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Record W4319939125 · doi:10.21203/rs.3.rs-2494605/v1

Intramolecular Hydroamidation of Alkenes Enabling Asymmetric Synthesis of β-Lactams via Unprecedented Mechanism of NiH Catalysis

2023· preprint· en· W4319939125 on OpenAlexaff
Xiang Lyu, Changhyeon Seo, Teresa Faber, Dongwook Kim, Sangwon Seo, Sukbok Chang

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldChemistry
TopicSynthesis and Catalytic Reactions
Canadian institutionsKootenay Association for Science & Technology
FundersInstitute for Basic Science
KeywordsIntramolecular forceMechanism (biology)CatalysisChemistryCombinatorial chemistryEnantioselective synthesisStereochemistryOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract Synthetic methods for constructing enantioenriched β-lactams are highly valuable given the ubiquity of this privileged heterocyclic unit in bioactive compounds, most notably in antibiotics such as penicillins and carbapenems. Intramolecular hydroamidation of β,γ-unsaturated amides would provide a convenient means to reach this alluring chemical space, yet it remains limited due to the regioselectivity issue arising from the difficulty associated with the formation of strained four-membered rings. Here we describe a NiH-catalysed strategy that addresses this challenge through the use of readily accessible alkenyl dioxazolone derivatives. The reaction transcends the conventional NiH operation mode via an unprecedented mechanism initiated by N-activation, thus allowing for proximal C–N bond formation with excellent regioselectivity, regardless of the electronic properties of substituents. This mechanistic platform is also highly effective for the enantioselective intramolecular hydroamidation of alkenes, which represents the first example of such a type of processes that enables the access to enantioenriched β-lactams.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.350
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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