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

Primary targets: JAK2 · FDA status: FDA Approved

Selectivity scorecard

MeasuredDerived
KISS
96.21
Gini
0.576
CATDS
0.010

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 Fedratinib. Strongest target: RET at 99.9% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1RET99.9%0.1%
2JAK299.4%0.6%
3FLT398.2%1.8%
4ZIPK_DAPK397.7%2.3%
5DAPK197.3%2.6%
6SIK296.8%3.2%
7DDR195.2%4.8%
8FAK_PTK294.4%5.6%
9JAK194.2%5.8%
10TYK293.6%6.4%
11ARK5_NUAK193.5%6.5%
12ACK193.4%6.6%
13AURORA_C92.1%7.9%
14ROS_ROS190.7%9.3%
15STK22D_TSSK190.5%9.5%
16SIK188.8%11.2%
17FLT4_VEGFR388.4%11.6%
18DDR288.3%11.7%
19LCK87.1%12.9%
20YES_YES186.8%13.2%

Selectivity landscape

MeasuredDerived

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

Atlas insights for Fedratinib

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-target5%
Off-target95%
Ghost (2nd-order)0%
PathwayCompositionTotal |Π|
ADIPOGENESIS
2978.90
ALLOGRAFT_REJECTION
10006.76
ANDROGEN_RESPONSE
1915.80
ANGIOGENESIS
1682.91
APICAL_JUNCTION
10132.24
APICAL_SURFACE
1213.44
APOPTOSIS
7716.30
BILE_ACID_METABOLISM
1124.55
CHOLESTEROL_HOMEOSTASIS
1384.27
COAGULATION
1136.95
COMPLEMENT
5578.90
DNA_REPAIR
1869.47
E2F_TARGETS
5241.38
EPITHELIAL_MESENCHYMAL_TRANSITION
2280.21
ESTROGEN_RESPONSE_EARLY
3833.72
ESTROGEN_RESPONSE_LATE
3774.63
FATTY_ACID_METABOLISM
997.31
G2M_CHECKPOINT
5228.55
GLYCOLYSIS
3202.91
HEDGEHOG_SIGNALING
1030.20
HEME_METABOLISM
2309.14
HYPOXIA
4407.63
IL2_STAT5_SIGNALING
3547.81
IL6_JAK_STAT3_SIGNALING
6918.98
INFLAMMATORY_RESPONSE
5462.27
INTERFERON_ALPHA_RESPONSE
1103.69
INTERFERON_GAMMA_RESPONSE
7660.13
KRAS_SIGNALING_DN
1224.11
KRAS_SIGNALING_UP
3586.57
MITOTIC_SPINDLE
6758.32
MTORC1_SIGNALING
4157.31
MYC_TARGETS_V1
3633.77
MYC_TARGETS_V2
867.28
MYOGENESIS
3485.24
NOTCH_SIGNALING
141.04
OXIDATIVE_PHOSPHORYLATION
1640.56
P53_PATHWAY
4029.34
PANCREAS_BETA_CELLS
290.15
PEROXISOME
1413.67
PI3K_AKT_MTOR_SIGNALING
10122.59
PROTEIN_SECRETION
2192.24
REACTIVE_OXYGEN_SPECIES_PATHWAY
518.19
SPERMATOGENESIS
1732.33
TGF_BETA_SIGNALING
2209.95
TNFA_SIGNALING_VIA_NFKB
4941.38
UNFOLDED_PROTEIN_RESPONSE
1835.49
UV_RESPONSE_DN
5681.06
UV_RESPONSE_UP
4086.88
WNT_BETA_CATENIN_SIGNALING
2336.26
XENOBIOTIC_METABOLISM
2349.43

See this drug on the perturbation map →

Hallmarks-of-Cancer reach

DerivedReference

Projection onto the 10 canonical Hanahan & Weinberg hallmarks. Breadth = how many hallmarks this drug meaningfully perturbs.

ProliferationEvading apoptosisAngiogenesisInvasion / metastasisReplicative immortalityDeregulated metabolismImmune evasionGenome instabilityInflammationGrowth signaling

Breadth = 3.09 bits (max possible across 10 hallmarks = 3.32 bits). Multi-hallmark agent — broad polypharmacology.

Compare against the full catalog →

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 = 0.844

SampleCancer typecos to ideal
EPT0291EPN0.844
SRR233037520.836
SRR108999840.827
aMVAC.P_005_TURBT_S2230.825
TCGA-CF-A5U8-01A-11R-A28M-070.825

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