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1.
J Biol Chem ; 298(6): 102040, 2022 06.
Artigo em Inglês | MEDLINE | ID: mdl-35595101

RESUMO

The enzyme m1A22-tRNA methyltransferase (TrmK) catalyzes the transfer of a methyl group to the N1 of adenine 22 in bacterial tRNAs. TrmK is essential for Staphylococcus aureus survival during infection but has no homolog in mammals, making it a promising target for antibiotic development. Here, we characterize the structure and function of S. aureus TrmK (SaTrmK) using X-ray crystallography, binding assays, and molecular dynamics simulations. We report crystal structures for the SaTrmK apoenzyme as well as in complexes with methyl donor SAM and co-product product SAH. Isothermal titration calorimetry showed that SAM binds to the enzyme with favorable but modest enthalpic and entropic contributions, whereas SAH binding leads to an entropic penalty compensated for by a large favorable enthalpic contribution. Molecular dynamics simulations point to specific motions of the C-terminal domain being altered by SAM binding, which might have implications for tRNA recruitment. In addition, activity assays for SaTrmK-catalyzed methylation of A22 mutants of tRNALeu demonstrate that the adenine at position 22 is absolutely essential. In silico screening of compounds suggested the multifunctional organic toxin plumbagin as a potential inhibitor of TrmK, which was confirmed by activity measurements. Furthermore, LC-MS data indicated the protein was covalently modified by one equivalent of the inhibitor, and proteolytic digestion coupled with LC-MS identified Cys92 in the vicinity of the SAM-binding site as the sole residue modified. These results identify a cryptic binding pocket of SaTrmK, laying a foundation for future structure-based drug discovery.


Assuntos
Proteínas de Bactérias , Staphylococcus aureus , tRNA Metiltransferases , Adenina , Proteínas de Bactérias/química , Proteínas de Bactérias/metabolismo , Cristalografia por Raios X , Conformação Proteica , RNA de Transferência/metabolismo , S-Adenosilmetionina/metabolismo , Staphylococcus aureus/enzimologia , tRNA Metiltransferases/química , tRNA Metiltransferases/metabolismo
2.
ACS Catal ; 12(4): 2381-2396, 2022 Feb 18.
Artigo em Inglês | MEDLINE | ID: mdl-37325394

RESUMO

Deep mutational scanning (DMS) has recently emerged as a powerful method to study protein sequence-function relationships but it has not been well-explored as a guide to enzyme engineering and identifying pathways by which their catalytic cycle may be improved. We report such a demonstration in this work using a Phenylalanine ammonia-lyase (PAL), which deaminates L-phenylalanine to trans-cinnamic acid and has widespread application in chemo-enzymatic synthesis, agriculture, and medicine. In particular, the PAL from Anabaena variabilis (AvPAL*) has garnered significant attention as the active ingredient in Pegvaliase®, the only FDA-approved drug treating classical Phenylketonuria (PKU). Although an extensive body of literature exists on the structure, substrate-specificity, and catalytic cycle, protein-wide sequence determinants of function remain unknown, as do intermediate reaction steps that limit turnover frequency, all of which has hindered rational engineering of these enzymes. Here, we created a detailed sequence-function landscape of AvPAL* by performing DMS and revealed 112 mutations at 79 functionally relevant sites that affect a positive change in enzyme fitness. Using fitness values and structure-function analysis, we picked a subset of positions for comprehensive single- and multi-site saturation mutagenesis and identified combinations of mutations that led to improved reaction kinetics in cell-free and cellular contexts. We then performed QM/MM and MD to understand the mechanistic role of the most beneficial mutations and observed that different mutants confer improvements via different mechanisms, including stabilizing transition and intermediate states, improving substrate diffusion into the active site, and decreasing product inhibition. This work demonstrates how DMS can be combined with computational analysis to effectively identify significant mutations that enhance enzyme activity along with the underlying mechanisms by which these mutations confer their benefit.

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