Navigating the Kinome Supplemental Accepted · (e.g., cdc7, nlk, bmx, and clk4 at the upper right) can be potently inhibited by 30-50% of the ... lck ros1 ntrk3 hipk4 stk3 csf1r mknk2

SUPPLEMENTRAY INFORMATION

Navigating the Kinome

James T. Metz, Eric F. Johnson, Niru B. Soni, Philip J. Merta, Lemma Kifle, Philip J. Hajduk*

Contents Methods Supplementary Table Descriptions Table S1. Supplementary Excel file containing pKI [-log10(KI)] values for 3858 compounds against 172 protein kinases. Table S2. Supplementary CSV file containing 112575 records for all pair-wise comparisons of 475 kinases from the human kinome. Supplementary Results Figure S1. Global kinase pharmacology interaction networks. Figure S2. Kinase promiscuity defined as the fraction of tested compounds that inhibited the kinase at a level of 1 uM or better (x-axis) versus 100 nM or better (y-axis). Figure S3. Dependence of compound promiscuity on physicochemical parameters. Figure S4. Dependence of various pharmacology associations on the parameters used in the calculations. Figure S5. Screenshot of the Pipeline Pilot protocol for calculating the pharmacology parameters from the provided data. Figure S6. High-res PDF of a global kinase pharmacology interaction network with kinases highlighted that were part of the profiling panel used in this work.

Nature Chemical Biology: doi:10.1038/nchembio.530

Methods In vitro kinase assays. Recombinant protein kinases were either commercially obtained or expressed using the FastBac bacculovirus expression system (GIBCO BRL, Gaithersburg, MD) and purified using either nickel (his-tag) or glutathione (GST) affinity chromatography (see table in supplemental material). Kinase assays were conducted in 24μl volumes on 384-well microplates using TECAN liquid-handling automation. Ser/Thr-kinase assays were performed using a radioactive FlashPlate-based assay platform (Luo Y, Smith RA, Guan R, et al. Pseudosubstrate peptides inhibit Akt and induce cell growth inhibition. Biochemistry 2004;43:1254–63.). In this format, biotinylated substrate peptide (2μM), γ-[33P]-ATP (5μM, 2mCi/μmol), inhibitors (3-10,000nM in 2% DMSO), and enzyme were incubated for 1hr in buffer containing 25mM Hepes pH 7.5, 1mM DTT, 10mM MgCl2 100μM Na3VO4, and 0.075mg/ml Triton X-100, stopped with 80μl stop buffer containing 100mM EDTA and 4M NaCl, transferred to streptavidin-coated 384-well FlashPlates (Perkin Elmer, Boston, Massachusetts) which were then washed 3 times and read using a TopCount microplate reader (Perkin Elmer). Tyr kinase reactions were performed using a time-resolved fluorescence (HTRF) platform. In this format, biotinylated substrate peptide (0.5μM), ATP (10μM-1mM), inhibitors (3-10,000nM in 2% DMSO), and enzyme were incubated for 1hr in buffer containing 50mM Hepes pH 7.4, 1mM DTT, 10mM MgCl2 2mM MnCl2, 100μM Na3VO4, and 0.01% BSA. Reactions were stopped with 50ul revelation buffer containing (final concentrations) of Eu-conjugated anti-pY-PT66-antibody (0.05ug/ml) (CisBio), PycolLink Streptaviding-APC (0.001ug/ml) (Prozyme), and 60mM EDTA in a buffer containing 25mM Hepes, pH 7.4, 250mM KF, 0.005% Tween-20, and 0.05% BSA. Following 60min incubation with revelation buffer, the reactions were read using an Envision fluorescence microplate reader (Perkin Elmer) with 615nm excitation and 665nm emission. Curating the activity data for inclusion in pharmacology calculations. Significant care was taken in curating the activity values and creating criteria for inclusion of data points. This is especially important as large numbers of compounds are inactive against many kinases, rendering the data uninformative from a pharmacology perspective. A compound was included in the pharmacology analysis of a given pair of kinases if the activity of that compound against the two kinases met either of the following criteria:

1. The compound exhibited a non-qualified (e.g, not “>” or “<”) activity value against both kinases 2. The compound was inactive against one kinase (e.g., pKI < 5.9) but the activity against the second

kinase was sufficiently high to establish at least a 10-fold window in selectivity (e.g., pKI = 7.1) The table below gives examples of compound activities against two kinases I and J and whether the compound would have been included in the pharmacology calculations for that pair.

pKI (Kinase I) PKI (Kinase J) Used? <5.9 <5.2 No <5.9 <7.0 No <5.9 6.2 No <5.9 7.1 Yes <5.9 8.0 Yes

Calculating kinase pharmacology parameters. All pharmacology parameters were calculated using only the subset of compounds tested against a given pair of kinases that pass the criteria listed above. Pij was calculated using a 10-fold potency window as described by Paolini [1], where the number of compounds exhibiting equivalent potency between the two kinases (as defined by a difference in pKI values of less than one log unit) was divided by the total number of compounds tested against the two kinases. The Pearson correlation coefficient (Rij) was simply derived from the two sets of activity data against the two kinases, again only using compounds that passed the criteria set out above. Vieth’s SAR Similarity value was calculated as described [2]. The Tanimoto similarity value (Tij) was also calculated as described [3], using a cut-off of 1 µM (pKI >= 6) for a compound to be considered active. Scaled Shannon Entropy. The two-dimensional Scaled Shannon Entropy was calculated by creating a 24 x 24 gridded histogram distribution of pKi values for the set of compounds tested against both kinases, using a scale from 4 to 10 and a bin size of 0.25 units. This creates 576 grid locations, and the fraction of


data points in each bin can be calculated. The Scaled Shannon Entropy was then calculated using the following equation [4]:

Npp

SSE i ii

2

2

loglog∑−=

Where pi is the fraction of pKI values in the ith grid location and N is the total number of bins (576 in this case).


Table S1. Supplementary CSV file containing pKI [-log10(KI)] values for 3858 compounds against 172 protein kinases. As these are pKI values, a value of 6 corresponds to a KI value of 1 µM, while a value of 7 corresponds to 100 nM. Column headings are as described in the text and defined below. The full table is provided as a separate CSV file. The subset of 1496 compounds for which the structure can be released have been deposited to PubChem with all associated kinase activity data. Cmpd_ID: Internal ID number PUBCHEM_SID: PubChem Substance ID value Canonical_Smiles: SMILES string for the compound (available for 1496 compounds) External_Cmpd_ID: External ID number of the compound exists in a public database External_Source: Source of the compound (if available) Cluster: Cluster number for the compound ClusterSize: Size of the cluster Cluster_MCSS: The SMILES string for the maximum common substructure across all cluster members Molecular_Weight: Molecular weight in Daltons AlogP: AlogP value as calculated in Pipeline Pilot Num_H_Acceptors: Number of hydrogen bond acceptors Num_H_Donors: Number of hydrogen bond donors tPSA: Topological polar surface area Promiscuity_1uM: Compound promiscuity defined as the number of kinases inhibited at 1 uM or better CDK7, etc..: Kinase name and associated pKi value Cmpd_ID Canonical_Smiles External_Cmpd_IDExternal_Source Cluster ClusterSize Cluster_MCSS

2407 [2H]C([2H])([2H])Oc1cccc(c1)[C@@H](C)NC(=O)c2sc(nc2C)c3ccncc3 55 2 O=C(NCc1ccccc1)c2cnc(s2)c3ccncc33769 [O-][N+](=O)c1ccc(NC(=O)N2CCc3[nH]c4c(Cl)cc(Cl)cc4c3C2)cc1 528 1 O=C(Nc1ccccc1)N2CCc3[nH]c4ccccc4c3C23349 [O-][N+](=O)c1ccc2[nH]c(nc2c1)c3occc3 MFCD02069085 ACD 252 1 o1cccc1c2nc3ccccc3[nH]23754 [O-][N+](=O)c1ccc2[nH]c3c(CC(=O)Nc4ccccc34)c2c1 MFCD02683579 ACD 513 1 O=C1Cc2c([nH]c3ccccc23)c4ccccc4N13518 [O-][N+](=O)c1ccc2N3C(=O)c4c(Br)cccc4N=C3C(=O)c2c1 340 1 O=C1N2C(=Nc3ccccc13)C(=O)c4ccccc24

Cmpd_ID Molecular_Weight ALogP Num_H_Acceptors Num_H_Donors tPSA Promiscuity_1uM CDK7 CDK8 CDK9 CHEK1 CLK2 CSF1R CSNK1A1 DAPK3

2407 356.41423 2.786 4 1 64.11 0.02 < 5.4 < 5.4 < 5.8 < 5.5 < 5.4 < 5.6 < 5.4 < 5.33769 405.23476 4.332 3 2 93.94 0.02 < 5.4 5.8 5.8 6 < 5.4 < 5.6 < 5.4 < 5.33349 229.19158 2.56 3 1 87.63 0 5.63754 293.27684 2.817 3 2 90.71 0.19 < 5.4 6.1 7.9 < 5.8 < 5.2 6 < 5.2 < 5.53518 372.12983 2.974 5 0 95.56 0.09 < 5.7 6.7 < 5.6


Table S2. Supplementary CSV file containing 112575 records for all pair-wise comparisons of 475 kinases from the human kinome. Column headings are as described in the text and defined below. The full table is provided as a separate CSV file. Kinase_Name_I: The Ith kinase in the pair Kinase_Name-J: The Jth kinase in the pair Ident_score: Sequence identity between the two kinases N_tested: Number of compounds with usable activity data against both kinases Equipotent_Sum: Number of compounds equipotent (ΔpKi < 1) against both kinases BothPotent_Sum: Number of compounds active (pKi > 6) against both kinases Hopkins_Pij: Hopkin’s Pij value for these two kinases based on the activity data Tij: Tanimoto similarity value of the activity data for these two kinases Pearson_R: Pearson correlation coefficient of the activity data for these two kinases SSE: Scaled Shannon Entropy of the activity data as described in the text Kinase_Name_I Kinase_Name_J ident_score N_tested Equipotent_Sum BothPotent_Sum Hopkins_Pij Tij Pearson_R SSECLK4 MAP4K4 0.225 1769 711 716 0.4 0.4 0.29 0.81GSK3B MAP4K4 0.231 1695 943 707 0.56 0.42 0.18 0.79CLK4 GSK3B 0.233 1574 612 691 0.39 0.44 0.29 0.81CLK4 PIM1 0.231 1508 329 312 0.22 0.21 0.24 0.71GSK3B PIM1 0.244 1477 730 433 0.49 0.29 0.19 0.74


Supplementary Results

Figure S1. Kinase promiscuity defined as the fraction of tested compounds that inhibited the kinase at a

level of 1 uM or better (x-axis) versus 100 nM or better (y-axis). Each kinase is labeled. Certain kinases

(e.g., CDC7, NLK, BMX, and CLK4 at the upper right) can be potently inhibited by 30-50% of the

compounds tested. In contrast, other kinases (e.g., BRAF at lower left) were potently inhibited by few if

any compounds.

Promiscuity_1uM

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 0.1 0.2 0.3 0.4 0.5

BRAF

MAPKA…

EEF2KDCAM…

MAPK…

AKT2

PRKCZ

CAMK1

MAPKAPK5

PAK1CDC2L6

PRKCI

TOPKAKT3MATK

AKT1

SRPK1

MAPK12

IKBKB

CAMK2B

PLK1

DYRK4

CHUK

MAPK…

PLK3

STK2…

GPRK5

SRMS

CAMK…

PTK2B

KIAA1811

MAPK… PHKG2ZAKTYK2ERBB4

NEK2

PRKG2CHEK1

PTK6

PIM2

CDC4…

INSRMAPK1

PRKCG

EPHA2 BTKIGF1R

NEK4

CSNK…

SGK

ERBB2

PTK2

PIM3

CAMK1D

MET

STK22DCSNK…

CAMK…

CSNK1G1

TAO1TYRO3

FES

PRKCD

CSNK1…

IRAK1

PAK4

PDPK1

CSNK…

NTRK1FGFR3

RPS6…

ITKMAPK9

IKBKE

PRKG1

LIMK1

IRAK4

ACK1

MARK2

SYK

NTRK2

PIM1

MAP2…

TBK1

ACVR1

CDC2

CAMK…

EGFR

MAPK8

PRKCQ

MARK3

JAK3

KITPRKD2

FGFR1CHEK2

SRCALK

CAMKK2CSNK1D

HCK

DYRK3

PRKAA1

MAP2K1

RPS6…

JAK2ABL1

MST1R

FYN

MAP3K10

LCK

ROS1

NTRK3

HIPK4

STK3

CSF1R

MKNK2

PRKXCDK5

RPS6K…

GSK3A

SLK

PRKCNPDGFRA

PRKACA

LYN

FER

FLT4MAPK10

MARK4

PKN2

MELK

PDGFRB

PLK4

DAPK3

MAP4K2

FRK

BLK

DYRK1A

FLT1CLK2

AXL

KDR

CDK2

ROCK1

STK6

LTK

MINK

DYRK1B

CDK8RET

GSK3B

FLT3

STK33

CDK7

WEE1MAP4K5

STK12

LRRK2STK17ACDK9

MAP4K4

HIPK2

RPS6KA4

SIK2

ROCK2

BMXNLK

CDC7

CLK4


Figure S2. Dependence of compound promiscuity on physicochemical parameters. (A) Molecular eight; (B) AlogP; (C) Polar surface area; (D) Number of hydrogen bond acceptors; (E) Number of hydrogen bond donors. Compound promiscuity is defined as the fraction of tested kinases for which that compound exhibited 1 uM or better potency. Very little dependence is observed for molecular weight, AlogP, and PSA, while compound with increasing numbers of hydrogen bond donors or acceptors appear progressively more promiscuous.

A.

B.

-0.10

0.10.20.30.40.50.60.70.80.9

1

x = 300.00 300.00 < x = 35... 350.00 < x = 40... 400.00 < x = 45... 450.00 < x = 50... 500.00 < xMedianCountMean

0.1 0.2 0.1 0.2 0.3 0.3576 748 901 663 486 4840.2 0.3 0.3 0.3 0.4 0.4

Binned Molec ular_W eight

Pro

mis

cu

ity

_1

uM

-0.10

0.10.20.30.40.50.60.70.80.9

1

x = 2.00 2.00 < x = 3.00 3.00 < x = 4.00 4.00 < x = 5.00 5.00 < xMedianCountMean

0.1 0.2 0.2 0.2 0.2721 994 1094 701 3480.3 0.3 0.3 0.3 0.3

Binned ALogP

Pro

mis

cu

ity

_1

uM

-0.10

0.10.20.30.40.50.60.70.80.9

1

x = 50.00 50.00 < x = 75.00 75.00 < x = 100.00 100.00 < x = 125.00 125.00 < xMedianCountMean

0.0 0.1 0.3 0.3 0.3253 1086 1467 832 2200.1 0.3 0.3 0.4 0.4

Binned tPSA

Pro

mis

cu

ity

_1

uM

-0.10

0.10.20.30.40.50.60.70.80.9

1

x = 1 1 < x = 2 2 < x = 3 3 < x = 4 4 < x = 5 5 < x = 6 6 < x = 7 7 < xMedianCountMean

0.0 0.1 0.1 0.2 0.2 0.2 0.3 0.433 255 616 978 870 527 312 2670.1 0.2 0.2 0.3 0.3 0.3 0.4 0.4

Binned Num_H_Ac c eptors

Pro

mis

cu

ity

_1

uM

-0.10

0.10.20.30.40.50.60.70.80.9

1

x = 0 0 < x = 1 1 < x = 2 2 < x = 3 3 < xMedianCountMean

0.0 0.1 0.2 0.3 0.588 758 1496 1111 4050.1 0.2 0.3 0.4 0.5

Binned Num_H_Donors

Pro

mis

cu

ity

_1

uM

C.

D.

E.


Figure S3. Global kinase pharmacology interaction networks. Net works were constructued based on (A)

sequence identity alone (requiring sequence identity ≥ 50%) or (B) either sequence identity (blue lines) or

pharmacology interactions (red lines, requiring either Pij ≥ 0.6, Rij ≥ 0.45, or Tij ≥ 0.55). Shown in (C) is

the nearest neighbor sub-network for KDR, showing both sequence and pharmacology relationships.

Network images were created using Cytoscape (http://cytoscape.org). Shown in (D) is the same view as in

(A) but with the kinases colored according to those experimentally interrogated as part of this work. For

clarity, singleton kinases with no edges (no connections to any other kinases using the criteria above) are

not shown in (A) and (B).

A. B.

C.


Figure S4. Dependence of various pharmacology associations on the parameters used in the calculations.

In all plots, data points are only shown for those kinase pairs whose scaled Shannon entropy (SSE) exceeds

0.4, as described in the text. The overall high degree of correlation observed with these changes suggests

that the network connectivity is not strongly dependent on the cut-offs used in the calculations.

(A) Dependence of the Hopkin’s Pij value using all available data (x-axis) vs only those data pairs where the pKi value of the compound is > 7 against at least one of the kinases. While there is s systematic decrease in the Pij values upon requiring more potent compounds, the values are highly correlated (R2 = 0.80). (B) Dependence of the Hopkins Pij value calculated using a 10-fold window (x-axis) vs a 30-fold window (y-axis) to define equipotency. While there is a systematic increase in the Pij values upon increasing the allowed potency window, the values are highly correlated (R2 = 0.86). (C) Dependence of the Pearson correlation coefficient (Rij) using all available data (x-axis) vs only those data pairs where the pKi value of the compound is > 7 against at least one of the kinases. While there is s systematic decrease in the Rij values upon requiring more potent compounds, the values are highly correlated (R2 = 0.77). (A) Dependence of the Tanimoto Tij value using all available data (x-axis) vs only those data pairs where the pKi value of the compound is > 7 against at least one of the kinases. While there is a slight increase in the Tij values upon requiring more potent compounds, the values are highly correlated (R2 = 0.80).

Hopkins_Pij

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

R2 = 0.80

Hopkins_Pij

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

R2 = 0.86

Pearson_R

-1

-0.5

0

0.5

1

-1 -0.5 0 0.5 1

R2 = 0.77

Tij

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

R2 = 0.88

A. B.

C. D.


Figure S5. Screenshot of the Pipeline Pilot protocol for calculating the pharmacology parameters from the provided data. The XML file is provided as a separate document.


CHEK1CHEK2

GUCY2F

PACE1

SK581

NLK

SCYL1

GUCY2D

PTK6

TLK1

CSK

KSR

MAPK4

INSRR

TLK2

MATK

IGF1R

MGC45428

SRMS

MYLK2

KSR2

MAST2

MAPK6

ACVR1

FLT3

PDGFRB

MYO3B

FGFR1

FGFR2

FGFR3

KIT_X_1T46_HU

PDGFRA

EPHB1

LCK

SK709

KIAA1804

GPRK7

MAP3K9

MYLK

HCK

GPRK6

EPHA7

EPHA4

GRK4

ERBB3

EPHB6

EPHB2

GRK1

EPHA8

EPHA5

EPHA3

EPHA2

TESK1

LATS1

OSR1

CAMKK2

KIAA1765

MAST3

CAMKK1

TESK2

DCAMKL1

PRKAA1

ROS1

MASTL MAPKAPK5

GUCY2C

PRKAA2

IRAK2

DKFZP434C131 CIT

RYK

BUB1BBUB1

FLJ25006HUNK

BMPR2ACK1

ILKIRAK1

VRK3

SLK

ACVR2

ERN1

NEK6

ERBB2

EGFR

MERTK

ERBB4

TYRO3

AXL

DAPK1DAPK3

DAPK2

STK39

LATS2

RNASEL PTK7 RAGE

MELK MGC4796MGC16169 MGC42105

PXK

DYRK4

DYRK2

NPR2

FES

ABL2

TIE

PHKG2PHKG1

TEK

ABL1

FER

NPR1

MAP3K11

DYRK3

EIF2AK3EIF2AK4CASK

KISLRRK1LOC91461

CCRK

IRAK4

TTBK1 TTBK2

CDC2L5 CRK7

SYK ZAP70

CDK4 CDK6CDK8

LIMK2

PRKCM

TRAD

CDC2L1

MAPK1

PRKCN

MAPK3

PIM3

MAPK8

MAPK9

NTRK1

NTRK3

CDKL4

MAPK11

MKNK2MKNK1

CSNK1A1L

CSNK1D

CSNK1E

CSNK1G3

CDKL3 MAPK14

CSNK1G2

CSNK1A1MARK4

SGKL

PIM1

SK690SNRK

PSKH2

STK11

PRKG1 PRKG2 PSKH1

SSTKSTK16

PRKR NEK11 MUSK NEK4 NEK2

MAPK13

MAPK12

MET

NEK3

SK558NEK1

MST1R

TBK1IKBKEMAKICK

TAOK3

TAOK1

RPS6KA6CT

LOC149420

STK32A

STK32BSTK32C

RPS6KA2CT

RPS6KA1CT

PRKACG

MAP2K2

SNARK ULK1

DYRK1B CDC2L6

TRIOVRK1

CDK10DDR2 DYRK1A

ULK2 VRK2

STK35

SRPK1SRPK2

PRKWNK4

STK23

LIMK1

RPS6KA5CTRPS6KA4CTROR2STK17BSTK17ASTK22D ROR1

FLJ32685

MAP3K8

CDKL5

MAPK7

CDK7 CDC7

MAP3K4

PIM2

MAPK10STK24

STK25

PRKD2

PRKWNK3

PRKWNK1

PRKWNK2

AKT3

RPS6KB2

AKT2

RPS6KA3CT

RPS6KB1

C9ORF96CAMK4CDK9

IRAK3KIAA2002MAP3K7 KIAA1639

TNK1 TEX14 STK36 STK33 STK31 STK22CSTYK1

PDPK1 PIK3R4 PINK1 PKMYT1 PLK4 PRPF4B

MARK3KIAA0999

CDKL1

MST4

SGK

KIAA0303

MAST1

SRC

LOC91807

FRK EPHA10

EPHB3

YES1

FGR

EPHA1

EPHA6

EPHB4

TXK

SGK2

TECBTK

GPRK5

BMX

AKT1

CDKL2

CAMK2GNTRK2

MAP3K10

SIK2MARK2

RPS6KA2

RPS6KA6

MARK1

RPS6KA5

SNF1LK

RPS6KA1

CSNK1G1

RPS6KA3HIPK2

HIPK4

RPS6KA4

MAP2K3

FLJ34389GAKGSG2

LYK5

APEG1 BMP2K

MAP3K1 MAP3K14

AMHR2

FLJ20574

MAP2K5

RIPK5

TGFBR2

STK22B

ARK5

STK4

CSNK2A2

TOPK

RIPK4 PASK

CAMK2B

RAF1

DDR1

LTK

PKA_X_1ATP_MO

BRAF

TAO1

MAP2K1

ARAF1

CAMK2D

MAP3K3

STK10

ZAK TTK TTN

ITK

PRKY

CLK2

CLK3

MAP2K6

LMTK2

HIPK3

PRKX

MAP2K4

LMTK3

HIPK1

PRKACB

PRKACA

AATK

MAP2K7

GSK3B

ADRBK2

MAP3K12NEK7

ERN2

WEE1

GSK3A

ADRBK1

MAP3K13

SK723

ACVR2B

CSNK2A1

ALK

STK3

TNNI3K

RIPK3

MAP3K2

CAMK1

CAMK1G

CAMK2A

CAMK1D

CLK4

AURKC

STK6

CLK1

STK12

ALS2CR2

FLJ23074

MGC8407

RIPK2

C14ORF20

FLJ23356

MOS

RIPK1

PAK7CDK5

CDK2

PAK1

PCTK2

PCTK3

PAK3

CDK3

ALS2CR7

PFTK1

PCTK1CDC2

PAK6JAK3PLK1

PAK2

PAK4

JAK2

JAK1

CDC42BPA

PLK2

PLK3

TYK2DMPK

PRKCD

PRKCA

PRKCB1

PRKCE

PRKCH

HSMDPKIN

CDC42BPB

PKN3

PKN1

PKN2

PRKCG

PRKCQ

LYN

RET

FGFR4

CSF1R

KIT

BLK

FYN

PRKCI ROCK2

ROCK1

PRKCZ

ERK8

HRI

SK592

PTK2B

STK38L

IKBKB

STK29

MAPKAPK3

ACVR1B

MAP4K2

INSR

MAP4K3

LOC340371

NEK9

SK650

CHUK

KIAA1811

MAP3K6

STK38

MAPKAPK2

FLJ10074

MAP4K5

PTK2

BMPR1B

MAP4K1

NEK8

FLT1

MAP3K5

SK681

MINK

BMPR1A

ACVR1C

ACVRL1

TNIK

TGFBR1

KDR

NRK

MAP4K4

FLT4

MYO3A


HAJDUPJ

Text Box

Figure S6. Global kinase pharmacology interaction network based on sequence identity alone (>50% identity required for a connection) and highlighting in green those kinases used in the profiling panel.

References 1 Paolini, G.V., Shapland, R.H., van Hoorn, W.P., Mason, J.S. and Hopkins, A.L. (2006) Global

mapping of pharmacological space. Nat Biotechnol 24 (7), 805-815 2 Vieth, M., Higgs, R.E., Robertson, D.H., Shapiro, M., Gragg, E.A. and Hemmerle, H. (2004)

Kinomics-structural biology and chemogenomics of kinase inhibitors and targets. Biochim Biophys Acta 1697 (1-2), 243-257

3 Bamborough, P., Drewry, D., Harper, G., Smith, G.K. and Schneider, K. (2008) Assessment of chemical coverage of kinome space and its implications for kinase drug discovery. J Med Chem 51 (24), 7898-7914

4 Godden, J.W. and Bajorath, J. (2000) Shannon entropy--a novel concept in molecular descriptor and diversity analysis. J Mol Graph Model 18 (1), 73-76


Documents

Navigating the Kinome Supplemental Accepted · (e.g., cdc7, nlk, bmx, and clk4 at the upper right) can be potently inhibited by 30-50% of the ... lck ros1 ntrk3 hipk4 stk3 csf1r mknk2