SCHEMBL10246462

SCHEMBL10246462

CCCCCCCCCCCCCCCC(=O)NC(CCS(C)(=O)=O)C(=O)NCCCCC(N)=O

nearest known ligand 0.54

Predicted protein targets (top 10)

geneUniProtsupporting neighboursconfidence
▸ LPAR3 Q9UBY5 4/20 0.54
▸ LPAR1 Q92633 2/20 0.53
▸ TLR2 O60603 1/20 0.52
▸ SIRT6 Q8N6T7 1/20 0.49
▸ SIRT1 Q96EB6 1/20 0.49
▸ NOD1 Q9Y239 4/20 0.48
▸ GLP1R P43220 8/20 0.48
▸ GRIA1 P42261 1/20 0.47
▸ NMT2 O60551 1/20 0.43
▸ NMT1 P30419 1/20 0.43

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.

Compoundsimilaritytop predictedshared targets
SCHEMBL20542799 0.89 TLR2 (0.62) LPAR3LPAR1TLR2SIRT6SIRT1
SCHEMBL10246707 0.86 NOD1 (0.54) LPAR3LPAR1TLR2NOD1
SCHEMBL10246700 0.83 NOD1 (0.52) TLR2NOD1
SCHEMBL20542804 0.83 LPAR3 (0.65) LPAR3LPAR1TLR2SIRT6SIRT1
SCHEMBL20542805 0.83 LPAR3 (0.65) LPAR3LPAR1TLR2SIRT6SIRT1
SCHEMBL25457033 0.81 SIRT6 (0.69) LPAR3LPAR1TLR2SIRT6SIRT1
SCHEMBL20543154 0.81 SIRT6 (0.69) LPAR3LPAR1TLR2SIRT6SIRT1
SCHEMBL17749154 0.81 SIRT6 (0.69) LPAR3LPAR1TLR2SIRT6SIRT1
SCHEMBL20543155 0.81 SIRT6 (0.69) LPAR3LPAR1TLR2SIRT6SIRT1
SCHEMBL17751797 0.81 SIRT6 (0.69) LPAR3LPAR1TLR2SIRT6SIRT1

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 9 patents. claimed = in the patent's claims; disclosed = body only.

PatentTitleAssigneePublishedPriorityFilingCountryStatus
EP-3744729-B1 PEPTIDES, COMPOSITIONS COMPRISING THEM AND COSMETIC AND DERMOPHARMACEUTICAL USES SEDERMA SA (FR) 2023-03-01 — — EP disclosed
EP-3744729-A1 COMPOUNDS, IN PARTICULAR PEPTIDES, COMPOSITIONS COMPRISING THEM AND COSMETIC AND DERMOPHARMACEUTICAL USES SEDERMA (FR) 2020-12-02 — — EP disclosed
EP-2382230-B1 PEPTIDES KXK, COMPOSITIONS LES COMPRENANT ET UTILISATIONS COSMETIQUES ET DERMO-PHARMACEUTIQUES. SEDERMA SA (FR) 2018-05-23 — — EP disclosed
US-8697656-B2 Compounds, in particular peptides, compositions comprising them and cosmetic and dermo-pharmaceutical uses SEDERMA (FR) 2014-04-15 — — US disclosed
US-8697656-B2 Compounds, in particular peptides, compositions comprising them and cosmetic and dermo-pharmaceutical uses SEDERMA (FR) 2014-04-15 — — US disclosed
US-20120014887-A1 NEW COMPOUNDS, IN PARTICULAR PEPTIDES, COMPOSITIONS COMPRISING THEM AND COSMETIC AND DERMO-PHARMACEUTICAL USES SEDERMA (FR) 2012-01-19 — — US disclosed
US-20120014887-A1 NEW COMPOUNDS, IN PARTICULAR PEPTIDES, COMPOSITIONS COMPRISING THEM AND COSMETIC AND DERMO-PHARMACEUTICAL USES SEDERMA (FR) 2012-01-19 — — US disclosed
WO-2010082177-A2 NEW COMPOUNDS, IN PARTICULAR PEPTIDES, COMPOSITIONS COMPRISING THEM AND COSMETIC AND DERMOPHARMACEUTICAL USES SEDERMA (FR) 2010-07-22 — — WO disclosed
WO-2010082175-A2 NEW COMPOUNDS, IN PARTICULAR PEPTIDES, COMPOSITIONS COMPRISING THEM AND COSMETIC AND DERMOPHARMACEUTICAL USES SEDERMA (FR) 2010-07-22 — — WO 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.

PatentTitleText reads most aboutPredicted target · text-rank
US-20120014887-A1 NEW COMPOUNDS, IN PARTICULAR PEPTIDES, COMPOSITIONS COMPRISING THEM AND COSMETIC AND DERMO-PHARMACEUTICAL USES CUTA, PLOD3, MC1R LPAR3 586/4885LPAR1 819/4885TLR2 1036/4885

“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.

Send feedback