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

Primary targets: BCR_ABL, ABL1, ABL2_ARG · FDA status: FDA Approved

Selectivity scorecard

MeasuredDerived
KISS
96.49
Gini
0.765
CATDS
0.020

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 Nilotinib. Strongest target: DDR2 at 99.7% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1DDR299.7%0.3%
2EPHB198.8%1.2%
3EPHB298.7%1.3%
4DDR198.5%1.5%
5RAF198.3%1.7%
6ABL198.0%2.0%
7PDGFRA97.9%2.1%
8EPHA297.6%2.4%
9ABL2_ARG96.9%3.1%
10LCK95.1%4.9%
11EPHB494.6%5.4%
12EPHA494.4%5.6%
13EPHA593.8%6.2%
14FMS91.4%8.6%
15EPHB389.9%10.1%
16ZAK_MLTK87.8%12.2%
17PDGFRB86.7%13.3%
18BRAF85.8%14.2%
19P38B_MAPK1183.9%16.1%
20ARAF81.8%18.2%

Selectivity landscape

MeasuredDerived

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

Atlas insights for Nilotinib

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
2085.73
ALLOGRAFT_REJECTION
6030.73
ANDROGEN_RESPONSE
751.26
ANGIOGENESIS
1235.38
APICAL_JUNCTION
7203.42
APICAL_SURFACE
626.48
APOPTOSIS
5251.31
BILE_ACID_METABOLISM
600.59
CHOLESTEROL_HOMEOSTASIS
1179.18
COAGULATION
1008.57
COMPLEMENT
4202.48
DNA_REPAIR
1109.37
E2F_TARGETS
2993.73
EPITHELIAL_MESENCHYMAL_TRANSITION
1352.27
ESTROGEN_RESPONSE_EARLY
2274.16
ESTROGEN_RESPONSE_LATE
1783.06
FATTY_ACID_METABOLISM
505.12
G2M_CHECKPOINT
3406.10
GLYCOLYSIS
1795.17
HEDGEHOG_SIGNALING
772.11
HEME_METABOLISM
1458.31
HYPOXIA
3114.78
IL2_STAT5_SIGNALING
2401.81
IL6_JAK_STAT3_SIGNALING
3286.96
INFLAMMATORY_RESPONSE
3610.42
INTERFERON_ALPHA_RESPONSE
741.63
INTERFERON_GAMMA_RESPONSE
3971.57
KRAS_SIGNALING_DN
620.68
KRAS_SIGNALING_UP
2501.34
MITOTIC_SPINDLE
5108.69
MTORC1_SIGNALING
2367.21
MYC_TARGETS_V1
2587.59
MYC_TARGETS_V2
552.91
MYOGENESIS
1948.63
NOTCH_SIGNALING
149.68
OXIDATIVE_PHOSPHORYLATION
880.77
P53_PATHWAY
2684.70
PANCREAS_BETA_CELLS
213.98
PEROXISOME
770.66
PI3K_AKT_MTOR_SIGNALING
6233.27
PROTEIN_SECRETION
1266.14
REACTIVE_OXYGEN_SPECIES_PATHWAY
484.11
SPERMATOGENESIS
1081.80
TGF_BETA_SIGNALING
1285.79
TNFA_SIGNALING_VIA_NFKB
3235.02
UNFOLDED_PROTEIN_RESPONSE
708.40
UV_RESPONSE_DN
3681.37
UV_RESPONSE_UP
2576.98
WNT_BETA_CATENIN_SIGNALING
1159.54
XENOBIOTIC_METABOLISM
1129.89

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 = 3.08 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 = 0.830

SampleCancer typecos to ideal
EPT0291EPN0.830
SRR233037520.829
TCGA-CF-A5U8-01A-11R-A28M-070.816
aMVAC.P_005_TURBT_S2230.813
C3N-034200.811

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