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

Primary targets: ALK · FDA status: FDA Approved

Selectivity scorecard

MeasuredDerived
KISS
97.24
Gini
0.694
CATDS
0.018

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 Lorlatinib. Strongest target: ROS_ROS1 at 99.5% inhibition.

Accessible data table
RankTargetInhibition %Residual activity %
1ROS_ROS199.5%0.5%
2ACK199.3%0.7%
3FER98.1%1.9%
4FAK_PTK297.7%2.3%
5PYK297.6%2.4%
6ALK97.2%2.8%
7TYK1_LTK93.8%6.2%
8FES_FPS93.7%6.3%
9GRK792.0%8.0%
10TRKC91.3%8.7%
11TRKB90.5%9.5%
12PHKG288.5%11.5%
13TNK187.9%12.1%
14STK22D_TSSK186.4%13.6%
15NEK881.2%18.8%
16PLK4_SAK80.6%19.4%
17FRK_PTK580.0%20.0%
18CAMKK279.2%20.8%
19DCAMKL177.5%22.5%
20SLK_STK273.0%27.0%

Selectivity landscape

MeasuredDerived

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

Atlas insights for Lorlatinib

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
1038.34
ALLOGRAFT_REJECTION
3752.33
ANDROGEN_RESPONSE
1049.52
ANGIOGENESIS
703.40
APICAL_JUNCTION
3746.83
APICAL_SURFACE
338.91
APOPTOSIS
2847.01
BILE_ACID_METABOLISM
338.15
CHOLESTEROL_HOMEOSTASIS
479.91
COAGULATION
487.61
COMPLEMENT
2129.23
DNA_REPAIR
681.21
E2F_TARGETS
2137.26
EPITHELIAL_MESENCHYMAL_TRANSITION
840.15
ESTROGEN_RESPONSE_EARLY
1532.39
ESTROGEN_RESPONSE_LATE
1206.29
FATTY_ACID_METABOLISM
261.45
G2M_CHECKPOINT
1689.63
GLYCOLYSIS
1481.40
HEDGEHOG_SIGNALING
443.04
HEME_METABOLISM
744.37
HYPOXIA
1843.91
IL2_STAT5_SIGNALING
1274.84
IL6_JAK_STAT3_SIGNALING
2161.80
INFLAMMATORY_RESPONSE
2264.27
INTERFERON_ALPHA_RESPONSE
306.57
INTERFERON_GAMMA_RESPONSE
2622.01
KRAS_SIGNALING_DN
547.54
KRAS_SIGNALING_UP
1382.39
MITOTIC_SPINDLE
2429.67
MTORC1_SIGNALING
1724.76
MYC_TARGETS_V1
1421.13
MYC_TARGETS_V2
463.05
MYOGENESIS
1408.93
NOTCH_SIGNALING
181.81
OXIDATIVE_PHOSPHORYLATION
336.31
P53_PATHWAY
1336.41
PANCREAS_BETA_CELLS
111.07
PEROXISOME
334.05
PI3K_AKT_MTOR_SIGNALING
3646.44
PROTEIN_SECRETION
924.55
REACTIVE_OXYGEN_SPECIES_PATHWAY
128.32
SPERMATOGENESIS
779.84
TGF_BETA_SIGNALING
708.41
TNFA_SIGNALING_VIA_NFKB
1725.03
UNFOLDED_PROTEIN_RESPONSE
701.66
UV_RESPONSE_DN
1767.05
UV_RESPONSE_UP
1566.79
WNT_BETA_CATENIN_SIGNALING
869.65
XENOBIOTIC_METABOLISM
867.94

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 = 3.10 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 = 0.847

SampleCancer typecos to ideal
EPT0291EPN0.847
TCGA-CF-A5U8-01A-11R-A28M-070.837
SRR233037520.836
TCGA-FD-A43X-01A-11R-A23W-070.825
C3N-034200.824

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