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

Primary targets: JAK3 · FDA status: FDA Approved

Selectivity scorecard

MeasuredDerived
KISS
99.25
Gini
0.684
CATDS
0.045

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 Tofacitinib. Strongest target: JAK3 at 98.2% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1JAK398.2%1.8%
2JAK195.2%4.8%
3JAK292.3%7.7%
4TYK281.0%19.0%
5PKN1_PRK155.8%44.2%
6PDK2_PDHK235.2%64.8%
7CAMKK233.0%67.0%
8TNK130.1%69.9%
9CK1D25.1%74.9%
10CDK9_CYCLIN_T122.6%77.4%
11PKCD20.7%79.3%
12MUSK20.2%79.8%
13VRK119.7%80.3%
14PKMYT119.3%80.7%
15STK38_NDR119.1%80.9%
16PKN2_PRK218.5%81.5%
17LRRK217.8%82.2%
18P38A_MAPK1417.6%82.4%
19PKG2_PRKG217.5%82.5%
20PDK1_PDPK117.3%82.7%

Selectivity landscape

MeasuredDerived

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

Atlas insights for Tofacitinib

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
885.96
ALLOGRAFT_REJECTION
2497.23
ANDROGEN_RESPONSE
379.42
ANGIOGENESIS
181.93
APICAL_JUNCTION
1684.15
APICAL_SURFACE
291.55
APOPTOSIS
1652.60
BILE_ACID_METABOLISM
135.85
CHOLESTEROL_HOMEOSTASIS
236.39
COAGULATION
178.03
COMPLEMENT
1106.29
DNA_REPAIR
372.42
E2F_TARGETS
1409.14
EPITHELIAL_MESENCHYMAL_TRANSITION
513.31
ESTROGEN_RESPONSE_EARLY
978.14
ESTROGEN_RESPONSE_LATE
965.20
FATTY_ACID_METABOLISM
212.89
G2M_CHECKPOINT
1186.95
GLYCOLYSIS
608.61
HEDGEHOG_SIGNALING
133.59
HEME_METABOLISM
444.21
HYPOXIA
1079.07
IL2_STAT5_SIGNALING
1090.34
IL6_JAK_STAT3_SIGNALING
2852.30
INFLAMMATORY_RESPONSE
1801.94
INTERFERON_ALPHA_RESPONSE
459.26
INTERFERON_GAMMA_RESPONSE
2718.34
KRAS_SIGNALING_DN
185.22
KRAS_SIGNALING_UP
795.71
MITOTIC_SPINDLE
972.45
MTORC1_SIGNALING
759.05
MYC_TARGETS_V1
867.44
MYC_TARGETS_V2
213.86
MYOGENESIS
786.41
NOTCH_SIGNALING
71.62
OXIDATIVE_PHOSPHORYLATION
251.95
P53_PATHWAY
859.99
PANCREAS_BETA_CELLS
67.28
PEROXISOME
143.00
PI3K_AKT_MTOR_SIGNALING
2459.49
PROTEIN_SECRETION
486.11
REACTIVE_OXYGEN_SPECIES_PATHWAY
44.90
SPERMATOGENESIS
687.13
TGF_BETA_SIGNALING
464.21
TNFA_SIGNALING_VIA_NFKB
1533.21
UNFOLDED_PROTEIN_RESPONSE
555.90
UV_RESPONSE_DN
1082.37
UV_RESPONSE_UP
946.42
WNT_BETA_CATENIN_SIGNALING
482.06
XENOBIOTIC_METABOLISM
225.68

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 = 0.836

SampleCancer typecos to ideal
EPT0291EPN0.836
C3L-037260.829
SRR108999840.822
TCGA-CF-A5U8-01A-11R-A28M-070.820
TCGA-CV-7424-01A-11R-2081-070.817

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