Sugi Predict

Sugi Predict / Compounds / SCHEMBL22229732

SCHEMBL22229732

SCHEMBL22229732

COCOc1c(-c2cc(-c3c(C)cc(C)cc3C)cc(-c3c(C)cc(C)cc3C)c2)cc2c(c1-c1c3c(cc(-c4cc(-c5c(C)cc(C)cc5C)cc(-c5c(C)cc(C)cc5C)c4)c1OCOC)CCCC3)CCCC2

nearest known ligand 0.46

Predicted protein targets (top 2)

geneUniProtsupporting neighboursconfidence
▸ MEN1 O00255 1/20 0.46
▸ KMT2A Q03164 1/20 0.46

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
SCHEMBL22256340 0.78 MEN1 (0.34) MEN1KMT2A
SCHEMBL22229733 0.75 CYP11B2 (0.37) MEN1KMT2A
SCHEMBL22229685 0.74 MEN1 (0.80) MEN1KMT2A
SCHEMBL30364392 0.74 MEN1 (0.80) MEN1KMT2A
SCHEMBL22229659 0.74 DHFR (0.39) MEN1KMT2A
SCHEMBL22229757 0.73 SLC6A2 (0.36) MEN1KMT2A
SCHEMBL22229675 0.73 ALDH1A1 (0.33) MEN1KMT2A
SCHEMBL1524896 0.69 MEN1 (0.61) MEN1KMT2A
SCHEMBL14460784 0.68 MEN1 (0.37) MEN1KMT2A
SCHEMBL22229709 0.68 MEN1 (0.49) MEN1KMT2A

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
US-11664093-B2 Extrapolative prediction of enantioselectivity enabled by computer-driven workflow, new molecular representations and machine learning THE BOARD OF TRUSTEES OF THE UNIVERSITY OF ILLINOIS (US) 2023-05-30 — — US disclosed
US-11664093-B2 Extrapolative prediction of enantioselectivity enabled by computer-driven workflow, new molecular representations and machine learning THE BOARD OF TRUSTEES OF THE UNIVERSITY OF ILLINOIS (US) 2023-05-30 — — US disclosed
US-20200234798-A1 EXTRAPOLATIVE PREDICTION OF ENANTIOSELECTIVITY ENABLED BY COMPUTER-DRIVEN WORKFLOW, NEW MOLECULAR REPRESENTATIONS AND MACHINE LEARNING THE BOARD OF TRUSTEES OF THE UNIVERSITY OF ILLINOIS 2020-07-23 — — US disclosed