SCHEMBL29410458

SCHEMBL29410458

O=C1OC[C@H](c2ccc(N3CCC(F)(F)C3)c(F)c2F)N1c1ccc2[nH]cnc2c1

nearest known ligand 0.88

Predicted protein targets (top 1)

geneUniProtsupporting neighboursconfidence
▸ QPCT Q16769 20/20 0.88

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
SCHEMBL17476410 1.00 QPCT (0.88) QPCT
SCHEMBL16053682 1.00 QPCT (0.88) QPCT
SCHEMBL16053298 0.88 QPCT (0.87) QPCT
SCHEMBL17476426 0.88 QPCT (0.87) QPCT
SCHEMBL29410510 0.88 QPCT (0.87) QPCT
SCHEMBL29410459 0.87 QPCT (0.88) QPCT
SCHEMBL17476423 0.87 QPCT (0.88) QPCT
SCHEMBL16052619 0.87 QPCT (0.88) QPCT
SCHEMBL16070928 0.84 QPCT (0.86) QPCT
SCHEMBL17476412 0.84 QPCT (0.86) QPCT

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

PatentTitleAssigneePublishedPriorityFilingCountryStatus
EP-3658141-B1 TREATING PATHOLOGICAL CONDITIONS BY DIRECT AND INDIRECT TARGETING OF SIRPALPHA - CD47 INTERACTION STICHTING HET NEDERLANDS KANKER INST ANTONI VAN LEEUWENHOEK ZIEKENHUIS (NL) 2022-11-16 — — EP claimed
US-20220087981-A1 TREATING PATHOLOGICAL CONDITIONS BY DIRECT AND INDIRECT TARGETING OF SIRPA-CD47 INTERACTION Stichting Het Nederlands Kanker Instituut-Antoni van Leeuwenhoek Ziekenhuis (NL) 2022-03-24 — — US disclosed
CN-108218849-B Novel inhibitors 维沃永治疗公众有限公司 2022-03-01 — — 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.

PatentTitleText reads most aboutPredicted target · text-rank
US-20220087981-A1 TREATING PATHOLOGICAL CONDITIONS BY DIRECT AND INDIRECT TARGETING OF SIRPA-CD47 INTERACTION QPCT, QPCTL, CD47 QPCT 1/4885

“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.

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