Late-Stage C(sp2)–C(sp3) Diversification via Nickel Oxidative Addition Complexes
Bibliographic record
Abstract
Nickel catalysis has emerged as a powerful technique for streamlining the access to exceedingly complex organic molecules from simple precursors. However, nickel-catalyzed cross-couplings with advanced synthetic intermediates still remain a considerable challenge. Herein, we describe a technique based on the utilization of nickel oxidative addition complexes (Ni-OAC) of drug-like molecules as a platform to rapidly and reliably generate lead candidates with enhanced C(sp3) fraction. The potential of Ni-OACs to access new chemical space has been assessed in three different C(sp2)–C(sp3) bond-forming events without recourse to specialized ligand backbones. Reactions with Ni-OACs proceed under exceptionally mild conditions and with improved generality when compared to nickel-catalyzed reactions. The development of an automated process for forging C(sp2)–C(sp3) architectures further illustrates the robustness and generality of Ni-OACs, thus offering a new gateway to expedite the design-make-test-analyze (DMTA) cycle in drug discovery
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".