Predicted protein targets (top 10)
| gene | UniProt | supporting neighbours | confidence | |
|---|---|---|---|---|
| ▸ | CCNA2 | P20248 | 2/20 | 0.57 |
| ▸ | CDK2 | P24941 | 2/20 | 0.57 |
| ▸ | CCNA1 | P78396 | 2/20 | 0.57 |
| ▸ | VIPR2 | P41587 | 10/20 | 0.57 |
| ▸ | VIPR1 | P32241 | 9/20 | 0.57 |
| ▸ | AGTR1 | P30556 | 2/20 | 0.51 |
| ▸ | AGTR2 | P50052 | 1/20 | 0.51 |
| ▸ | SLC15A2 | Q16348 | 1/20 | 0.51 |
| ▸ | PTH1R | Q03431 | 2/20 | 0.50 |
| ▸ | OPRL1 | P41146 | 1/20 | 0.49 |
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 | |
|---|---|---|---|---|
| SCHEMBL29876193 | 0.88 | GRIN2D (0.54) | VIPR2VIPR1OPRL1 | |
| SCHEMBL29412270 | 0.87 | VIPR2 (0.66) | VIPR2VIPR1PTH1R | |
| SCHEMBL29587816 | 0.84 | VIPR2 (0.63) | VIPR2VIPR1PTH1R | |
| SCHEMBL29464255 | 0.84 | PTH1R (0.55) | CCNA2CDK2CCNA1PTH1ROPRL1 | |
| SCHEMBL29542974 | 0.84 | CCNA2 (0.57) | CCNA2CDK2CCNA1VIPR2VIPR1 | |
| SCHEMBL29350082 | 0.84 | OPRL1 (0.61) | CCNA2CDK2CCNA1VIPR2VIPR1 | |
| SCHEMBL30122771 | 0.81 | CCNA2 (0.64) | CCNA2CDK2CCNA1AGTR1AGTR2 | |
| SCHEMBL29980392 | 0.80 | OPRL1 (0.55) | OPRL1 | |
| SCHEMBL31738162 | 0.79 | BACE1 (0.62) | VIPR2VIPR1 | |
| SCHEMBL29361994 | 0.78 | AGTR2 (0.57) | CCNA2CDK2CCNA1AGTR1AGTR2 |
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 75 patents — showing the first 20. claimed = in the patent's claims; disclosed = body only.
| Patent | Title | Assignee | Published | Priority | Filing | Country | Status |
|---|---|---|---|---|---|---|---|
| CN-112613323-B | Grammar-dependent enhanced math application topic semantic recognition and reasoning method and system | 中国科学技术大学 | 2025-03-18 | — | — | CN | claimed |
| CN-118569816-B | System for determining running state of target area equipment | 北京中实信息技术有限公司 | 2024-11-01 | — | — | CN | claimed |
| CN-118822005-A | Capacity double-layer optimization method for polar region cleaning comprehensive energy system | 山西省能源互联网研究院 | 2024-10-22 | — | — | CN | claimed |
| CN-118800110-A | High-simulation hemodialysis skill simulation training and checking complete equipment | 营口东峰工贸有限公司 | 2024-10-18 | — | — | CN | claimed |
| CN-118569816-A | System for determining running state of target area equipment | 北京中实信息技术有限公司 | 2024-08-30 | — | — | CN | claimed |
| CN-118537047-A | Medical market data analysis system and method based on big data | 上海倍通医药科技咨询有限公司 | 2024-08-23 | — | — | CN | claimed |
| CN-114578830-B | Snake-like robot motion planning method based on reinforced learning | 北京化工大学 | 2024-06-28 | — | — | CN | claimed |
| CN-113075284-B | Method for detecting accumulated oxides in boiler heating surface tube | 国能锅炉压力容器检验有限公司 | 2023-09-05 | — | — | CN | claimed |
| CN-219279382-U | Novel mechanical safety lock mechanism | 中意泰达(营口)汽车保修设备有限公司 | 2023-06-30 | — | — | CN | claimed |
| CN-114491146-B | Video image processing method suitable for video monitoring equipment | 广州智慧城市发展研究院 | 2022-07-12 | — | — | CN | claimed |
| CN-114578830-A | Snake-imitating robot motion planning method based on reinforcement learning | 北京化工大学 | 2022-06-03 | — | — | CN | claimed |
| CN-114491146-A | Video image processing method suitable for video monitoring equipment | 广州智慧城市发展研究院 | 2022-05-13 | — | — | CN | claimed |
| CN-110750049-B | Intermittent process 2D prediction fault-tolerant control method with time lag and disturbance | 海南师范大学 | 2022-03-29 | — | — | CN | claimed |
| EP-4748905-A1 | LIQUID-CRYSTALLINE MEDIUM | Merck Patent GmbH (DE) | 2026-05-27 | — | — | EP | disclosed |
| CN-122080952-A | Liquid-crystalline medium | — | 2026-05-26 | — | — | CN | disclosed |
| US-20260106735-A1 | SECURE MULTI-PARTY COMPARISON | BEIJING ZITIAO NETWORK TECHNOLOGY CO LTD (CN) | 2026-04-16 | — | — | US | disclosed |
| CN-112270276-B | Behavior identification method in complex environment based on Kinect and WiFi data combination | 重庆邮电大学 | 2022-05-06 | — | — | CN | disclosed |
| CN-114304156-A | Application of sugar composition in promoting plant growth and preventing plant diseases | 广州市浩丰生物科技有限公司 | 2022-04-12 | — | — | CN | disclosed |
| CN-110750049-B | Intermittent process 2D prediction fault-tolerant control method with time lag and disturbance | 海南师范大学 | 2022-03-29 | — | — | CN | disclosed |
| CN-113956513-A | Butadiene rubber and preparation method thereof | 中国石油化工股份有限公司 | 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-20260106735-A1 | SECURE MULTI-PARTY COMPARISON | MPC2, OTC, OCIAD2 | CCNA2 2683/4885CDK2 4321/4885CCNA1 3112/4885 |
“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.