Predicted protein targets (top 9)
| gene | UniProt | supporting neighbours | confidence | |
|---|---|---|---|---|
| ▸ | NPY2R | P49146 | 8/20 | 0.73 |
| ▸ | NPY4R | P50391 | 8/20 | 0.73 |
| ▸ | NPY5R | Q15761 | 8/20 | 0.73 |
| ▸ | NPY1R | P25929 | 6/20 | 0.73 |
| ▸ | KISS1R | Q969F8 | 3/20 | 0.64 |
| ▸ | CXCR4 | P61073 | 3/20 | 0.62 |
| ▸ | CXCL8 | P10145 | 1/20 | 0.61 |
| ▸ | GLP1R | P43220 | 3/20 | 0.61 |
| ▸ | GCGR | P47871 | 3/20 | 0.61 |
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 | |
|---|---|---|---|---|
| SCHEMBL29578881 | 1.00 | NPY2R (0.73) | NPY2RNPY4RNPY5RNPY1RKISS1R | |
| SCHEMBL29819538 | 0.92 | NPY1R (0.66) | NPY2RNPY4RNPY5RNPY1RCXCR4 | |
| SCHEMBL30423525 | 0.92 | NPY2R (0.72) | NPY2RNPY4RNPY5RNPY1RCXCR4 | |
| SCHEMBL30786585 | 0.92 | KISS1R (0.68) | NPY2RNPY4RNPY5RNPY1RKISS1R | |
| SCHEMBL30398408 | 0.92 | NPY1R (0.65) | NPY2RNPY4RNPY5RNPY1RKISS1R | |
| SCHEMBL30423542 | 0.91 | NPY1R (0.66) | NPY2RNPY4RNPY5RNPY1RKISS1R | |
| SCHEMBL31182571 | 0.91 | NPY2R (0.71) | NPY2RNPY4RNPY5RNPY1RCXCR4 | |
| SCHEMBL29552852 | 0.91 | KISS1R (0.68) | NPY2RNPY4RNPY5RNPY1RKISS1R | |
| SCHEMBL29815129 | 0.90 | KISS1R (0.67) | NPY2RNPY4RNPY5RNPY1RKISS1R | |
| SCHEMBL30633122 | 0.90 | NPY2R (0.70) | NPY2RNPY4RNPY5RNPY1RKISS1R |
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 235 patents — showing the first 20. claimed = in the patent's claims; disclosed = body only.
| Patent | Title | Assignee | Published | Priority | Filing | Country | Status |
|---|---|---|---|---|---|---|---|
| EP-3417102-B1 | METHOD FOR RECOVERING CONCENTRATED HYDROLYSATE AFTER HYDROLYSIS OF CELLULOSE MATERIAL | VALMET OY (SE) | 2024-10-09 | — | — | EP | claimed |
| EP-3990692-B1 | METHOD FOR EXTRACTING HEMICELLULOSE FROM LIGNOCELLULOSIC MATERIAL | VALMET OY (SE) | 2024-07-24 | — | — | EP | claimed |
| CN-111046504-B | Low-noise optimization method suitable for geometric parameters of bionic vane pump | 江苏大学 | 2024-03-22 | — | — | CN | claimed |
| CN-113543194-B | L1-SINR measurement period based on Channel Measurement Resources (CMR) and Interference Measurement Resources (IMR) | 联发科技股份有限公司 | 2024-03-15 | — | — | CN | claimed |
| EP-3559340-B1 | A METHOD FOR MANUFACTURING DISSOLVING PULP | SOEDRA SKOGSAEGARNA EKONOMISK FOERENING (SE) | 2023-12-13 | — | — | EP | claimed |
| CN-116703195-A | Method for estimating soil erosion of different geographical areas based on factor algorithm combination optimization | 中国科学院南京地理与湖泊研究所 | 2023-09-05 | — | — | CN | claimed |
| CN-114726686-B | Uniform area array millimeter wave large-scale MIMO channel estimation method | 南京邮电大学 | 2023-07-14 | — | — | CN | claimed |
| CN-116286928-A | Lactobacillus paracasei gene editing system based on endogenous CRISPR-Cas system and application | 中国农业科学院农产品加工研究所 | 2023-06-23 | — | — | CN | claimed |
| CN-111819323-B | Method for producing dissolving pulp | 安德里兹公司 | 2023-05-16 | — | — | CN | claimed |
| CN-112987088-B | Seepage medium seismic transverse wave numerical simulation and imaging method | 成都理工大学 | 2023-04-18 | — | — | CN | claimed |
| CN-108897977-B | Runoff evolution uncertain attribution method based on large-area hydrological simulation | 河海大学 | 2022-10-14 | — | — | CN | claimed |
| CN-114008264-B | Method for extracting hemicellulose from lignocellulose material | 维美德公司 | 2022-09-13 | — | — | CN | claimed |
| CN-114726686-A | Uniform area array millimeter wave large-scale MIMO channel estimation method | 南京邮电大学 | 2022-07-08 | — | — | CN | claimed |
| CN-111709587-B | Power distribution system state probability evaluation method based on probability-time sequence uncertainty | 国网山西省电力公司电力科学研究院 | 2022-05-24 | — | — | CN | claimed |
| EP-3990692-A1 | METHOD FOR EXTRACTING HEMICELLULOSE FROM LIGNOCELLULOSIC MATERIAL | VALMET AB (SE) | 2022-05-04 | — | — | EP | claimed |
| CN-114096711-A | High alpha and high intrinsic viscosity pulp production apparatus, method and system | 布拉塞尔巴伊亚特种纤维素公司 | 2022-02-25 | — | — | CN | claimed |
| CN-116398251-B | Method and apparatus for providing damping of airfoils | GENERAL ELECTRIC CO. (US) | 2026-05-26 | — | — | CN | disclosed |
| US-12637951-B2 | Part-span shrouds for pitch controlled aircrafts | GENERAL ELECTRIC COMPANY (US) | 2026-05-26 | — | — | US | disclosed |
| WO-2022017711-A1 | POSITION CONTROLLER SELF-ASSESSMENT FOR DIGITAL TWIN | SAMSON AKTIENGESELLSCHAFT (DE) | 2022-01-27 | — | — | WO | disclosed |
| CN-113962440-A | DPC and GRU fused photovoltaic prediction method and system | 国家电投集团综合智慧能源科技有限公司 | 2022-01-21 | — | — | 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-12637951-B2 | Part-span shrouds for pitch controlled aircrafts | SEPTIN8, ZW10, FZD7 | NPY2R 1510/4885NPY4R 2558/4885NPY5R 2853/4885 |
“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.