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

Primary targets: BRAF · FDA status: FDA Approved

Selectivity scorecard

MeasuredDerived
KISS
94.74
Gini
0.633
CATDS
0.011

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 Dabrafenib. Strongest target: RAF1 at 99.8% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1RAF199.8%0.2%
2NEK999.7%0.3%
3LIMK199.0%1.0%
4LIMK298.9%1.1%
5BRAF98.3%1.7%
6TESK197.0%3.0%
7EIF2AK296.6%3.4%
8ZAK_MLTK96.4%3.6%
9ARAF96.3%3.7%
10RIPK396.0%4.0%
11SIK196.0%4.0%
12DDR295.4%4.6%
13EIF2AK394.5%5.5%
14LCK93.7%6.3%
15PKCMU_PRKD193.3%6.7%
16CSK92.7%7.3%
17TESK292.4%7.6%
18ALK6_BMPR1B92.3%7.7%
19PKCNU_PRKD392.3%7.7%
20NEK1192.1%7.9%

Selectivity landscape

MeasuredDerived

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

Atlas insights for Dabrafenib

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-target1%
Off-target99%
Ghost (2nd-order)0%
PathwayCompositionTotal |Π|
ADIPOGENESIS
2301.95
ALLOGRAFT_REJECTION
7055.57
ANDROGEN_RESPONSE
1227.80
ANGIOGENESIS
1120.76
APICAL_JUNCTION
6804.92
APICAL_SURFACE
742.50
APOPTOSIS
5770.86
BILE_ACID_METABOLISM
839.32
CHOLESTEROL_HOMEOSTASIS
915.35
COAGULATION
981.97
COMPLEMENT
4410.80
DNA_REPAIR
1670.25
E2F_TARGETS
5126.26
EPITHELIAL_MESENCHYMAL_TRANSITION
1674.75
ESTROGEN_RESPONSE_EARLY
3024.56
ESTROGEN_RESPONSE_LATE
2753.35
FATTY_ACID_METABOLISM
711.33
G2M_CHECKPOINT
4680.59
GLYCOLYSIS
2027.02
HEDGEHOG_SIGNALING
583.47
HEME_METABOLISM
2132.26
HYPOXIA
3476.73
IL2_STAT5_SIGNALING
2781.14
IL6_JAK_STAT3_SIGNALING
3434.31
INFLAMMATORY_RESPONSE
4250.12
INTERFERON_ALPHA_RESPONSE
857.88
INTERFERON_GAMMA_RESPONSE
4902.89
KRAS_SIGNALING_DN
852.05
KRAS_SIGNALING_UP
2673.41
MITOTIC_SPINDLE
5180.88
MTORC1_SIGNALING
3585.29
MYC_TARGETS_V1
3538.49
MYC_TARGETS_V2
816.01
MYOGENESIS
2490.79
NOTCH_SIGNALING
248.08
OXIDATIVE_PHOSPHORYLATION
1093.91
P53_PATHWAY
3722.74
PANCREAS_BETA_CELLS
487.15
PEROXISOME
837.52
PI3K_AKT_MTOR_SIGNALING
7662.41
PROTEIN_SECRETION
1534.06
REACTIVE_OXYGEN_SPECIES_PATHWAY
441.00
SPERMATOGENESIS
1506.16
TGF_BETA_SIGNALING
1718.97
TNFA_SIGNALING_VIA_NFKB
4020.69
UNFOLDED_PROTEIN_RESPONSE
1140.42
UV_RESPONSE_DN
4469.32
UV_RESPONSE_UP
3571.43
WNT_BETA_CATENIN_SIGNALING
1936.93
XENOBIOTIC_METABOLISM
1381.30

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 = 0.858

SampleCancer typecos to ideal
EPT0291EPN0.858
SRR233037520.839
TCGA-CF-A5U8-01A-11R-A28M-070.839
SRR122024980.834
aMVAC.P_005_TURBT_S2230.828

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