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Identifying metal binding amino acids based on backbone geometries as a tool for metalloprotein engineering.

ABSTRACT: Metal cofactors within proteins perform a versatile set of essential cellular functions. In order to take advantage of the diverse functionality of metalloproteins, researchers have been working to design or modify metal binding sites in proteins to rationally tune the function or activity of the metal cofactor. This study has performed an analysis on the backbone atom geometries of metal-binding amino acids among 10 different metal binding sites within the entire protein data bank. A set of 13 geometric parameters (features) was identified that is capable of predicting the presence of a metal cofactor in the protein structure with overall accuracies of up to 97% given only the relative positions of their backbone atoms. The decision tree machine-learning algorithm used can quickly analyze an entire protein structure for the presence of sets of primary metal coordination spheres upon mutagenesis, independent of their original amino acid identities. The methodology was designed for application in the field of metalloprotein engineering. A cluster analysis using the data set was also performed and demonstrated that the features chosen are useful for identifying clusters of structurally similar metal-binding sites.

SUBMITTER: Nguyen H

PROVIDER: S-EPMC8138524 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Identifying metal binding amino acids based on backbone geometries as a tool for metalloprotein engineering.

Nguyen Hoang H Kleingardner Jesse J

Protein science : a publication of the Protein Society 20210420 6

Metal cofactors within proteins perform a versatile set of essential cellular functions. In order to take advantage of the diverse functionality of metalloproteins, researchers have been working to design or modify metal binding sites in proteins to rationally tune the function or activity of the metal cofactor. This study has performed an analysis on the backbone atom geometries of metal-binding amino acids among 10 different metal binding sites within the entire protein data bank. A set of 13 ...[more]

PMID: 33829594

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Project description:The relationship between structure and function has long been one of the major points of investigation in Biophysics. Understanding how much, or how little, of a protein's often complicated structure is necessary for its function can lead to directed therapeutic strategies and would allow one to design proteins for specific desired functions. Studying protein function by de novo design builds the functionality from the ground up in a completely unrelated and noncoded protein scaffold. Our lab has used this strategy to study heavy and transition metal binding within the TRI family of three stranded coiled coil (3SCC) constructs to understand coordination geometry and metalloenzyme catalytic control within a protein environment. These peptides contain hydrophobic layers within the interior of the 3SCC, which one can mutate to metal binding residues to create a minimal metal binding site, while solid phase synthesis allows our lab to easily incorporate a number of noncoded amino acids including d enantiomers of binding or secondary coordination sphere amino acids, penicillamine, or methylated versions of histidine. Our studies of Cd(II) binding to Cys3 environments have determined, largely through the use of 113Cd NMR and 111mCd PAC, that the coordination environment around a heavy metal can be controlled by incorporating noncoded amino acids in either the primary or secondary coordination spheres. We found mutating the metal binding amino acids to l-Pen can enforce trigonal Cd(II)S3 geometry exclusively compared to the mixed coordination determined for l-Cys coordination. The same result can be achieved with secondary sphere mutations as well by incorporating d-Leu above a Cys3. We hypothesize this latter effect is due to the increased steric packing above the metal binding site that occurs when the l-Leu oriented toward the N-terminus of the scaffold is mutated to d-Leu and oriented toward the C-terminus. Mutating the layer below Cys3 to d-Leu instead formed a mixed 4- and 5-coordinate Cd(II)S3(H2O) and Cd(II)S3(H2O)2 construct as steric bulk was decreased below the metal binding site. We have also applied noncoded amino acids to metalloenzyme systems by incorporating His residues that are methylated at the δ- or ε-nitrogen to enforce Cu(I) ligation to the opposite open nitrogen of His and found a 2 orders of magnitude increased catalytic efficiency for nitrite reductase activity with ε-nitrogen coordination compared to δ-nitrogen. These results exemplify the ability to tune coordination environment and catalytic efficiency within a de novo scaffold as well as the utility of noncoded amino acids to increase the chemist's toolbox. By furthering our understanding of metalloprotein design one could envision, through our use of amino acids not normally available to nature, that protein design laboratories will soon be capable of outperforming the native systems previously used as their benchmark of successful design. The ability to design proteins at this level would have far reaching and exciting benefits within various fields including medical and industrial applications.

Dataset Information

Identifying metal binding amino acids based on backbone geometries as a tool for metalloprotein engineering.

Publications

Identifying metal binding amino acids based on backbone geometries as a tool for metalloprotein engineering.

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