than non-functional sites to have computed sequence profiles which differ significantly from the naturally occurring sequence profiles and to have residues with sub-optimal free energies, and that incorporation of these two measures improves sequence based prediction of protein functional sites. The combined sequence and structure based functional site prediction method has been implemented in a publicly available web server.
Cheng
Gong
G
Department of Biochemistry, University of Washington Seattle, Washington, USA.
Qian
Bin
B
Samudrala
Ram
R
Baker
David
D
D000465:Algorithms; D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D017124:Conserved Sequence; D004798:Enzymes / Q000737:chemistry; D019143:Evolution, Molecular; D008958:Models, Molecular; D011506:Proteins / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D020539:Sequence Analysis, Protein / Q000379:methods
D000596:Amino Acids; D004798:Enzymes; D011506:Proteins