Pain-blocking opioid research peptide (CHEMBL1927270)
A lab-made compound that switches on the brain's opioid receptors, copying the pain-relieving effect of the body's own opioid molecules; used only as a research tool.
A researcher, an agent, or an algorithm wrote down the sequence and picked a target to hit.
An AI model like OpenFold3 or AlphaFold built a 3D structure and scored how well it fits the binding site.
A second contributor repeated the computation on their own hardware and the scores matched.
A chemistry service or a researcher ordered the sequence, it was manufactured, and mass spectrometry confirmed the right molecule was produced.
A binding or activity measurement confirmed that it actually does what the computer predicted — or didn't.
What this is
This card describes a research-only synthetic peptide (ChEMBL identifier CHEMBL1927270) developed by Anna Janecka's medicinal-chemistry group at the Medical University of Łódź as part of a programme building short, cyclic analogs of the brain's own opioid peptides. The stored "FFD" sequence shows only the Phe-Phe-Asp portion of the molecule; the actual compound is a cyclic pseudo-tetrapeptide built on the endomorphin-2 / morphiceptin scaffold (Tyr-Pro-Phe-Phe-NH₂), in which a Tyr–D-Lys "address" segment is fused through two side-chain amide bridges to a Phe-Phe-Asp-amide "message" segment (ChEMBL HELM record; Fichna and colleagues 2011). It is a laboratory tool compound for studying opioid receptors — not a drug, not in clinical development, and not approved for any use.
History
The endogenous tetrapeptides endomorphin-1 (Tyr-Pro-Trp-Phe-NH₂) and endomorphin-2 (Tyr-Pro-Phe-Phe-NH₂) were proposed as the brain's own high-affinity, highly selective agonists of the μ-opioid receptor. Their potential as analgesics with potentially cleaner side-effect profiles than morphine drove a decade of structure-activity work aimed at protecting them from rapid enzymatic breakdown and improving their ability to reach the brain after systemic dosing. Cyclisation of the linear backbone is one of the main strategies the Janecka group and collaborators used to address this stability problem (Fichna and colleagues 2011; Piekielna and colleagues 2014; Perlikowska and colleagues 2016; Adamska-Bartłomiejczyk and colleagues 2017). This compound is one product of that programme.
What it does
In binding assays it acts predominantly at the μ-opioid receptor (MOR, gene OPRM1) — the same receptor activated by morphine and by the endogenous endomorphins — with much weaker affinity at the δ-opioid receptor (DOR, gene OPRD1) and detectable affinity at the κ-opioid receptor (KOR). After intracerebroventricular injection in mice it produced antinociception in the paw-licking test, and a follow-up study reported antinociceptive activity after systemic (intraperitoneal) administration, indicating that the cyclic scaffold survives long enough in plasma to reach the brain (Fichna and colleagues 2011; Perlikowska and colleagues 2016).
Evidence
- Human: No human trials. The compound has not entered clinical development.
- Animal: Active in mouse antinociception models after central administration in the paw-licking assay (Fichna and colleagues, Bioorganic & Medicinal Chemistry 2011) and active after systemic intraperitoneal dosing in mouse pain models in a follow-up cyclic-analog series (Perlikowska and colleagues, European Journal of Medicinal Chemistry 2016).
- In vitro: In rat-brain radioligand binding, the compound displaced [³H]DAMGO from MOR with IC50 ≈ 0.56 nM and [³H][Ile⁵,⁶]deltorphin-2 from DOR with IC50 ≈ 279 nM, giving roughly 498-fold MOR-over-DOR selectivity; brain-homogenate half-life was ≈ 6 h at the test concentration, much longer than the parent endomorphin-2 (Fichna and colleagues 2011). A separate evaluation reported MOR Ki ≈ 0.35 nM, DOR Ki ≈ 171 nM and KOR Ki ≈ 1.1 nM (Perlikowska and colleagues 2016). All affinity values are from rat or guinea-pig tissue binding assays as deposited in ChEMBL.
A note on the card metadata: the stored sequence "FFD" is the linear three-residue fragment that the platform's sequence field can represent in single-letter code. The biologically active molecule additionally contains an N-terminal Tyr (the canonical opioid-pharmacophore "message" residue), a D-Lys, two side-chain-to-side-chain amide bridges that lock the structure into a cycle-in-cycle scaffold, and a C-terminal carboxamide on the Asp. The card's primary-target list includes both OPRD1 and OPRM1, but the verified pharmacology in the source paper is MOR-selective.
Known effects
- MOR binding (high affinity) — Sub-nanomolar in rat brain (Fichna 2011; Perlikowska 2016)
- DOR binding (weak) — Nanomolar-to-submicromolar; ≈ 500-fold weaker than MOR (Fichna 2011)
- KOR binding — Low-nanomolar in guinea-pig brain (Perlikowska 2016)
- Antinociception, central administration — Mouse paw-licking, intracerebroventricular dose (Fichna 2011)
- Antinociception, systemic administration — Mouse, intraperitoneal dose (Perlikowska 2016)
Regulatory status
- US / EU: Not approved. Research compound only; no IND, no marketing authorisation in any jurisdiction.
- Clinical development: None. No registered clinical trials.
- WADA: Not individually listed. Synthetic μ-opioid receptor agonists fall under the general framework for narcotics during competition (S7) when used in vivo; this is a research peptide, not a clinical product, and the compound itself is not on the WADA prohibited list.
Related peptides
This compound sits inside a wider catalog of designed short opioid peptides on the platform. Most platform cards for individual ChEMBL research ligands in this series do not carry hand-written context; the structurally and pharmacologically closest reference points are the natural μ-opioid tetrapeptides endomorphin-1 and endomorphin-2 and the casein-derived μ-opioid tetrapeptide morphiceptin (Tyr-Pro-Phe-Pro-NH₂), all of which served as the parent scaffolds for this design programme.
Research directions for this peptide, selected from the current sources — hypotheses you can explore and model. None of it is proven yet; tap any one to see the full thinking.
Could this compound be hitting two different pain-blocking targets in the brain at the same time?
If true, it would mean the compound's pain-relieving effect works differently from morphine, which only acts on one receptor. That difference could matter for how quickly tolerance builds and whether the drug causes the mood-darkening side effects tied to the second receptor type.
Can we identify exactly which section of this molecular ring makes the drug stick to the intended pain receptor and not to others?
If this structural segment turns out to be the selectivity switch, chemists could dial the drug's receptor preference up or down on purpose. That kind of precision could eventually lead to painkillers with fewer off-target side effects.
Does the molecule flip between two shapes, and does only one of those shapes actually bind tightly to the pain receptor?
If one shape is responsible for almost all the activity, drug makers could engineer a version that is locked into that shape, making dosing more predictable and potentially more effective. Right now, mixtures of both shapes make it harder to understand what the drug is really doing.
If we shorten one building block in the molecular ring by a few atoms, could we get a cleaner, single-shape molecule that still blocks pain just as powerfully?
A molecule that exists as one stable shape rather than two interconverting forms is simpler to study, easier to develop into a drug, and more straightforward to assess for safety. This could speed up the path from research compound to clinical tool.
Could this compound, because it survives long enough in the body to reach the brain, hold withdrawal symptoms at bay after just one dose?
If this holds up in animal studies, it would point toward a new class of non-alkaloid compounds for managing opioid withdrawal. People going through withdrawal currently have very few options, and a molecule like this, derived from natural peptides rather than synthetic opioids, might open a different chemical path to treatment.
▸full evidence table1 metrics
| metric | value | tool |
|---|---|---|
| EC50 | 6.607 nM | GPCRDB/ChEMBL |
▸structural qualityopenfold3
| metric | value | note |
|---|---|---|
| gpde | 0.746 | global PDE — lower = better |
| disorder | NaN | fraction disordered |
▸3-letter notation
▸recipeboltz-2 1.0
| parameter | value |
|---|---|
| model | boltz-2 1.0 |
| weights | — |
| hardware | nvidia_nim_api |
| mlx version | — |
| python | — |
| random seed | — |
| msa strategy | none |
| diffusion samples | 1 |
| runtime | — |
| predicted by | mlx@peptide |
| predicted at | 2026-04-24 |
▸citationbibtex
@peptide{pep10425,
sequence = {FFD},
target = {oprd1},
author = {peptidemodel},
year = {2026},
status = {bioassayed}
}