Pharmacological Characterization of 5-Substituted 1-[(2,3-dihydro-1-benzofuran-2-yl)methyl]piperazines: Novel Antagonists for the Histamine H3 and H4 Receptors with Anti-inflammatory Potential
Bibliographic record
Abstract
The histamine receptors (HRs) are traditional G protein-coupled receptors of extensive therapeutic interest. Recently, H3R and H4R subtypes have been targeted in drug discovery projects for inflammation, asthma, pain, cancer, Parkinson’s, and Alzheimer’s diseases, which includes searches for dual acting H3R/H4R ligands. In the present work, nine 1-[(2,3-dihydro-1-benzofuran-2-yl)methyl]piperazine (LINS01 series) molecules were synthesized and evaluated as H3R and H4R ligands. Our data show that the N-allyl-substituted compound LINS01004 bears the highest affinity for H3R (pKi 6.40), while the chlorinated compound LINS01007 has moderate affinity for H4R (pKi 6.06). In addition, BRET assays to assess the functional activity of Gi1 coupling indicate that all compounds have no intrinsic activity and act as antagonists of these receptors. Drug-likeness assessment indicated these molecules are promising leads for further improvements. In vivo evaluation of compounds LINS01005 and LINS01007 in a mouse model of asthma showed a better anti-inflammatory activity of LINS01007 (3 g/kg) than the previously tested compound LINS01005. This is the first report with functional data of these compounds in HRs, and our results also show the potential of their applications as anti-inflammatory.
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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 | 0.000 | 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".