MétaCan
Menu
Back to cohort
Record W4413358799 · doi:10.1111/dom.16652

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

2025· article· en· W4413358799 on OpenAlexafffund
Yusman Manchanda, Ben Jones, Gaëlle Carrat, Zenouska Ramchunder, Piero Marchetti, Isabelle Leclerc, Rajamannar Thennati, Vinod Burade, Muthukumaran Natarajan, Pradeep Shahi, Alejandra Tomás, Guy A. Rutter

Bibliographic record

VenueDiabetes Obesity and Metabolism · 2025
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsMcGill University Health CentreCentre Hospitalier de l’Université de Montréal
FundersDivision of Diabetes, Endocrinology, and Metabolic DiseasesInstitute of Nutrition, Metabolism and DiabetesNational Institute of Diabetes and Digestive and Kidney DiseasesMedical Research CouncilCanadian Institutes of Health ResearchNational Institutes of HealthEli Lilly and CompanySociety for EndocrinologyDiabetes UKWellcome TrustCanada Foundation for Innovation
KeywordsReceptorIncretinAgonistInternalizationInternal medicineEndocrinologyG protein-coupled receptorInsulinIn vivoDownregulation and upregulationGlucagon-like peptide-1MedicineGlucagon-like peptide 1 receptorType 2 diabetesPharmacologyDiabetes mellitusChemistryBiologyBiochemistry

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.234
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueDiabetes Obesity and MetabolismSame topicDiabetes Treatment and ManagementFrench-language works237,207