Back

LanD-like Flavoprotein-Catalyzed Aminovinyl-Cysteine Formation through Oxidative Decarboxylation and Cyclization of a Peptide at the C-Terminus

Liu, J.; Qiu, Y.; Fu, T.; Li, M.; Li, Y.; Yang, Q.; Tang, Z.; Tang, H.; Li, G.; Pan, L.; Liu, W.

2020-02-14 biochemistry
10.1101/2020.02.13.947028 bioRxiv
Show abstract

Aminovinyl-cysteine residues arise from processing the C-terminal O_SCPLOWLC_SCPLOW-Cys and an internal O_SCPLOWLC_SCPLOW-Ser/O_SCPLOWLC_SCPLOW-Thr or O_SCPLOWLC_SCPLOW-Cys of a peptide. Formation of these nonproteinogenic amino acids, which occur in a macrocyclic ring of diverse ribosomally synthesized lanthipeptides and non-lanthipeptides, remains poorly understood. Here, we report that LanD-like flavoproteins in the biosynthesis of distinct non-lanthipeptides share an unexpected dual activity for aminovinyl-cysteine formation. Each flavoprotein catalyzes oxidative decarboxylation of the C-terminal O_SCPLOWLC_SCPLOW-Cys and couples the resulting enethiol nucleophile with the internal residue to afford a thioether linkage for peptide cyclization. The cyclization step, which largely depends on proximity effect by positioning the enethiol intermediate with a bent conformation at the active site, can be substrate-dependent, proceeding inefficiently through nucleophilic substitution for an unmodified peptide or efficiently through Michael addition for a dehydrated/dethiolated peptide. Uncovering this unusual flavin-dependent paradigm for thioether residue formation advances the understanding in the biosynthesis of aminovinyl-cysteine-containing RiPPs and renews interest in flavoproteins, particularly those involved in non-redox transformations. LanD-like flavoproteins activity, which is flexible in peptide substrate and amenable for evolution by engineering, can be combined with different post-translational modifications for structural diversity, thereby holding promise for peptide macrocyclization/functionalization in drug development by chemoenzymatic or synthetic biology approaches.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"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.