A Series of 2‐((1‐Phenyl‐1H‐imidazol‐5‐yl)methyl)‐1H‐indoles as Indoleamine 2,3‐Dioxygenase 1 (IDO1) Inhibitors
Bibliographic record
Abstract
Abstract Indoleamine 2,3‐dioxygenase 1 (IDO1) is a promising therapeutic target in cancer immunotherapy and neurological disease. Thus, searching for highly active inhibitors for use in human cancers is now a focus of widespread research and development efforts. In this study, we report the structure‐based design of 2‐(5‐imidazolyl)indole derivatives, a series of novel IDO1 inhibitors which have been designed and synthesized based on our previous study using N1‐substituted 5‐indoleimidazoles. Among these, we have identified one with a strong IDO1 inhibitory activity (IC50=0.16 μM, EC50=0.3 μM). Structural‐activity relationship (SAR) and computational docking simulations suggest that a hydroxyl group favorably interacts with a proximal Ser167 residue in Pocket A, improving IDO1 inhibitory potency. The brain penetrance of potent compounds was estimated by calculation of the Blood Brain Barrier (BBB) Score and Brain Exposure Efficiency (BEE) Score. Many compounds had favorable scores and the two most promising compounds were advanced to a pharmacokinetic study which demonstrated that both compounds were brain penetrant. We have thus discovered a flexible scaffold for brain penetrant IDO1 inhibitors, exemplified by several potent, brain penetrant, agents. With this promising scaffold, we provide herein a basis for further development of brain penetrant IDO1 inhibitors.
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 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 | 0.000 | 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) | 0.001 | 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 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".