The Quest for a Practical Synthesis of Morphine Alkaloids and Their Derivatives by Chemoenzymatic Methods
Bibliographic record
Abstract
We became interested in approaches to morphine in the early 1990s following our immersion into the new program on the enzymatic dihydroxylation of aromatics. Larry Kwart, a former classmate of one of us at Rice University, who worked with our group at Virginia Tech in the mid-1980s, introduced to us the use of blocked mutants of Pseudomonas putida (Pp39D) for the production of arene-cis-dihydrodiols. Larry had gained expertise in microbiology from a postdoctoral stay with David Gibson, who discovered this unique enzymatic transformation, and he helped us to establish a strong program in chemoenzymatic synthesis that continues to this day. Without his pioneering effort, none of our accomplishments in chemoenzymatic synthesis, including the various approaches to morphine, would have materialized. Here we trace the evolution of our approaches to morphine alkaloids and some commercial opiate-derived medicinal agents. The design features and chronology of our approaches are discussed in a way that allows the reader to appreciate a number of errors that were made in conception as well as in execution. Experience acquired from many failed or less-than-effective attempts has finally led to an "almost reasonable" total synthesis, the key concept being based on our very first but unsuccessful attempt more than two decades ago. The irony of this accomplishment has not been lost on us. Each section of this Account presents a summary of distinctly different approaches to morphine alkaloids. Each ends with a short and philosophical lesson that was (or should have been) learned in the process. We intend for this Account to offer more than the history of a search for the perfect design solution to a synthetic problem. In today's era of rapid and often careless publication of results, it should serve also as a reminder that the success and the integrity of synthetic ventures depends on perseverance, adjustment of strategy, improvements of previous attempts, and serious attention to the quality of experimental data. Although somewhat satisfied with our latest accomplishment in morphinan synthesis, we plan to improve our design in the hope that a six-step synthesis is no longer in the realm of fantasy. With more than 20 years of effort in this area, our continuing involvement may qualify as obsession.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".