ArticleJournal of the American Chemical Society2026
Catalytic Enantioselective Aziridination of Z-Disubstituted Alkenes with Aspartyl β-Turn-Based Dirhodium(II) Metallopeptides and Assessment of Catalyst Scaffold Versatility.
Article in Journal of the American Chemical Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
We report an enantioselective aziridination of open-chain Z-disubstituted alkenes, enabled by a dirhodium(II) metallopeptide featuring finely tuned, β-turn-biased peptidyl ligands. This method affords cis-aziridines in up to 99:1 er and exhibits broad tolerance toward diverse aryl substitution patterns and peripheral functional groups. In conjunction, we explore a data science model that uncovers patterns in molecular features that reflect enantioselectivity across two nitrene transfer reactions catalyzed by dirhodium(II) metallopeptides: the aziridination reported here and a related benzylic amination reaction. This model is trained on molecular descriptors of both catalysts and substrates and used to interpret the differences between the two reactions. By linking a new synthetic methodology to cross-reaction, data science-driven modeling, this study offers both an efficient route to valuable aziridine scaffolds and a framework for analyzing enantioinduction across mechanistically diverse transformations.
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.