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Record W4413659568 · doi:10.26434/chemrxiv-2025-hk0d9

The Atroposelective Iodination of 2-Amino-6-arylpyridines Catalyzed by Chiral Disulfonimides Actually Proceeds via Brønsted Base Catalysis: A Combined Experimental and Computational Study

2025· preprint· en· W4413659568 on OpenAlexfundno aff
Karnjit Parmar, Seth A. Bawel, Mihai V. Popescu, Jacob C. Timmerman, Bilal Altundas, Robert S. Paton, Scott E. Denmark

Bibliographic record

VenueChemRxiv · 2025
Typepreprint
Languageen
FieldChemistry
TopicAxial and Atropisomeric Chirality Synthesis
Canadian institutionsnot available
FundersDivision of ChemistryNatural Sciences and Engineering Research Council of CanadaUniversity of Illinois at Urbana-ChampaignW. M. Keck FoundationNational Science Foundation
KeywordsCatalysisHalogenationBase (topology)ChemistryBrønsted–Lowry acid–base theoryCombinatorial chemistryMedicinal chemistryOrganic chemistryMathematics

Abstract

fetched live from OpenAlex

A thorough mechanistic investigation into the disulfonimide (DSI)-catalyzed atroposelective iodination of 2-amino-6-arylpyridines with N-iodosuccinimide is described. While initially hypothesized to proceed via Brønsted-acid catalysis through activation of NIS, experimental evidence led us to reconsider the possible function of the DSI catalyst. We now propose a mechanism in which the conjugate base of the DSI functions instead as a Brønsted-base, with the rate and stereodetermining step involving an enantioselective deprotonation of a Wheland intermediate. The experimental data was used to initiate a DFT exploration of the reaction mechanism, which after thorough analysis of the transition state structures and reaction coordinate confirmed our revised hypothesis. The unique structural features of the highest performing catalyst were explored further with a chemoinformatics derived workflow, leading to a highly detailed elucidation of those factors contributing to the origin of enantioselection.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.100
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.251
Teacher spread0.241 · 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 teacher head, not a consensus.

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
Published2025
Admission routes1
Has abstractyes

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