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Rothe, M. L.

Publications and source records attributed to Rothe, M. L..

2 recordsLinked to original sources

Substrate scope and catalytic mechanism of α, β-epoxyketone synthase EpnF illuminated by in-situ esterase-mediated deprotection

, {beta}-Epoxyketones are an important class of bacterial natural products with wide-ranging potential applications in oncology, immunology, and infectious disease. Their clinical potential derives from the , {beta}-epoxyketone pharmacophore, which covalently modifies the N-terminal catalytic threonine residue of proteasome {beta}-subunits with high selectivity. Although a synthetic , {beta}-epoxyketone (Carfilzomib) is approved for clinical use, stereo-controlled synthesis of the pharmacophore remains challenging, involving either multiple steps and energy-intensive processes, or unsustainable reagents. Unusual flavoenzymes catalyze the assembly of the pharmacophore in , {beta}-epoxyketone biosynthesis. A detailed understanding of the substrate scope and catalytic mechanism of these enzymes has thus far been limited by the intrinsic instability of their - (di)methyl-{beta}-ketoacid substrates. Here, we report the development and application of an esterase-mediated unmasking strategy for in-situ generation of these substrates from the corresponding methyl esters. Using this approach, we demonstrate that EpnF, the epoxyketone synthase involved in eponemycin / TMC-86A biosynthesis, tolerates a broad range of synthetic substrate analogs, including several with N-terminal protecting groups widely used in peptide synthesis. These findings establish that EpnF has the potential to be developed into a useful biocatalyst for the chemoenzymatic synthesis of dipeptidyl epoxyketone precursors of clinically approved drugs and drug candidates. To elucidate the molecular basis for catalysis of , {beta}-epoxyketone formation by EpnF, substrate docking and molecular dynamics simulations were performed on a well-validated AlphaFold model, providing support for a previously proposed decarboxylation-dehydrogenation-monooxygenation mechanism. Site-directed mutagenesis and LC-MS analysis validated the proposed roles of key active-site residues in substrate positioning and catalysis of epoxide formation. Collectively, these results demonstrate that EpnF and related enzymes belong to a new class of internal flavoprotein monooxygenases and provide a foundation for developing epoxyketone synthases into useful biocatalysts for the sustainable synthesis of high-value ,{beta}-epoxyketones.

biochemistry↗

PARAS: high-accuracy machine-learning of substrate specificities in nonribosomal peptide synthetases

Nonribosomal peptides are diverse natural products with important applications in medicine and agriculture. Bacterial and fungal genomes contain thousands of nonribosomal peptide biosynthetic gene clusters (BGCs) of unknown function, providing a promising resource for peptide discovery. Core structural features of such peptides can be inferred by predicting the substrate(s) of adenylation (A) domains in nonribosomal peptide synthetases (NRPSs). However, existing approaches to A domain prediction rely on limited datasets and often struggle with domains selecting large substrates or from less-studied taxa. Here, we systematically curate and computationally analyse 3,653 A domains and present two high-accuracy specificity predictors, PARAS and PARASECT. A type of A domain with unusually high L-tryptophan specificity was identified through the application of PARAS, and intact protein mass spectrometry to the corresponding NRPS showed it to direct the production of tryptopeptin-related metabolites in Streptomyces species. Together, these technologies will accelerate the characterisation of novel NRPSs and their metabolic products. PARAS and PARASECT are available at https://paras.bioinformatics.nl. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/631717v2_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@8e48aaorg.highwire.dtl.DTLVardef@144c78dorg.highwire.dtl.DTLVardef@890c11org.highwire.dtl.DTLVardef@1776de9_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗