Research Use Only. KIRhub outputs are computational research artifacts. They are not validated for clinical decision-making, diagnosis, or treatment.

Primary targets: C_MET · FDA status: FDA Approved

Selectivity scorecard

MeasuredDerived
KISS
99.75
Gini
0.727
CATDS
0.042

Computed from wild-type kinome inhibition at 1 μM. Gini reproduces the published values within tolerance; KISS and CATDS are computed but pending reconciliation with the paper's reference code.

Polypharmacology radar

MeasuredDerived

Top 20 strongest-inhibited wild-type kinases for Tepotinib. Strongest target: C_MET at 95.2% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1C_MET95.2%4.8%
2TRKC86.2%13.8%
3IRAK472.7%27.3%
4IRAK172.6%27.4%
5FGFR272.6%27.4%
6AXL69.6%30.4%
7FGFR162.3%37.7%
8MELK50.4%49.6%
9FGFR349.8%50.2%
10FGFR449.2%50.8%
11TRKB33.1%66.9%
12STK39_STLK330.5%69.5%
13FLT4_VEGFR328.5%71.5%
14FLT1_VEGFR128.2%71.8%
15BMPR225.1%74.9%
16ALK24.9%75.1%
17LYN24.9%75.1%
18CAMK1G23.4%76.6%
19LCK19.9%80.1%
20GSK3B18.7%81.3%

Selectivity landscape

MeasuredDerived

Where Tepotinib sits in the 92-drug selectivity landscape (KISS vs Gini). The highlighted point is Tepotinib.

Atlas insights for Tepotinib

MeasuredReference

Pathway-space view of what this drug actually does, drawn from the Pathway Atlas.

On-target vs off-target shadow

DerivedMeasured

How much of this drug's pathway perturbation comes from primary targets vs polypharmacology vs 2nd-order propagation. When off-target dominates, the FDA label is the smallest description of the drug.

On-target0%
Off-target100%
Ghost (2nd-order)0%
PathwayCompositionTotal |Π|
ADIPOGENESIS
737.96
ALLOGRAFT_REJECTION
1938.38
ANDROGEN_RESPONSE
682.09
ANGIOGENESIS
314.24
APICAL_JUNCTION
2189.69
APICAL_SURFACE
222.84
APOPTOSIS
2110.72
BILE_ACID_METABOLISM
295.92
CHOLESTEROL_HOMEOSTASIS
327.49
COAGULATION
235.70
COMPLEMENT
1275.25
DNA_REPAIR
701.15
E2F_TARGETS
1823.46
EPITHELIAL_MESENCHYMAL_TRANSITION
521.96
ESTROGEN_RESPONSE_EARLY
841.90
ESTROGEN_RESPONSE_LATE
905.18
FATTY_ACID_METABOLISM
310.95
G2M_CHECKPOINT
1885.24
GLYCOLYSIS
912.22
HEDGEHOG_SIGNALING
133.01
HEME_METABOLISM
639.29
HYPOXIA
1214.53
IL2_STAT5_SIGNALING
816.55
IL6_JAK_STAT3_SIGNALING
1532.50
INFLAMMATORY_RESPONSE
1138.22
INTERFERON_ALPHA_RESPONSE
201.58
INTERFERON_GAMMA_RESPONSE
1821.90
KRAS_SIGNALING_DN
248.18
KRAS_SIGNALING_UP
732.25
MITOTIC_SPINDLE
1606.16
MTORC1_SIGNALING
1130.81
MYC_TARGETS_V1
1163.26
MYC_TARGETS_V2
281.03
MYOGENESIS
858.63
NOTCH_SIGNALING
91.90
OXIDATIVE_PHOSPHORYLATION
561.40
P53_PATHWAY
1211.04
PANCREAS_BETA_CELLS
146.10
PEROXISOME
372.77
PI3K_AKT_MTOR_SIGNALING
2803.44
PROTEIN_SECRETION
549.46
REACTIVE_OXYGEN_SPECIES_PATHWAY
178.27
SPERMATOGENESIS
427.03
TGF_BETA_SIGNALING
829.05
TNFA_SIGNALING_VIA_NFKB
1398.94
UNFOLDED_PROTEIN_RESPONSE
391.70
UV_RESPONSE_DN
1451.33
UV_RESPONSE_UP
854.74
WNT_BETA_CATENIN_SIGNALING
688.12
XENOBIOTIC_METABOLISM
510.18

See this drug on the perturbation map →

Anti-tumor matches — the "ideal patient" search

ModeledDerived

Top 5 real tumors closest to this drug's ideal patient (the tumor whose pathway state = −Π_d). Closest match cosine = 0.859

SampleCancer typecos to ideal
EPT0291EPN0.859
TCGA-CF-A5U8-01A-11R-A28M-070.835
SRR122024980.832
SRR1443713GTEX0.832
aMVAC.P_005_TURBT_S2230.832

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