Molecular Insight into Recognition of the CGRPR Complex by Migraine Prevention Therapy Aimovig (Erenumab)
Bibliographic record
Abstract
Calcitonin-gene-related peptide (CGRP) plays a key role in migraine pathophysiology. Aimovig (erenumab; erenumab-aooe in the United States) is the only US Food and Drug Administration (FDA)-approved monoclonal antibody (mAb) therapy against the CGRP receptor (CGRPR) for the prevention of migraine. Aimovig is also the first FDA-approved mAb against a G-protein-coupled receptor (GPCR). Here, we report the architecture and functional attributes of erenumab critical for its potent antagonism against CGRPR. The crystal structure of erenumab in complex with CGRPR reveals a direct ligand-blocking mechanism, enabled by a remarkable 21-residue-long complementary determining region (CDR)-H3 loop, which adopts a tyrosine-rich helix-turn tip and projects into the deep interface of the calcitonin receptor-like receptor (CLR) and RAMP1 subunits of CGRPR. Furthermore, erenumab engages with residues specific to CLR and RAMP1, providing the molecular basis for its exquisite selectivity. Such structural insights reveal the drug action mechanism of erenumab and shed light on developing antibody therapeutics targeting GPCRs.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".