Enantioselective Synthesis of 1-Aryl-Substituted Tetrahydroisoquinolines Employing Imine Reductase
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Bibliographic record
Abstract
Tetrahydroisoquinolines (THIQs) with a C1-aryl-substituted groups are common in many natural and synthetic compounds of biological importance. Currently, their enantioselective synthesis are primarily reliant on chemical catalysis. Enzymatic synthesis using imine reductase is very attractive, because of the cost-effectiveness, high catalytic efficiency, and enantioselectivity. However, the steric hindrance of the 1-aryl substituents make this conversion very challenging, and current successful examples are mostly restricted to the simple alkyl-THIQs. In this report, through extensive evaluation of a large collection of IREDs (including 88 enzymes), we successfully identified a panel of steric-hindrance tolerated IREDs. These enzymes are able to convert meta - and para -substituted chloro-, methyl-, and methoxyl-benzyl dihydroisoquinolines (DHIQs) into corresponding R- or S- THIQs with very high enantioselectivity and conversion. Among them, the two most hindrance-tolerated enzymes (with different stereospecificity) are also able to convert ortho -substituted chloro-, methyl-, and methoxyl-benzyl DHIQs and dimethoxyl 1-chlorobenzyl-DHIQs with good enantiometric excess. Furthermore, using in silico modeling, a highly conserved tryptophan residue (W191) was identified to be critical for substrate accommodation in the binding cavity of the S -selective IRED (IR45). Replacing W191 with alanine can dramatically increase the catalytic performance by decreasing the K m value by 2 orders of magnitude. Our results provide an effective route to synthesize these important classes of THIQs. Moreover, the disclosed sequences and substrate binding model set a solid basis to generate more-efficient and broad-selective enzymes via protein engineering.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it