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

Primary targets: KDR_VEGFR2 · FDA status: NMPA Approved

Selectivity scorecard

MeasuredDerived
KISS
97.73
Gini
0.704
CATDS
0.022

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 Apatinib. Strongest target: RAF1 at 100.0% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1RAF1100.0%0.0%
2C_KIT98.9%1.1%
3FMS97.8%2.2%
4FLT1_VEGFR195.6%4.4%
5YSK4_MAP3K1995.3%4.7%
6BRAF94.1%5.9%
7KDR_VEGFR292.3%7.7%
8FLT4_VEGFR390.8%9.2%
9ARAF90.7%9.3%
10JAK188.7%11.3%
11LYN82.3%17.7%
12TAOK2_TAO181.5%18.6%
13RET81.1%18.9%
14DDR280.9%19.1%
15PDGFRB80.9%19.1%
16LCK71.8%28.2%
17ZAK_MLTK71.1%28.9%
18HIPK470.8%29.2%
19ABL2_ARG65.4%34.6%
20JAK265.3%34.7%

Selectivity landscape

MeasuredDerived

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

Atlas insights for Apatinib

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
1807.53
ALLOGRAFT_REJECTION
5296.23
ANDROGEN_RESPONSE
723.40
ANGIOGENESIS
820.54
APICAL_JUNCTION
5706.96
APICAL_SURFACE
586.03
APOPTOSIS
3734.49
BILE_ACID_METABOLISM
461.52
CHOLESTEROL_HOMEOSTASIS
566.65
COAGULATION
635.26
COMPLEMENT
3080.44
DNA_REPAIR
800.12
E2F_TARGETS
2540.09
EPITHELIAL_MESENCHYMAL_TRANSITION
994.35
ESTROGEN_RESPONSE_EARLY
1886.59
ESTROGEN_RESPONSE_LATE
1624.68
FATTY_ACID_METABOLISM
376.56
G2M_CHECKPOINT
2479.88
GLYCOLYSIS
1451.23
HEDGEHOG_SIGNALING
528.46
HEME_METABOLISM
1339.99
HYPOXIA
2182.46
IL2_STAT5_SIGNALING
2065.76
IL6_JAK_STAT3_SIGNALING
3898.34
INFLAMMATORY_RESPONSE
3394.06
INTERFERON_ALPHA_RESPONSE
695.59
INTERFERON_GAMMA_RESPONSE
3996.85
KRAS_SIGNALING_DN
524.97
KRAS_SIGNALING_UP
2199.89
MITOTIC_SPINDLE
3201.98
MTORC1_SIGNALING
2044.51
MYC_TARGETS_V1
1995.06
MYC_TARGETS_V2
453.28
MYOGENESIS
1544.77
NOTCH_SIGNALING
83.78
OXIDATIVE_PHOSPHORYLATION
754.71
P53_PATHWAY
1745.17
PANCREAS_BETA_CELLS
120.79
PEROXISOME
489.86
PI3K_AKT_MTOR_SIGNALING
5775.16
PROTEIN_SECRETION
1122.07
REACTIVE_OXYGEN_SPECIES_PATHWAY
219.76
SPERMATOGENESIS
1183.35
TGF_BETA_SIGNALING
860.42
TNFA_SIGNALING_VIA_NFKB
2760.38
UNFOLDED_PROTEIN_RESPONSE
771.61
UV_RESPONSE_DN
3031.79
UV_RESPONSE_UP
2014.42
WNT_BETA_CATENIN_SIGNALING
907.08
XENOBIOTIC_METABOLISM
947.62

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 = 0.824

SampleCancer typecos to ideal
SRR233037520.824
EPT0291EPN0.823
TCGA-CF-A5U8-01A-11R-A28M-070.814
TCGA-FD-A43X-01A-11R-A23W-070.811
SRR108999840.808

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