Controlling Enzyme Inhibition Using an Expanded Set of Genetically Encoded Amino Acids
Zheng, Shun, Chemical Engineering - School of Engineering and Applied Science, University of Virginia
Kwon, Inchan, Department of Chemical Engineering, University of Virginia
Enzyme inhibition plays an important role in drug development, metabolic pathway regulation, and biocatalysis with product inhibition. When an inhibitor is structurally highly similar to the substrate of an enzyme, controlling inhibitor binding without affecting substrate binding is often challenging and requires fine tuning of the active site. A carefully selected, extended set of genetically encoded amino acids is hypothesized to precisely modify the enzyme active site to reduce inhibitor binding without compromising substrate binding. To validate this hypothesis, murine dihydrofolate reductase (mDHFR), its substrate dihydrofolate (DHF), and inhibitor methotrexate (MTX) were chosen as a model system. Structural models of mDHFR variants containing non-natural amino acids (NAAs) complexed with each ligand were constructed to identify a key residue for inhibitor binding and NAAs to replace the key residue. Two mutants containing pBrF and 2Nal at position 31 (mDHFRpBrF31 and mDHFR2Nal31) were prepared. The three mDHFR samples (mDHFRWT, mDHFRpBrF31, and mDHFR2Nal31) were used for inhibitor binding assays and kinetic analysis. The results revealed that replacing the phenylalanine at position 31 with two phenylalanine analogs (p-bromophenylalanine (pBrF) and L-2-naphthylalanine (2Nal)) enhanced binding affinity toward the substrate DHF over the inhibitor MTX by 3.9 and 5.6 times, respectively. Such an enhanced selectivity was mainly due to a reduced inhibitor binding affinity by 2.1±1.1 and 4.3±2.0 times, respectively. The catalytic efficiency of the mDHFR variant containing pBrF was comparable to that of wild-type mDHFR, whereas the mDHFR variant containing 2Nal exhibited a moderate decrease in the catalytic efficiency. The work described here clearly demonstrated the feasibility of selectively controlling enzyme inhibition using an expanded set of genetically encoded amino acids.
MS (Master of Science)
protein engineering, enzyme engineering, non-natural amino acids
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