Skip to content

Family of β-Propeller Diels–Alderases Directs cis -Decalin Formation in Polyketide Biosynthesis

Unknown authors
Sep 2026 · Journal of the American Chemical Society · 0 citations · 62 references

TL;DR

The fold and mechanistic diversity of Diels–Alderases are expanded, an exo-selective β-propeller pericyclase superfamily is defined, and a new handle for mining and bioengineering cis-decalin biosynthetic pathways is provided.

Abstract

Decalin-forming Diels–Alderases (pericyclases) exemplify how Nature repeatedly recruits unrelated protein folds to control [4 + 2] cycloadditions, yet exo-selective intramolecular Diels–Alder (IMDA) reactions that yield cis-fused decalins remain rare and poorly understood. Here, we uncover a previously unrecognized bacterial pericyclase family that enforces an exo-IMDA trajectory in polyketide assembly. Using alchivemycin A, a macrocyclic antibacterial polyketide whose scaffold is defined by a highly functionalized cis-decalin core, we identify AvmG as the dedicated decalin-forming enzyme. Disruption of avmG diverts pathway flux to trans-decalin shunt isomers consistent with spontaneous, endo-biased cyclization that cannot be processed by the downstream macrocyclase, whereas AvmG enables formation of the authentic cis-decalin intermediate. AvmG is unrelated to known [4 + 2] cyclases and adopts an integrin α N-terminal domain-like β-propeller architecture, revealing an unexpected scaffold for pericyclic stereocontrol. Genome mining shows that AvmG-like proteins are widespread and enriched in actinomycete polyketide gene clusters; characterization of the lydicamycin homolog LymR establishes conserved exo-IMDA activity in a distinct pathway. Structural and mutational analyses implicate a loop-defined catalytic cavity in steering the kinetically demanding cis-decalin outcome. Together, these findings expand the fold and mechanistic diversity of Diels–Alderases, define an exo-selective β-propeller pericyclase superfamily, and provide a new handle for mining and bioengineering cis-decalin biosynthetic pathways.

View source

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

Google DeepMind Blog Sep 30, 2026

Introducing SynthID Bio

Proof of concept for watermarking AI-generated proteins while preserving biological function.

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.