Molecular Basis for Asynchronous Chain Elongation During Rifamycin Antibiotic Biosynthesis
Liu, C.; West, R. C.; Chen, M.; Cohn, W.; Wang, G.; Mandot, A. M.; Kim, S.; Cogan, D. P.
Show abstract
The rifamycin synthetase (RIFS) from the bacterium Amycolatopsis mediterranei is a large (3.5 MDa) multienzyme system that catalyzes over 40 chemical reactions to generate a complex precursor to the antibiotic rifamycin B. It is considered a hybrid enzymatic assembly line and consists of an N-terminal nonribosomal peptide synthetase loading module followed by a decamodular polyketide synthase (PKS). While the biosynthetic functions are known for each enzymatic domain of RIFS, structural and biochemical analyses of this system from purified components are relatively scarce. Here, we examine the biosynthetic mechanism of RIFS through complementary crosslinking, kinetic, and structural analyses of its first PKS module (M1). Thiol-selective crosslinking of M1 provided a plausible molecular basis for previously observed conformational asymmetry with respect to ketosynthase (KS)-substrate carrier protein (CP) interactions during polyketide chain elongation. Our data suggest that C-terminal dimeric interfaces--which are ubiquitous in bacterial PKSs--force their adjacent CP domains to co-migrate between two equivalent KS active site chambers. Cryogenic electron microscopy analysis of M1 further supported this observation while uncovering its unique architecture. Single-turnover kinetic analysis of M1 indicated that although removal of C-terminal dimeric interfaces supported 2-fold greater KS-CP interactions, it did not increase the partial product occupancy of the homodimeric protein. Our findings cast light on molecular details of natural antibiotic biosynthesis that will aid in the design of artificial megasynth(et)ases with untold product structures and bioactivities. Significance StatementBacteria use enzymatic assembly lines for the manufacture of complex and often medicinally active organic compounds. Their conserved modular design and biosynthetic logic suggest they evolved to be intrinsically reprogrammable. Yet, strategies to manipulate assembly-line product structures through protein engineering are still met with considerable challenges. This work investigates how a representative bacterial assembly line catalyzes an essential reaction during biosynthesis of the antibiotic rifamycin. Our data provide a molecular rationale for asynchronous C-C bond formation catalyzed by equivalent subunits of the homodimeric system while exposing new aspects of assembly line architecture. These findings represent a step closer towards the design of artificial assembly lines for sustainable production of user-defined chemicals.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- A widespread family of ribosomal peptide metallophores involved in bacterial adaptation to copper stress 96%
- Structural basis for divergent and convergent evolution of catalytic machineries in plant aromatic amino acid decarboxylase proteins 96%
- Mechanism of allosteric activation in human mitochondrial ClpP protease 96%
Similar papers in this journal
Similar papers in this journal
- Sm-like protein Rof inhibits transcription termination factor Rho by binding site obstruction and conformational insulation 96%
- Conformational Landscapes of a Class I Ribonucleotide Reductase Complex during Turnover Reveal Intrinsic Dynamics and Asymmetry 96%
- Structural mechanism of mRNA decoding by mammalian GTPase GTPBP1 96%
Similar papers in this journal
- Synthetic nanobody-SARS-CoV-2 receptor-binding domain structures identify distinct epitopes 95%
- Transmembrane helix 6b links proton- and metal-release pathways to drive conformational change in an Nramp transition metal transporter 95%
- Conserved and repetitive motifs in an intrinsically disordered protein drive α-carboxysome assembly 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.