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

Primary targets: ALK · FDA status: FDA Approved

Selectivity scorecard

MeasuredDerived
KISS
95.44
Gini
0.618
CATDS
0.014

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 Ceritinib. Strongest target: FES_FPS at 99.8% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1FES_FPS99.8%0.3%
2STK22D_TSSK199.7%0.3%
3LRRK299.4%0.6%
4IRR_INSRR98.9%1.1%
5FER98.4%1.6%
6ALK98.3%1.7%
7IGF1R98.1%1.9%
8IR97.8%2.2%
9ROS_ROS197.7%2.3%
10TNK197.3%2.7%
11TYK1_LTK97.3%2.7%
12ACK197.2%2.8%
13FAK_PTK296.4%3.6%
14MYO3B94.4%5.6%
15CAMKK292.7%7.3%
16CLK192.1%7.9%
17CLK291.1%8.9%
18PHKG190.1%9.9%
19PYK289.7%10.3%
20STK32B_YANK289.3%10.7%

Selectivity landscape

MeasuredDerived

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

Atlas insights for Ceritinib

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-target3%
Off-target97%
Ghost (2nd-order)0%
PathwayCompositionTotal |Π|
ADIPOGENESIS
1150.87
ALLOGRAFT_REJECTION
3699.17
ANDROGEN_RESPONSE
1336.08
ANGIOGENESIS
854.18
APICAL_JUNCTION
4242.72
APICAL_SURFACE
456.58
APOPTOSIS
3604.64
BILE_ACID_METABOLISM
727.17
CHOLESTEROL_HOMEOSTASIS
591.22
COAGULATION
544.16
COMPLEMENT
2419.87
DNA_REPAIR
1000.78
E2F_TARGETS
3452.41
EPITHELIAL_MESENCHYMAL_TRANSITION
1092.49
ESTROGEN_RESPONSE_EARLY
2299.43
ESTROGEN_RESPONSE_LATE
2198.60
FATTY_ACID_METABOLISM
414.12
G2M_CHECKPOINT
3258.07
GLYCOLYSIS
1860.37
HEDGEHOG_SIGNALING
549.19
HEME_METABOLISM
1092.43
HYPOXIA
2508.76
IL2_STAT5_SIGNALING
1415.77
IL6_JAK_STAT3_SIGNALING
2257.31
INFLAMMATORY_RESPONSE
2431.96
INTERFERON_ALPHA_RESPONSE
339.56
INTERFERON_GAMMA_RESPONSE
3095.51
KRAS_SIGNALING_DN
951.33
KRAS_SIGNALING_UP
1342.19
MITOTIC_SPINDLE
3460.05
MTORC1_SIGNALING
2293.50
MYC_TARGETS_V1
2209.88
MYC_TARGETS_V2
582.63
MYOGENESIS
2102.50
NOTCH_SIGNALING
224.56
OXIDATIVE_PHOSPHORYLATION
576.84
P53_PATHWAY
2033.40
PANCREAS_BETA_CELLS
163.26
PEROXISOME
602.18
PI3K_AKT_MTOR_SIGNALING
4537.83
PROTEIN_SECRETION
1134.27
REACTIVE_OXYGEN_SPECIES_PATHWAY
153.45
SPERMATOGENESIS
948.11
TGF_BETA_SIGNALING
873.00
TNFA_SIGNALING_VIA_NFKB
2516.03
UNFOLDED_PROTEIN_RESPONSE
989.95
UV_RESPONSE_DN
2313.53
UV_RESPONSE_UP
2075.05
WNT_BETA_CATENIN_SIGNALING
1407.58
XENOBIOTIC_METABOLISM
1161.43

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 = 0.867

SampleCancer typecos to ideal
EPT0291EPN0.867
TCGA-CF-A5U8-01A-11R-A28M-070.849
SRR233037520.834
R2470.830
SRR122024980.830

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