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

Primary targets: PKCA, PKCB1, PKCB2, PKCD, PKCEPSILON, PKCETA, PKCG, PKCIOTA, PKCMU_PRKD1, PKCNU_PRKD3, PKCTHETA, PKCZETA · FDA status: Phase III FDA Trials

Selectivity scorecard

MeasuredDerived
KISS
96.99
Gini
0.719
CATDS
0.019

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 Darovasertib. Strongest target: PKCD at 99.9% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1PKCD99.9%0.1%
2PKCTHETA99.9%0.1%
3PKCEPSILON99.8%0.2%
4PKCETA99.8%0.2%
5PKCB299.5%0.5%
6PKCB199.0%1.0%
7PKCG97.7%2.3%
8PKCA97.5%2.5%
9DMPK297.2%2.8%
10TRKC94.5%5.5%
11MRCKB_CDC42BPB91.2%8.8%
12MSK2_RPS6KA491.0%9.0%
13TRKB88.9%11.1%
14ERBB2_HER287.7%12.3%
15GCK_MAP4K280.0%20.1%
16MLCK2_MYLK279.6%20.4%
17PKN2_PRK279.3%20.7%
18MRCKA_CDC42BPA75.1%24.9%
19STK21_CIT73.4%26.6%
20PKCNU_PRKD372.8%27.2%

Selectivity landscape

MeasuredDerived

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

Atlas insights for Darovasertib

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
1132.36
ALLOGRAFT_REJECTION
2147.23
ANDROGEN_RESPONSE
1077.79
ANGIOGENESIS
265.79
APICAL_JUNCTION
2066.98
APICAL_SURFACE
243.98
APOPTOSIS
3234.09
BILE_ACID_METABOLISM
427.77
CHOLESTEROL_HOMEOSTASIS
299.70
COAGULATION
247.56
COMPLEMENT
1463.03
DNA_REPAIR
838.70
E2F_TARGETS
2927.46
EPITHELIAL_MESENCHYMAL_TRANSITION
1013.79
ESTROGEN_RESPONSE_EARLY
1512.98
ESTROGEN_RESPONSE_LATE
1319.83
FATTY_ACID_METABOLISM
260.00
G2M_CHECKPOINT
3107.83
GLYCOLYSIS
1148.96
HEDGEHOG_SIGNALING
386.79
HEME_METABOLISM
1165.44
HYPOXIA
2198.27
IL2_STAT5_SIGNALING
1507.68
IL6_JAK_STAT3_SIGNALING
1302.14
INFLAMMATORY_RESPONSE
1788.94
INTERFERON_ALPHA_RESPONSE
284.02
INTERFERON_GAMMA_RESPONSE
1992.57
KRAS_SIGNALING_DN
456.08
KRAS_SIGNALING_UP
970.63
MITOTIC_SPINDLE
2290.57
MTORC1_SIGNALING
1581.48
MYC_TARGETS_V1
1543.31
MYC_TARGETS_V2
522.05
MYOGENESIS
1863.73
NOTCH_SIGNALING
264.16
OXIDATIVE_PHOSPHORYLATION
295.27
P53_PATHWAY
2095.29
PANCREAS_BETA_CELLS
349.93
PEROXISOME
561.43
PI3K_AKT_MTOR_SIGNALING
3457.13
PROTEIN_SECRETION
566.79
REACTIVE_OXYGEN_SPECIES_PATHWAY
208.65
SPERMATOGENESIS
764.87
TGF_BETA_SIGNALING
1164.63
TNFA_SIGNALING_VIA_NFKB
2514.93
UNFOLDED_PROTEIN_RESPONSE
661.82
UV_RESPONSE_DN
2074.38
UV_RESPONSE_UP
1302.31
WNT_BETA_CATENIN_SIGNALING
1147.95
XENOBIOTIC_METABOLISM
574.47

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 = 3.12 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 = 0.863

SampleCancer typecos to ideal
EPT0291EPN0.863
TCGA-CF-A5U8-01A-11R-A28M-070.852
SRR122024980.836
SRR1443713GTEX0.835
b6a7e87e-2674-4a48-a3c2-c8a9806762b50.830

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