Binding kinetics, bias, receptor internalization and effects on insulin secretion in vitro and in vivo of a novel <scp>GLP</scp> ‐ <scp>1R</scp> / <scp>GIPR</scp> dual agonist, <scp>HISHS</scp> ‐2001
Bibliographic record
Abstract
Abstract Aims The use of incretin analogues has emerged as an effective approach to achieve both enhanced insulin secretion and weight loss in Type 2 diabetes (T2D) patients. Agonists which bind and stimulate multiple receptors have shown particular promise. However, off‐target effects remain a complication of using these agents, and modified versions with optimised pharmacological profiles and/or biased signalling are sought. Materials and Methods Ligand synthesis was achieved using standard solid‐phase techniques. Assessments of GLP‐1R‐binding kinetics, G protein recruitment and receptor internalisation were performed using biochemical and imaging approaches. Insulin secretion was measured in purified mouse and human islets, and drug efficacy was assessed in hyperglycaemic db/db mice. Results We describe the synthesis and properties of a molecule which binds to both glucagon‐like peptide‐1 (GLP‐1) and glucose‐dependent insulinotropic polypeptide (GIP) receptors (GLP‐1R and GIPR) to enhance insulin secretion. HISHS‐2001 shows increased affinity at the GLP‐1R, as well as a tendency towards reduced internalisation and recycling at this receptor versus FDA‐approved dual GLP‐1R/GIPR agonist tirzepatide. HISHS‐2001 also displayed significantly greater bias towards cAMP generation versus β‐arrestin 2 recruitment compared to tirzepatide. In contrast, G α s recruitment was lower versus tirzepatide at the GLP‐1R, but unchanged at the GIPR. Administered to obese hyperglycaemic db/db mice, HISHS‐2001 increased circulating insulin whilst lowering body weight and HbA1c with similar efficacy to tirzepatide at substantially lower doses. Conclusion HISHS‐2001 represents a novel dual receptor agonist with a promising pharmacological profile and actions. Future clinical studies will be needed to assess the safety and efficacy of this molecule in humans.
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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".