The prediction and characterization of metal binding sites in proteins.
The rational engineering of novel functions into proteins can only be attempted when the underlying structural scaffold on which the new function is displayed and the structure of the target protein are both well understood. To introduce functions mediated by metals it is therefore necessary to identify the principal liganding residues for the chosen metal, the required architecture of the metal-ligand complex and sites within the target protein that could accommodate such sites. Here we present a method that applies structural information from the protein data bank to the ab initio design and characterization of novel metal binding sites. The prediction method has been tested on 28 metalloprotein structures from the Brookhaven Protein Data Bank. It successfully identified > 90% of the metal binding sites. In addition, we have used the method to design and characterize zinc binding sites in two antibody structures. Metal binding studies on one of these putative metalloantibodies showed metal binding, confirming the predictive power of the method.
Gregory
D S
DS
Laboratory of Molecular Biophysics, Oxford, UK.
Martin
A C
AC
Cheetham
J C
JC
Rees
A R
AR
D000465:Algorithms; D000906:Antibodies / Q000737:chemistry / Q000378:metabolism; D001665:Binding Sites; D002412:Cations / Q000737:chemistry / Q000378:metabolism; D003198:Computer Simulation; D016208:Databases, Factual; D008667:Metalloproteins / Q000737:chemistry* / Q000276:immunology / Q000378:metabolism; D008670:Metals / Q000737:chemistry / Q000378:metabolism*; D008958:Models, Molecular; D009113:Muramidase / Q000276:immunology; D011487:Protein Conformation; D015202:Protein Engineering / Q000379:methods*; D015032:Zinc / Q000737:chemistry / Q000378:metabolism
D000906:Antibodies; D002412:Cations; D008667:Metalloproteins; D008670:Metals; D009113:Muramidase; D015032:Zinc