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

Primary targets: JAK1 · FDA status: FDA Approved

Selectivity scorecard

MeasuredDerived
KISS
99.50
Gini
0.581
CATDS
0.024

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 Abrocitinib. Strongest target: JAK1 at 98.7% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1JAK198.7%1.3%
2JAK292.6%7.4%
3TYK289.9%10.1%
4LRRK262.1%37.9%
5DMPK257.3%42.7%
6AURORA_A55.6%44.4%
7AURORA_C54.5%45.5%
8JAK351.1%48.9%
9MYLK450.0%50.0%
10SRPK147.9%52.1%
11STK38_NDR147.7%52.3%
12PKA37.8%62.2%
13BMPR235.8%64.2%
14PKACB34.8%65.2%
15TAK134.7%65.3%
16FLT333.2%66.8%
17MARK432.8%67.2%
18CLK132.1%67.9%
19MEK131.8%68.2%
20RET31.3%68.7%

Selectivity landscape

MeasuredDerived

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

Atlas insights for Abrocitinib

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-target9%
Off-target91%
Ghost (2nd-order)0%
PathwayCompositionTotal |Π|
ADIPOGENESIS
1209.62
ALLOGRAFT_REJECTION
3276.24
ANDROGEN_RESPONSE
681.65
ANGIOGENESIS
425.33
APICAL_JUNCTION
2840.33
APICAL_SURFACE
481.92
APOPTOSIS
2947.72
BILE_ACID_METABOLISM
281.99
CHOLESTEROL_HOMEOSTASIS
309.22
COAGULATION
285.48
COMPLEMENT
1583.32
DNA_REPAIR
761.87
E2F_TARGETS
2382.37
EPITHELIAL_MESENCHYMAL_TRANSITION
753.99
ESTROGEN_RESPONSE_EARLY
1529.42
ESTROGEN_RESPONSE_LATE
1422.49
FATTY_ACID_METABOLISM
278.90
G2M_CHECKPOINT
2396.32
GLYCOLYSIS
910.18
HEDGEHOG_SIGNALING
301.36
HEME_METABOLISM
938.36
HYPOXIA
1701.14
IL2_STAT5_SIGNALING
1562.80
IL6_JAK_STAT3_SIGNALING
3210.29
INFLAMMATORY_RESPONSE
2414.81
INTERFERON_ALPHA_RESPONSE
589.89
INTERFERON_GAMMA_RESPONSE
3439.75
KRAS_SIGNALING_DN
293.18
KRAS_SIGNALING_UP
1063.86
MITOTIC_SPINDLE
2071.94
MTORC1_SIGNALING
1289.37
MYC_TARGETS_V1
1518.97
MYC_TARGETS_V2
393.22
MYOGENESIS
1488.50
NOTCH_SIGNALING
125.70
OXIDATIVE_PHOSPHORYLATION
483.20
P53_PATHWAY
1589.84
PANCREAS_BETA_CELLS
103.00
PEROXISOME
314.74
PI3K_AKT_MTOR_SIGNALING
3671.69
PROTEIN_SECRETION
854.43
REACTIVE_OXYGEN_SPECIES_PATHWAY
154.73
SPERMATOGENESIS
765.67
TGF_BETA_SIGNALING
794.67
TNFA_SIGNALING_VIA_NFKB
2278.00
UNFOLDED_PROTEIN_RESPONSE
777.14
UV_RESPONSE_DN
1988.42
UV_RESPONSE_UP
1445.94
WNT_BETA_CATENIN_SIGNALING
928.85
XENOBIOTIC_METABOLISM
459.23

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 = 3.03 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 = 0.857

SampleCancer typecos to ideal
EPT0291EPN0.857
TCGA-CF-A5U8-01A-11R-A28M-070.845
TCGA-CV-7424-01A-11R-2081-070.840
SRR108999840.835
SRR122024980.834

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