ArticleNature communications2026
Cyclic sulfone ring remodeling enables molecular shape diversity-oriented synthesis of privileged biaryl and oligoaryl motifs.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Cyclic sulfone ring remodeling enables molecular shape diversity-oriented synthesis of privileged biaryl and oligoaryl motifs.Nature communications · 2026Article
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Authors and funding
16 authors.
Funding
Abstract
Molecular shape is a key determinant of the structural properties and intermolecular interactions of privileged scaffolds, such as biaryl and oligoaryl compounds, which are widely used in the design of drugs, catalysts, and functional materials. Despite the well-recognized importance of molecular shape diversity and increased three-dimensionality, the chemical space of biaryl compounds remains dominated by linear and disk-like structures featuring para and meta substitution patterns. In contrast, more sphere-like bis-ortho-substituted biaryl scaffolds have been underexplored, because of the dearth of synthetic methods for generating focused libraries of ortho analogs in a synthetically efficient manner. We report herein the development of regioselective nucleophile/electrophile couple-mediated cyclic sulfone ring remodeling that can streamline access to a wide range of biaryl and oligoaryl scaffolds, featuring aliphatic and (hetero)aromatic amines, phenols, (thio)ethers, and phosphines. To facilitate prediction of the regiochemistry of structurally complex biaryl products, a machine learning model based on the previously unexplored Bernoulli Naïve Bayes classifier is developed. The integrated experimental, computational, and data-driven approach charts the course for mitigating structural biases and exploring the underpopulated biaryl chemical space in medicinal chemistry, catalysis, and materials science.
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Registered trials
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