Bioproduction of a Large-Scale Library of Tryptamine Derivatives for Neuropsychiatric Drug Screening
Bibliographic record
Abstract
Drug screening programs targeting novel indolethylamines with pharmacological properties suitable for the treatment of psychiatric and central nervous system disorders benefit from the availability of large compound libraries normally prepared using synthetic chemistry. Bioproduction strategies based on microbial metabolic engineering and fermentation generally fail to achieve the throughput, scale, or versatility of synthetic chemistry owing, in part, to a lack of efficient and promiscuous enzymes. Moreover, synthetic biology rarely extends to the purification of targeted products, which is an essential component of synthetic chemistry and drug screening regimes. A lattice of biosynthetic routes beginning with endogenous tryptophan or exogenous indole derivatives were engineered in Escherichia coli using heterologous genes encoding enzymes sourced from plants, mushrooms, microbes and animals. Twelve tryptophan decarboxylase candidates were screened and highly versatile top-performers from Bacillus atrophaeus and the gut microbiome species Clostridium sporogenes were identified. Seven halogenases, three tryptophan synthase β-subunits, six N -methyltransferases, five regioselective prenyltransferases, a cytochrome P450 oxidoreductase 5-hydroxylase, an N -acetyltransferase, a 4- O -kinase and various accessory proteins were also tested. These enzymes were used in various combinations and permutations to build E. coli strains capable of 344 putative biotransformations, which resulted in the formation of 279 products with only 63 targeted compounds not detected. A set of 17 novel N -acetylated derivatives were selected for upscaled culturing and purification to ≥95% from 0.5 to 1 L of the fermentation broth, which yielded ∼6–80 mg of each molecule. The potential of each compound for bioactivity at 14 different receptors or transporters with established or purported involvement in neuropsychiatric diseases was tested using a single ligand concentration. Nearly all the N -acetylated compounds showed interaction with the melatonin (MT 1 ) receptor, and several molecules showed interaction with serotonergic receptors 5-HT 2B, 5-HT 2C, and 5-HT 7 . Overall, we show that bio-fermentation is useful in the large-scale screening of molecules with potential in drug development.
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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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".