Known targets — ChEMBL curated mechanism
The experimentally established mechanism targets of Metoprolol. The predicted profile below is derived independently by chemical similarity — agreement is a validation signal, a miss is honest.
Predicted protein targets (top 20)
| gene | UniProt | supporting neighbours | confidence | |
|---|---|---|---|---|
| ▸ | ADRB1 known ✓ | P08588 | 4/20 | 0.84 |
| ▸ | TDP1 | Q9NUW8 | 3/20 | 1.00 |
| ▸ | PMP22 | Q01453 | 2/20 | 1.00 |
| ▸ | NPY1R | P25929 | 1/20 | 1.00 |
| ▸ | NPY2R | P49146 | 1/20 | 1.00 |
| ▸ | NPSR1 | Q6W5P4 | 1/20 | 1.00 |
| ▸ | ADRB2 | P07550 | 3/20 | 0.84 |
| ▸ | ADRA1A | P35348 | 2/20 | 0.84 |
| ▸ | CYP2D6 | P10635 | 2/20 | 0.84 |
| ▸ | NR3C1 | P04150 | 1/20 | 0.84 |
| ▸ | CYP2J2 | P51589 | 1/20 | 0.84 |
| ▸ | PDE4D | Q08499 | 1/20 | 0.84 |
| ▸ | ABCB1 | P08183 | 1/20 | 0.60 |
| ▸ | LMNA | P02545 | 2/20 | 0.60 |
| ▸ | CNR1 | P21554 | 1/20 | 0.60 |
| ▸ | ADRA1D | P25100 | 1/20 | 0.60 |
| ▸ | ADRA1B | P35368 | 1/20 | 0.60 |
| ▸ | KDM4E | B2RXH2 | 1/20 | 0.60 |
| ▸ | CYP1A2 | P05177 | 1/20 | 0.60 |
| ▸ | GLA | P06280 | 1/20 | 0.60 |
Click a target to see other patent compounds predicted against it — the reverse direction, in place.
Similar compounds — the chemically nearest patent molecules
Nearest neighbours by Morgan-fingerprint cosine across the patent-compound collection, with each neighbour's top predicted target and the predicted targets it shares with this molecule.
| Compound | similarity | top predicted | shared targets | |
|---|---|---|---|---|
| Metoprolol SCHEMBL19211129 | 1.00 | TDP1 (1.00) | TDP1PMP22NPY1RNPY2RNPSR1 | |
| Metoprolol SCHEMBL29995613 | 1.00 | TDP1 (1.00) | TDP1PMP22NPY1RNPY2RNPSR1 | |
| Metoprolol SCHEMBL1649321 | 1.00 | TDP1 (1.00) | TDP1PMP22NPY1RNPY2RNPSR1 | |
| Metoprolol SCHEMBL4881939 | 1.00 | TDP1 (1.00) | TDP1PMP22NPY1RNPY2RNPSR1 | |
| Metoprolol SCHEMBL41104 | 1.00 | TDP1 (1.00) | TDP1PMP22NPY1RNPY2RNPSR1 | |
| (S)-Metoprolol SCHEMBL141366 | 1.00 | TDP1 (1.00) | TDP1PMP22NPY1RNPY2RNPSR1 | |
| Metoprolol SCHEMBL2124595 | 0.99 | TDP1 (0.98) | TDP1PMP22NPY1RNPY2RNPSR1 | |
| Metoprolol SCHEMBL4879331 | 0.98 | TDP1 (0.96) | TDP1PMP22NPY1RNPY2RNPSR1 | |
| Metoprolol SCHEMBL28264735 | 0.97 | TDP1 (0.94) | TDP1PMP22NPY1RNPY2RNPSR1 | |
| (S)-Metoprolol SCHEMBL3123844 | 0.93 | ADRB2 (0.88) | TDP1PMP22NPY1RNPY2RNPSR1 |
Similarity is cosine over the 2,048-bit Morgan fingerprint (≈ Tanimoto). Identical fingerprints score 1.00.
Patent provenance — the patents this molecule appears in, and who filed them
Claimed or disclosed in 120 patents — showing the first 20. claimed = in the patent's claims; disclosed = body only.
| Patent | Title | Assignee | Published | Priority | Filing | Country | Status |
|---|---|---|---|---|---|---|---|
| CN-119440767-A | Multi-star multi-task parallel scheduling processing method, device, equipment, medium and product | 国家卫星气象中心(国家空间天气监测预警中心) | 2025-02-14 | — | — | CN | claimed |
| CN-118203558-A | Transdermal patch for treating hypertension | 天津汉瑞药业有限公司 | 2024-06-18 | — | — | CN | claimed |
| CN-117243179-A | Method for preparing mouse CNV model and bearing device | 上海朗昇生物科技有限公司 | 2023-12-19 | — | — | CN | claimed |
| CN-111650102-B | Haze pollution analysis method, device, medium and equipment based on satellite data | 北京中科锐景科技有限公司 | 2023-08-29 | — | — | CN | claimed |
| CN-116644379-A | Machine learning fusion method, equipment and medium for multisource sea surface physical elements | 中国海洋大学 | 2023-08-25 | — | — | CN | claimed |
| CN-116626782-A | Double-index monitoring method for south sea summer monsoon based on wind cloud polar orbit meteorological satellite | 国家卫星气象中心(国家空间天气监测预警中心) | 2023-08-22 | — | — | CN | claimed |
| WO-2023286966-A1 | VARIABLE STACK-TYPE HEAT DISSIPATING PLATE PACKAGE | 주식회사 알에프세미 | 2023-01-19 | — | — | WO | claimed |
| CN-114417560-A | Bus residual voltage detection method, motor voltage loss protection method, storage device and terminal | 国网山西省电力公司晋城供电公司 | 2022-04-29 | — | — | CN | claimed |
| CN-121705609-B | Satellite emissivity data deviation correction method and system based on constraint optimization | 中国气象局地球系统数值预报中心 | 2026-05-19 | — | — | CN | disclosed |
| CN-122046984-A | CFLGBM-based offshore surface wind field correction method | 北京信息科技大学 | 2026-05-15 | — | — | CN | disclosed |
| CN-122018047-A | All-weather satellite microwave humidity data assimilation method based on ARMS | 中国人民解放军国防科技大学 | 2026-05-12 | — | — | CN | disclosed |
| EP-4165441-B1 | RECEIVER OF RADIONAVIGATION SIGNALS COMPRISING A COMPUTER OF A CORRELATION POWER INDICATOR | CENTRE NAT ETD SPATIALES (FR) | 2026-04-15 | — | — | EP | disclosed |
| CN-116626782-B | Double-index monitoring method for south sea summer monsoon based on wind cloud polar orbit meteorological satellite | 国家卫星气象中心(国家空间天气监测预警中心) | 2026-02-10 | — | — | CN | disclosed |
| US-20260007711-A1 | NUTRACEUTICAL FORMULATIONS TO PREVENT, TREAT, AND INHIBIT EXCESS CYTOKINES, SARS-CoV-2 SPIKE PROTEINS, AND mRNA VACCINE SPIKE PROTEIN | PONO LIFESTYLE, LLC (US) | 2026-01-08 | — | — | US | disclosed |
| US-11281822-B2 | Atmospheric sensor network and analytical information system related thereto | Scepter Incorporated (US) | 2022-03-22 | — | — | US | disclosed |
| US-20220080376-A1 | METHODS FOR CONVERTING COLLOIDAL SYSTEMS TO RESUSPENDABLE/REDISPERSABLE POWDERS THAT PRESERVE THE ORIGINAL PROPERTIES OF THE COLLOIDS | THE REGENTS OF THE UNIVERSITY OF CALIFORNIA (US) | 2022-03-17 | — | — | US | disclosed |
| CN-114119787-A | Hyper-spectral image prediction compression method based on orthogonal matching pursuit | 哈尔滨工业大学 | 2022-03-01 | — | — | CN | disclosed |
| CN-114117899-A | Space-time filling method, system and computer equipment for satellite data | 中山大学 | 2022-03-01 | — | — | CN | disclosed |
| CN-114120020-A | Hyperspectral image inter-spectrum sequencing method based on key channel protection and spectral clustering | 哈尔滨工业大学 | 2022-03-01 | — | — | CN | disclosed |
| CN-114004303-A | Multi-source data fusion method based on space-time dynamic triple matching analysis | 浙江大学 | 2022-02-01 | — | — | CN | disclosed |
Patent text — is the patent's own abstract consistent with the prediction?
For each of this compound's patents that has machine-readable text (1 of them — usually the abstract, not the full specification), we ask MedCPT which protein the text reads most about, and where the chemistry-predicted target lands among 4885 human targets. A high rank means the patent's own wording is consistent with the prediction — a weak, independent signal, not proof of activity.
| Patent | Title | Text reads most about | Predicted target · text-rank |
|---|---|---|---|
| US-20260007711-A1 | NUTRACEUTICAL FORMULATIONS TO PREVENT, TREAT, AND INHIBIT EXCESS CYTOKINES, SARS-CoV-2 SPIKE PROTEINS, AND mRNA VACCINE SPIKE PROTEIN | VDR, RNMT, CD14 | ADRB1 1185/4885TDP1 4847/4885PMP22 754/4885 |
“Text reads most about” is the patent abstract's nearest protein in MedCPT space (background-debiased). Only ~1.4% of patents have machine-readable text, so most compounds won't have this panel.