1. Introduction

2. The current state of protein

kinase R&D

3. Inhibitor profiling

4. The challenge of target

selection: what makes a good

kinase inhibition profile?

5. Conclusion

6. Expert opinion: kinase

system-based research

Review

System-based drug discoverywithin the human kinomePaul BamboroughComputational and Structural Chemistry, Molecular Discovery Research, GlaxoSmithKline

Medicines Research Centre, Stevenage, UK

Introduction: For well over a decade, significant effort has been devoted to

the search for inhibitors of the human protein kinase family. This is increas-

ingly translating into success in the clinic, with five new kinase inhibitor drugs

approved since 2011. However, despite encouraging signs in other areas,

success has been largely restricted to oncology.

Areas covered: This article reviews the prospects for kinase inhibitor drug dis-

covery in oncology and other therapeutic areas. Major topics include the

application of kinome profiling and lessons learned from kinase system-

based research. With these fields nearing maturity, the validation of kinases

as targets or their classification as liabilities is becoming increasingly perti-

nent. Other topics include a discussion of the properties required of good

small molecule kinase probes.

Expert opinion: The tractability of protein kinases to small molecule discov-

ery through system-based research is excellent, and adequate selectivity

can often be achieved. With advances in screening methodology now

enabling compound profiling across most of the kinome, researchers

involved in drug discovery must decide what inhibition profiles are desir-

able. However, this assessment must be made on the basis of incomplete

understanding of the disease biology of most kinases, and as a result

there is a significant risk that drugs entering clinical trials will lack efficacy.

Because of this, as well as greater effort to determine which kinases are

therapeutically relevant for particular diseases, opportunities for quality

pre-candidate compounds developed for specific indications to find alter-

native uses should be maximised by early screening through panels of

phenotypic assays.

Keywords: kinase drug discovery, kinome profiling, system-based research

Expert Opin. Drug Discov. [Early Online]

1. Introduction

Protein kinases were among the most actively studied families of pharmaceuticaltargets even prior to the publication of the full catalogue of the human kinomein 2002 [1]. In 2005, it was estimated that around one in three early drug dis-covery efforts targeted protein kinases [2]. Several years on, this has translatedinto regulatory approval of 15 small-molecule kinase inhibitor drugs, five ofwhich have been approved for the treatment of cancers since the beginning of2011. A recent review concluded that the attrition rate of kinase anticancer com-pounds in the clinic is lower than that of non-kinase compounds, particularlyduring the high-risk Phase II [3]. In contrast to this story of success, only onekinase inhibitor has yet been approved for use outside oncology. This reviewwill begin by summarising compounds currently approved for cancer, beforediscussing activity in other areas and possible reasons why these have beenless fruitful.

10.1517/17460441.2012.724056 © 2012 Informa UK, Ltd. ISSN 1746-0441 1All rights reserved: reproduction in whole or in part not permitted

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2. The current state of protein kinase R&D

Although it is difficult to judge the extent of current activity,one of the best estimators of recent R&D effort is the numberof small-molecule patents filed. A survey of kinase publicationsand patents noted a decline in number between 2006 and2009 [4]. This might suggest that research is moving intoother areas, although it could also signify changes in patentingstrategy, or that it is becoming harder to differentiate novelcompounds from prior art. A comprehensive investigation isbeyond the scope of this review, but a simple analysis of patentscontained within a large commercial database provides inter-esting statistics. Although the number of kinase-targetedpatents declined from 2009 onwards, this was mirrored by awholesale decrease in small molecule-containing patents acrossall target classes (Figure 1A). The decrease in published patentsin 2010 is larger than the 4.8% fall in international PCT patentfilings in 2009 attributed to the global recession [5]. It is tempt-ing to speculate that this could be a consequence of industrialreorganisation and resizing, a switch of priorities away fromsmall molecules towards biologicals, or into novel areas ofresearch that have not yet delivered patentable molecules on a

significant scale [6,7]. Normalising for this patent decline,Figure 1B suggests that as a proportion of small-moleculepharmaceutical activity, early-stage commercial sector kinaseresearch remained stable at about 20% of the total effort at leastup to about 2010.

Not all protein kinases have received equal treatment.Figure 2 shows that certain tyrosine kinases, CMGC kinasesand AGC kinases have been intensively studied. By contrast,there are sub-branches of the kinome tree for which small-molecule inhibitor data is completely absent, apart from thatarising from cross-kinase profiling efforts. Naturally, thosewith good therapeutic target validation have received farmore attention than others, and the distribution mirrors thebody of literature describing the functions of these kinases,of which ~50% are said to be largely uncharacterised [4].Many kinases still have unknown function, still fewer diseasevalidation, and as a result there has been little incentive toseek to develop inhibitors.

2.1 Approved kinase inhibitorsThe intended targets of the 15 approved drugs (Figure 3,Table 1) follow the same trends as the literature. All but onewere originally developed as inhibitors of tyrosine or tyro-sine-kinase-like protein kinases, as far as it is possible to tellfrom the published stories of their discovery. However, thetrue profile of kinase inhibition even of these compounds issometimes different to that probably originally intended [8].The compounds range from those considered highly selective,such as lapatinib, which only targets EGFR and ErbB2, tothose inhibiting multiple targets such as sunitinib. Anotherremarkable point is that all are approved for oncology indica-tions, with the exception of fasudil, which is approved in Japanfor the treatment of stroke. The molecular targets of this com-pound were determined after its discovery, and include ROCKas well as other AGC family kinases [9,10], making this the onlyknown marketed inhibitor of this branch of the kinometo date.

2.2 Kinase inhibitors for oncologyThe emphasis on cancer therapeutics (Table 1) reflects thefocus on these diseases within R&D institutions. Kinasesunder investigation are biased towards those already validatedas targets, as investigators attempt to improve upon first-in-class drugs (Figure 2). However, many new targets are alsobeing pursued for cancer. One important development camewith recent FDA draft guidelines for the efficient use of com-panion diagnostic tools alongside targeted drugs [11]. Shortlyafterwards, vemurafenib and crizotinib were approved alongwith diagnostic kits for relevant BRAF and ALK mutationsand fusions. The continuing development of ‘personalisedmedicine’ seems likely to accelerate the rate of approval ofnew kinase-targeted cancer therapies [12,13]. However, drugresistance remains a serious challenge [14]. When this arisesfrom mutation of the target kinase [15,16], it can be combatedby multi-drug therapy, if existing compounds inhibit the

Article highlights.

. Protein kinases have demonstrated tractability astherapeutic targets, as evidenced by a total of15 approved drugs. However, only one of these isoutside the oncology field. Success in other areas hasoften been limited by lack of efficacy, due to poortarget selection arising from incompletebiological knowledge.

. Kinase inhibitor profiling now provides insights intocompound selectivity and the relationships betweenkinases. It will also be valuable for the interpretation ofpreclinical and clinical toxicity data.

. The system-based approach enables the efficientproduction of inhibitors with defined kinase profiles.However, in many cases given the current limited stateof biological understanding, the ideal profile cannot bedefined with certainty.

. Validation of kinases as disease targets can be advancedusing high-quality chemical probes, but producing suchmolecules from screening hits can require significanteffort. A combination of data from multiple chemicaland biological approaches is usually needed, and thismay be slow to generate.

. Phenotypic screening is a valuable complement to thereductionist target approach, but there remains a needto develop assays and models that are genuinelypredictive of complex diseases.

. For greater efficiency, kinase inhibitors should beprofiled through in vitro assays, but also phenotypicscreens targeting multiple diseases in parallel. Thisshould be done with quality probes at preclinical stagesin the discovery process, rather than waiting toreposition drugs after they fail in clinical trials.

This box summarises key points contained in the article.

P. Bamborough

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mutant form. Alternatively, compounds can be designed toinhibit multiple commonly mutated forms, as, for example,nilotinib and dasatinib for imatinib resistance [17,18]. Resis-tance may also arise through other mechanisms, such as acti-vation of kinases elsewhere on the same or differentpathways [19,20]. In such situations, compounds with targetedpolypharmacology offer one approach to reduce the potentialfor resistance [21]. This approach has been the focus for inhib-itors targeting multiple positions in the PI3K/mTORpathway [22-24], and several such compounds are in clinicaldevelopment including NVP-BEZ235, NVP-BGT266,PF-04691502 and GSC-0980 [25-28].

2.3 Kinase inhibitor development for other diseases,

and what has limited itConsiderable effort has also been expended in other areas,notably for chronic diseases such as inflammatory disor-ders [29], with less benefit for patients. Kinase inhibitors forsuch conditions should not suffer from problems of emergingresistance, yet significant challenges remain. The main limit-ing factor has been a persistent concern over the risk of seriousside effects that may be less acceptable in chronic illness wheredosing is anticipated over a longer period. All medicines maysuffer target-related toxicity, but due to the size of the genefamily, their conserved fold and ATP-binding site targetedby most inhibitors, and the consequent well-established likeli-hood of inhibitor cross-activity, protein kinase inhibitorscarry additional risks of unintended off-target effects. Thedecision to focus on targets including the tyrosine kinases,which have especially closely related homologues, may haveamplified the difficulty of achieving selectivity [30].A secondary factor in chronic diseases is that patient adher-ence over a longer period may be required, so physico-chemical properties permitting oral, once or twice-dailydosing is more important. As shown in Table 1, many first-generation kinase inhibitors are larger than average for oraldrugs (which have an average molecular weight of 337 [31]).They are also more lipophilic [32]. Such molecules generally

have poorer pharmacokinetic properties [33] that could limitthe potential for chronic disease treatment. The aromaticnature of ATP-mimetic parts of kinase inhibitors tends tomake them lipophilic, so solubilising polar groups are added,increasing their molecular weight. Bulky modificationsneeded for selectivity also govern the size and lipophilicityof the largest approved molecules. For example, the benzyloxygroup of lapatinib induces an alternative conformation in theC-helix of its EGFR target, contributing to its potency andselectivity over related anilinoquinazoline inhibitors lackingthis group [34]. Similarly, the diaryl amide and urea groupsof imatinib, nilotinib and sorafenib are required because theseselect a ‘DFG-loop out’ conformation of their target kinases,which largely determines their selectivity profile [35-37]. Per-haps to succeed for chronic diseases, kinase inhibitors needto be smaller and more typically drug-like than some of theoncology compounds, while still remaining relatively selec-tive. Fortunately, this does seem to be achievable, and themore recently approved cancer compounds fall within typicaldrug-like property space. Indeed, protein kinases have beenshown to be highly tractable to fragment-based screening, inwhich weak but efficiently binding low-MW compounds arefavoured over larger but less attractive starting points [38-41].With careful optimisation, the resulting molecules areexpected to suffer lower rates of clinical attrition.

Figure 4 and Table 2 show a small selection of some late-stage development compounds for inflammation. Histori-cally, rheumatoid arthritis (RA) has been one of the mostintensively studied chronic diseases targeted with kinaseinhibitors. The first and most intensively studied target wasp38 MAP kinase (strictly the alpha isoform, although mostcompounds are dual alpha/beta inhibitors with excellent selec-tivity over gamma and delta). Following serial preclinical andclinical failures, it seems that only BMS-582949 remains intrials for this indication [42,43]. Early failures were attributableto preclinical toxicity of a few closely related chemical serieswith incompletely determined selectivity profiles. Theseincluded pyridinyl imidazoles of the SB-203580 class, which

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Figure 1. A. WO patents by year for kinases and non-kinases 1997 -- 2010. B. Percentage of small-molecule patents per year

targeting kinases, for WO and for combined WO, US and EU patents. Source: GVK Bio database [123], recently reviewed and

compared to public databases by researchers at AstraZeneca [124].

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were thought to be selective for p38 but are now known toinhibit JNKs and other kinases [8]. Genuinely selective inhib-itors such as VX-702, pamapimod and Scio-469 enteringPhase II trials were relatively well-tolerated [44-46], but thecompounds were not pursued due to an unexpected time-dependent loss of effect on inflammatory biomarkers. Thissuggests that after prolonged p38 inhibition an unknown

escape mechanism engages in the RA disease process. Someconsequences of this for drug discovery will be discussed inSection 4.4.

Although p38 inhibitors continue to progress for otherindications [47], alternative kinase targets have come to thefore for RA and inflammation. The JAK inhibitor tofacitinibis most advanced in Phase III trials, and seems likely to be

Figure 2. The distribution of compounds with protein kinase screening data published in journal and patent literature.

Source: AurScope database, Aureus Pharma [125]. Kinome illustration reproduced courtesy of Cell Signaling Technology, Inc.

(www.cellsignal.com).

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HN

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Axitinib Crizotinib Dasatinib Erlotinib

Gefitinib

Pazopanib

Vandetanib Vemurafenib Fasudil

Ruxolitinib

Sorafenib Sunitinib

Imatinib Lapatinib Nilotinib

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Figure 3. Approved kinase inhibitor drugs (June 2012).

Table 1. Approved kinase inhibitor drugs, manufacturer, indication, intended molecular targets and parent

molecular weight.

Name Manufacturer Approved for Intended target(s) MW

Axitinib [129] Pfizer RCC VEGFR, PDGFR, KIT 386Crizotinib [130] Pfizer NSCLC ALK/c-Met 450Dasatinib [131] Bristol-Myers Squibb CML, ALL Abl/Src family 488Erlotinib [132] Genentech/Roche NSCLC, pancreatic cancer EGFR 393Gefitinib [133] AstraZeneca NSCLC EGFR 447Imatinib [35] Novartis CML, ALL, MDS/MPD, ASM, HES, CEL, DFSP, GIST Abl, KIT, PDGFR 494Lapatinib [34] GlaxoSmithKline Breast cancer EGFR, ErbB2 581Nilotinib [36] Novartis CML Abl 530Pazopanib [134] GlaxoSmithKline Renal cell carcinoma VEGFR 438Ruxolitinib [135] Incyte/Novartis Myelofibrosis JAK 306Sorafenib [37] Bayer/Onyx Hepato/renal cell carcinoma Raf 465Sunitinib [136] Pfizer GIST, renal cell carcinoma VEGFR, PDGFR, FLT3, KIT 398Vandetanib [137] AstraZeneca Medullary thyroid cancer RET, VEGFR, EGFR 475Vemurafenib [138] Plexxikon/Hoffman-La Roche Melanoma B-Raf 490Fasudil [139] Asahi Cerebral vasospasm (Japan) ROCK 291

This table excludes antibodies targeting kinases, and macrocycles such as sirolimus (rapamycin) and related allosteric inhibitors of mTor [126]. Pirfenidone, a

treatment for idiopathic pulmonary fibrosis, has been reported to act through p38-gamma inhibition [127], but this seems unlikely as its reported IC50 against this

target is only 4 mM [128].

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approved later this year [48-50]. Ruxolitinib, another JAKinhibitor recently approved for myelofibrosis (Table 1) isalso in development for RA and psoriasis, as are inhibitorsof SYK, another tyrosine kinase [51]. It seems likely that kin-ases on other phylogenetic branches could also impact chronicdiseases, such as IKKb [52], MK2 [53], mTOR [54] and thephosphoinositide-3-kinases [55]. With fewer close homologuesthan most tyrosine kinases, achieving greater selectivityfor these may prove simpler, with beneficial consequencesfor safety provided the biology of the target allows for atherapeutic window.

3. Inhibitor profiling

An important change in the kinase drug discovery landscapehas been the arrival of technologies permitting the profilingof compounds against a significant proportion of human kin-ases. These approaches have some limitations. One is that as a

trade-off for higher throughput, kinases are usually screenedin vitro as truncated domains, removed from their cellularintra- and inter-molecular context [56]. The expression systemsmay or may not produce kinases in disease-relevant states ofmodification, complexation and activation, which areexpected to be important, although the frequency with whichthis makes a practical difference is currently not widely dem-onstrated. In a drug-discovery setting, hits discovered usingsuch assays require subsequent testing and sometimes optimi-sation to attain potency in more realistic systems. Readersinterested in a detailed discussion of these technologiesare directed to a recent review in this journal [57]: here,conclusions relevant to drug discovery will be emphasised.

A summary of kinase profiling publications is shownin Table 3. Researchers at the University of Dundee wereamong the first to publish kinase profiling data in order tohighlight differences between the reported and actual selec-tivity of commonly used kinase inhibitors [9,58,59]. Cell-

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Dilmapimod BMS-582949 Tofacitinib Fostamatinib

Pamapimod PH-797804 Losmapimod

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Figure 4. Selected kinase inhibitors in clinical trials for inflammation-related diseases.

Table 2. Selected inhibitors currently in Phase II/III clinical trials for treatment of inflammation-related diseases,

their manufacturer, indication, intended molecular targets and molecular weight.

Name Manufacturer Phase Intended target(s) MW

VX-702 [44] Vertex Ph II for RA, discontinued p38 404Pamapimod [140] Pfizer Ph II for RA, discontinued p38 406PH-797804 [141] Pfizer Ph II for COPD, neuropathic pain p38 477GW856553/losmapimod [142] GlaxoSmithKline Ph II for COPD, ACS p38 383SB-681323/dilmapimod [143] GlaxoSmithKline Ph II for ARDS, ALI p38 456BMS-582949 [144] Bristol-Myers Squibb Ph II for RA, atherosclerosis, psoriasis p38 406CP-690,550/tofacitinib [145] Pfizer Ph III for RA, psoriasis JAK 312R935788/fostamatinib [51] Rigel/AstraZeneca Ph III for RA SYK 580*

*Phosphate pro-drug.

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permeable compounds can be valuable tools to dissect thefunction of individual kinases because of their inducibleaction, their utility across many different cell types andbecause they disturb only the catalytic function of the target.Unfortunately, this is often complicated by lack of apprecia-tion of the true selectivity of commonly used inhibitors,some of which are used to assign cellular functions to individ-ual kinases despite having been shown to be unsuitable for thistask years earlier. It is disappointing that recommendationsmade in these papers to discontinue use of some tools andto use others in combination are still not always followed.

In 2005, researchers at Ambit Biosciences (now DiscoveRx)reported an efficient method to determine kinase binding [60].Compared to biochemical assays measuring catalytic phos-phorylation of a substrate, competition for binding betweenimmobilised ligands and bacterially expressed phage-tagged truncated kinase domains is a step removed from thecellular context [56], but this enabled compounds to be screenedagainst 119 kinase domains, a greater number than previouslypossible. The discussion within the first paper focused mainlyupon alternative targets of compounds in clinical development,but subsequent publications described results from largercompound sets against up to 442 kinases [8,61]. At least twoindustrial groups have also used this methodology to profilelarger corporate compound sets [30,62]. A recent study reportedgenerally good agreement between results from this compe-tition binding format and a catalytic activity radiometricassay [63].

Besides activity-based biochemical assays and competitionbinding assays, other techniques have been used to profile kin-ases. Researchers at the Structural Genomics Consortiummeasured the thermal stability change induced upon com-pound binding to 60 serine/threonine kinases [64], linkingthe hit frequency in this assay to the ‘druggability’ of thetarget. In another competition displacement approach, a

split-luciferase format using staurosporine (a poorly selectiveATP-site kinase inhibitor) linked to the Jun peptide wasused to screen 27 AGC-family kinases [10].

Profiling panels now include mutant protein kinases impor-tant in cancer or drug resistance. Studies using these panelshave identified compounds that bind to disease mutants inaddition to their previously known activities, suggesting alter-native uses for existing inhibitors in cancer therapy [61]. Non-human kinome screens are also becoming increasingly availableand data is beginning to emerge. For example, 80 compoundswere screened against 14 microbial antibiotic resistance kin-ases [65]. Some showed the ability to partially attenuate resis-tance, suggesting that co-administration of appropriate kinaseinhibitors alongside antibiotics may be a useful strategy.

Although all these data sets are of great value in assessingthe activities of individual compounds, the studies includingthe greatest number of kinases and statistically significantnumbers of compounds were able to carry out more generalanalyses. These may be divided into those focusing on com-pounds, and those focusing on kinases, which will be brieflydiscussed in turn.

3.1 Analysis of compound selectivity profilesIn the drug discovery setting, medicinal chemists usually focuson those off-target kinases believed to be most important,using dose--response data to quantify selectivity windows.For the larger data sets in Table 3, measurement of dos-e--response data was impractical, so inhibition was determinedinitially at only one or two compound concentrations, varyingfrom study to study. There have been several attempts todefine a single number, the selectivity score, of compoundsbased upon single-concentration data. The simplest is the pro-portion of kinases inhibited at a given percentage inhibitionthreshold [8]. Other metrics have been proposed to avoid theneed for a fixed activity cutoff [66,67], although much of the

Table 3. Human kinase cross-screening publications, compound data set composition, assay format and compound

screening concentration.

Authors Kinases Compounds Assay type Measurement

Davies et al., 2000 [9] 28 24 commercially available reported tools Biochemical inhibition %I at 1 -- 50 µMBain et al., 2003 [58] 28 14 commercially available reported tools Biochemical inhibition %I at 10 -- 100 µMFabian et al., 2005 [60] 119 20 literature compounds Competition binding %I at 10 µMBain et al., 2007 [59] 70 -- 80 65 commercially available reported tools Biochemical inhibition %I at 1 -- 25 µMKaraman et al., 2008 [8] 317 38 literature compounds Competition binding %I at 10 µMFederov et al., 2008 [64] 60 156 literature compounds Thermal stabilisation Tm (�C)Bamborough et al., 2008 [30] 203 577 diverse lead-like compounds Competition binding %I at 10 µMOlaharski et al., 2009 [72] 290 113 diverse compounds Competition binding %I at 10 µMPosy et al., 2010 [62] 317 -- 402 21,851 compounds including analogues Competition binding %I at 1 µMOlaharski et al., 2010 [73] 317 48 diverse compounds Competition binding %I at 10 µMMetz et al., 2011 [68] 172 3800 (historical data analysis) Biochemical inhibition IC50

Bamborough et al., 2011 [41] 30 936 fragments Biochemical or binding %I at 400 -- 667 µMMiduturu et al., 2011 [120] 353 118 compounds from two scaffolds Competition binding %I at 10 µMAnastassiadis et al., 2011 [63] 300 178 commercially available compounds Biochemical inhibition %I at 500 nMDavis et al., 2011 [61] 442 72 literature compounds Competition binding %I at 10 µMJester et al., 2012 [10] 27 80 commercially available compounds Competition binding %I at 10 µM

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benefit is negated by the need to choose a single screeningconcentration, and the noise from inactive responses cansignificantly affect the score for more selective compounds.Generally, selectivity scores are most useful in large-scaledata analysis, for example, in seeking relationships betweenselectivity and molecular properties. Two studies found aninverse relationship between the number of hydrogen-bond donors in compounds and their selectivity, possiblydue to interactions with conserved residues within the ATPsite [62,68]. Others have used kinase selectivity profiles to definethe activity-based similarity between pairs of compounds.Comparison of these to structural similarity metrics showedthe expected trend between compound similarity and inhibi-tion profiles [30,62]. Within chemical series as defined bytheir hinge-binding group, substituents also greatly influencewhich kinases are targeted [62]. Results such as these provideuseful information to guide the design of kinase-targetedscreening collections.

3.2 Analysis of kinase selectivity profilesSequence analysis and protein crystallography have greatlyhelped in the search for selective kinase inhibitors. Screeningdata provides additional insights into the relationshipsbetween kinases useful in this respect [69]. Analysis of profiledata can guide the rational selection of targets and key selec-tivity assays [30]. One important piece of information com-mented upon in most studies is the hit-rate for each kinase,which contains information about their druggability, at leastwithin the chemical space defined by the compound set.Unfortunately, comparison is hindered by the fact that aswell as the compound set composition, the hit-rate alsodepends upon the screening concentration and assay format.Where different compound sets were compared using thesame assay format, encouraging similarity was reported inkinase hit-rates [62].Profiling data is also used to estimate another important

consideration in target selection, the likelihood that selectivitycan be achieved between the target and other kinases. The firstattempt to relate kinases to one another pre-dated broad pro-filing platforms so used a relatively small compound set [70],yet many of its conclusions still seem valid [30,62]. Similar kin-ases usually have similar compound-binding profiles, so co-inhibition usually occurs between close neighbours on thesame branch of the phylogenetic tree. Less predictably, com-pounds inhibit clusters of distantly related kinases. Evenmore rarely, pairs of kinases which are only distantly relatedshow a preference for binding the same compounds, althoughit remains to be seen how robust some of these findings are tochanges in the assay format and compound selection.These data suggest that gross differences between distant

kinases are relatively easy to exploit, but that subtle differencesbetween closely related kinases are not taken advantage of bymost compounds in the screening sets. Medicinal chemistsfrequently report targeting single amino acid differenceswithin kinase-active sites to great effect, but it is difficult to

know how often this is attempted without success. It is verylikely that careful design can achieve greater selectivity thanthe profiling data suggests, but profile analysis indicates howdifficult this is likely to be for a particular pair of kinases.Interestingly, crude measures of ATP-site similarity are notmuch better than kinase domain similarity at predicting co-inhibition of kinases [10], highlighting the dominant influenceof global as well as local structural differences as determinantsof inhibitor selectivity.

Profiling data should also be of value for predictive toxicol-ogy, although relatively little has been published so far in thisarea. Rather than using empirical data, current predictions ofkinase-driven toxicity mostly extrapolate from their knownroles in biological pathways: for example, see a recent reviewon cardiotoxicity [71]. In a first attempt to utilise kinase inhi-bition profiling in predictive toxicology, in vitromicronucleustest genotoxic activity was correlated with the profiles of a setof compounds, leading to the identification of 21 kinases pre-dictive of MNT activity [72]. A second publication attemptedto rationalise in vivo bone marrow toxicity through kinaseinhibition profiles [73]. About half of human protein kinaseswere assayed. In both studies, the toxic compounds appearedto be among the least selective compounds profiled, so someof the identified liabilities may be markers or surrogates forother kinases not present in the panel rather than the causeof the toxicity. Computational prediction will not replaceexperimental testing for safety, but this work illustrates howit may become possible to give earlier warning of potentialtoxicities, or to steer medicinal chemistry design away fromriskier kinase profiles.

Similar approaches to toxicity prediction would beenhanced by linking information from failed clinical trials tothe kinase profile [74]. Unfortunately, this data is sparse andoften inaccessible. Improved access to preclinical toxicologydata, a goal of consortia such as the European Union Innova-tive Medicines Initiative [75], will hopefully help to realisethis ambition.

3.3 Limitations of current compound setsKinase profiling data depends upon both the screening con-centration and composition of the compound set, whichmust be of sufficient size, diversity and quality to ensurethat the results are meaningful. The studies with the largestand most diverse compound sets should yield the most gener-ally applicable conclusions, and to date these have been drawnfrom corporate collections. Full profiling data were madeavailable, enabling analysis of the kinase inhibition profiles,but chemical structures could not be disclosed. There remainsa need for greater availability of well-validated sets of diversekinase compounds with confirmed modes of action forprofiling activities. Roche and GlaxoSmithKline are makingpublished kinase inhibitor sets available to attempt to addressthis gap [76].

Most profiling studies did not have access to such extensivecompound sets, so used commercially available panels,

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containing drugs and late-stage development inhibitors sup-plemented by literature compounds. Unfortunately, the lattermay not always be well characterised. Reports of compoundactivity can prove impossible to reproduce [77], and are ofteninsufficiently characterised to be able to exclude artefactualmodes of action [78]. Compounds showing ATP-competitivekinetics almost certainly bind to the target, yet this basicdata is often not published for new kinase active series.When non-competitive kinetics is found, compounds are usu-ally reported to be allosteric, yet stoichiometry, reversibility orevidence of direct target engagement at the relevant concen-tration is rarely shown. The presence of uncharacterisedmolecules in profiling studies is a concern. For example, inter-pretation of profiling results from compounds such as querce-tin [65] will be complicated by their ability to act as non-stoichiometric false positives in many in vitro assays [79,80].Some profiled kinase compounds contain undesirable sub-structures such as catechols and activated thioethers, whichmany organisations do not screen because of their propensityto interfere in assays [81-85]. Ideally, molecular mode of actionstudies recommended for probes (Table 4) should also becarried out for compounds used for profiling.

4. The challenge of target selection: whatmakes a good kinase inhibition profile?

In current pharmaceutical research, the first decision made isusually which disease to treat. Targets are then selected onthe basis of the best knowledge available. It has been arguedconvincingly that costly clinical trial failures frequently arisefrom inappropriate target selection [86]. Until relativelyrecently, definitive target validation (efficacy of a selectivedrug in patients) has rarely been available for kinases. Simi-larly, there has been little evidence to ascribe undesirableeffects of clinical kinase inhibitors to defined molecular mech-anisms. Opportunities to increase confidence in the causativelink between target inhibition and biological effects canbroadly be divided into biological or chemical approaches.

4.1 Biological target validationClues to biological target validation may arise from the prev-alence of disease-associated mutations, particularly in cancer,or from effects seen in vivo in knockout models [87]. Upregu-lation of kinase expression levels of mRNA or protein in dis-ease tissue can provide additional support [88]. Insights mayalso come at the cellular level, from understanding the com-plex phosphorylation-dependent signalling pathways of dis-ease [89]. A relatively recent development is the availability ofcomplete human kinome RNAi libraries. Outcomes of theiruse include the implication of kinases such as GRK6 andTNK1 in the survival of multiple myeloma and pancreaticcancer cell lines, respectively [90,91], LMTK3 as an estrogenreceptor regulator in breast cancer cell lines [92], and ATMin a TNF-stimulated canonical NF-kB pathway luciferasereporter assay for inflammation [93]. Although most studies

have examined the effects of knocking down one kinase at atime, synergistic effects can also be sought [94].

Biological approaches have greater specificity than mostchemical probes, but a different set of limitations. Kinasescarry out multiple functions in multi-domain macromolecu-lar complexes, and knocking out the entire protein may pro-duce different effects to small molecule inhibition of kinaseactivity [95]. Advances in gene targeting approaches (e.g.,homologous recombination) allow subtle modifications tobe made more readily in cells and model organisms [96,97].Combined chemical genetic approaches, for example,designed ‘bumped’ or covalent kinase inhibitors [98,99], canprovide greater specificity in model systems where sensitisingmutations can be introduced into protein kinases of inter-est [100]. In practice, combinations of multiple biological andchemical approaches are usually needed to achieve confidenceof the role of specific kinases in disease, and this data can beslow to generate.

4.2 Chemical target validationAdvances in kinome profiling and chemoproteomics haveenabled a more complete understanding of the selectivity ofclinical kinase inhibitors, which should increase the reliabilityof target validation and of liability prediction. Examples of thelatter are illustrated in Section 3.2. Of course, insights into thefunctions of kinases in model systems can also come frompreclinical compounds. The most comprehensive summaryto date highlights inhibitors of 20 kinases, having at leastreasonable selectivity [101].

Some requirements of chemical probes suitable for use incellular assays have recently been discussed [102] and are para-phrased inTable 4. For reasons outlined in Section 3.3, to avoidmisinterpretation of data from artefactual hits, one require-ment of these principles has been stated more explicitly: ATPcompetition, and perhaps reversibility and stoichiometry ofbinding to the molecular target, should be confirmed.

As mentioned in Section 3.3, sets of widely profiled kinasecompounds have recently been made available to the widercommunity with the aim of finding new indications for kinaseinhibitors by determining kinase profiles that are efficaciousin model systems of disease [76]. However, the relevance of cel-lular model systems to complex disorders may be uncertain, inwhich case in vitro probe compounds may be of limitedpredictability. For use in in vivo models, effective probe mol-ecules require pharmacokinetic properties comparable tothose of preclinical drug candidates. Unfortunately, suchcompounds may require almost as much time, expense orgood fortune to produce as clinical candidates, so it is lesslikely that they would be freely available to the academic com-munity. For these reasons, chemical probes may augment butwill not replace the need for biological tools.

4.3 Single versus multi-target inhibitionSelective and multi-kinase inhibitors have their own advan-tages and disadvantages [103]. Selective inhibitors should not

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suffer from off-target kinase-related toxicity, but their efficacyis wholly reliant upon one dominant disease/target hypothe-sis. Many ATP-site inhibitors are able to achieve excellentselectivity, including those of EGFR/ErbB2, cMET, cFMS,MEK1/2 and p38a/b ( [42,61], and references in Table 2).Selectivity is more likely to be possible for targets that havefew close homologues or where unique amino acid differencesin the binding site can be exploited. The ability of kinases toadopt unique conformations that are induced or trapped byinhibitor binding may also provide a means of achieving selec-tivity, although so far this has only been possible to rationaliseafter the discovery of the compound. Modulators of kinaseactivity that bind outside the kinase domain of multi-domain proteins (e.g., the pleckstrin-homology domain ofAKT [104]) may be highly selective, but examples of suchcompounds with probe-like properties (Table 4) are extremelyrare, and approaches to discover them will not benefit fromthe chemical connectivity of the system-based approach toATP-site inhibition.The multi-target polypharmacology of some kinase drugs

has been rationalised after the event, but increasingly this isbeing proactively sought. Multi-target inhibitors must strikea balance: they risk more target-related liabilities, which asdiscussed above are very poorly understood, and which maybe more acceptable for some diseases than others. Conversely,if safe, they will have greater opportunity for efficacy andpotential for multiple uses. In cancer, they may be less suscep-tible to resistance. The ability to generate compounds that aretargeted against a defined subset of kinases yet still broadly

selective may be limited to certain combinations of kinases.For example, it has proved easier to obtain compounds withdual EGFR/ErbB2 activity than ones selective between thetwo. In general, the profile of a compound that targetstwo dissimilar kinases is more likely to include additionalactivities than that of a compound that binds two closelyrelated kinases.

4.4 Phenotypic screening and kinase

chemoproteomicsCell-based kinase assays can be divided into four types, rankedapproximately in order of decreasing target specificity andincreasing disease-relevance: target-specific, pathway-specific,reporter and phenotypic [105]. These are traditionally usedafter in vitro target screens to confirm that enzyme activityhas the expected cellular consequences. Rich additional infor-mation may be found, for example, as one recent report inwhich 24 inhibitors with known kinase profiles were testedin a panel of 12 reporter-based assays [106]. As well ashighlighting cellular results that were unexpected based onexisting biochemical screening data, the selectivity of com-pounds was assessed based upon the number of pathwaysinhibited, a potentially more relevant result than the numberof molecular targets. Like kinase profiling, the high-content screening field is also advancing rapidly. Imagingtechniques allow simultaneous multi-parameter measure-ments to be made on individual cells. One study examinedthe effects of 44 cell-cycle kinase inhibitors on markers ofcell cycle and apoptosis, characterising the effects of

Table 4. Properties of validated kinase chemical probes.

Property Requirement Suggested data required for a kinase probe

Molecular profiling Potent and selective enough in vitro so thatmolecular target(s) can be assumed toproduce the cellular or in vivo effects

. Sub-µM activity against primary targets

. Selectivity over closely homologous kinasesand in a panel broad enough to estimate fullkinome selectivity

Molecular mode of action Molecular activity has a relevant mode ofaction at appropriate concentration underassay conditions

. Enzymological determination of ATPcompetition and 1:1 stoichiometry at relevantconcentration

. Kinetic reversibilityPhenotypic activity Cellular or in vivo effects . Dose-dependent behaviour at concentrations

consistent with molecular potency. SAR of close structural analogues correlatebetween in vitro and cellular/in vivo studiesover a wide potency range

Identity of the active species Chemical structure is fully characterised andhas suitable physical properties and stabilityfor its intended purpose

. Confirmed chemical structure

. Stability under assay conditions

. Aqueous solubility at relevant concentrations

. Cell permeability

. Measured DMPK properties if used in vivoProven utility as a probe Cellular data supporting the role of the

molecular target in mediating activity

. Controls to distinguish phenotypic effectsfrom, for example, cytotoxic or cytostaticeffects mediated by cell-cyclekinases or non-kinase mechanisms

Availability Available to the scientific community

Adapted from [102].

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compounds with various selectivities, and fingerprinting com-pounds according to their effects [107]. Importantly, imaginganalysis of individual cells can enable the identification ofsubpopulations that respond differently to inhibition.

Cell-based screening may also be used for primary hit dis-covery as an alternative to the reductionist molecular targetapproach. This strategy aims to avoid poor target selectionfor first-in-class drugs and to better mimic the activity ofkinases in their native context [57,106,108-110]. This also offersthe potential to assay many molecular targets simultaneously.In this case, deconvolution to a molecular mode of action isnot essential but is usually desirable. Knowledge of the targetprofile can help to judge potential risks. In addition, cellularactivity depends on multiple factors including target affinity,membrane permeability and cytotoxicity, which can confoundattempts to understand SAR within a series and make leadoptimisation more challenging. Deconvolution using panelsof target-specific assays negates one key benefit of phenotypicscreening, to identify unexpected modes of action for whichmolecular assays do not exist, so to discover the targets ofbio-active molecules chemoproteomics approaches are oftenpreferred [111,112]. In a recent example, kinases from lung cancercell lines were identified that interact with immobiliseddasatinib. Some of these were confirmed by monitoring com-pound-induced autophosphorylation and the effects of RNAiknockdown and inhibitor-resistant mutations [113]. Immobi-lised inhibitors can also form the basis of competition-formatchemoproteomic platforms. In one example, beads linked tounselective kinase inhibitors were used to detect 181 kinasesin K562 cell lysates. Binding of three kinase inhibitors againstthis panel was measured [114]. Novel targets of imatinib foundin this way included the kinase DDR1 and the oxidoreductaseNQO2, illustrating the ability of chemoproteomics to identifyunexpected non-kinase targets of kinase inhibitors. Activity-based protein profiling is an alternative chemoproteomics plat-form [115]. In one example of its use, protection of kinasesagainst modification by a reactive ATP analogue by competi-tive inhibitors was monitored using mass spectroscopy. Sevencompounds were assayed against lysates from which ~220kinases could be profiled, leading to the identification ofMAP2K5 as a novel target of dasatinib [116].

Despite great progress in cell-based screening, significanthurdles remain. Cell-based screening can alleviate any discon-nect between molecular target assays and cellular activity(although this is usually apparent early in a drug discoveryprogram). However, this relies upon the extent to which agiven cell-type, stimulus or readout is relevant to the diseasein question. The p38 story is a cautionary tale. One of the firstkinases discovered through phenotypic screening, it was iden-tified as the target for anti-inflammatory compounds throughradio-photoaffinity labelling [117]. Despite potent inhibitionof recombinant p38 enzyme activity, TNFa release in cellsand ex vivo human whole blood, and activity in animal mod-els of inflammation, compounds lacked long-term efficacy inRA patients (Section 2.2). This unpredicted result arose not

from disagreement between the target kinase assay and path-way, phenotypic or animal models, but from the use of assaysand models based upon incomplete understanding of themechanism of RA. If the biology of complex disordersremains the biggest gap in our understanding, our greatestchallenge is to develop phenotypic assays and animal modelsthat replicate the genuinely important features of disease.

5. Conclusion

Advances in kinase molecular profiling and cell-basedapproaches are providing ever-more sophisticated approachesto measure the properties of kinase compounds. Combinedwith the significant body of protein structural knowledgeand expertise in protein kinase medicinal chemistry, this pro-vides a powerful platform for the efficient generation of small-molecule kinase inhibitors. The success of this approach isdemonstrated by the wave of approvals of kinase inhibitordrugs in 2011 -- 12. Following the demonstration of the effi-cacy of JAK inhibitors for RA [49,50], even inflammatory dis-eases may finally be starting to succumb to kinase inhibitortreatment. The most significant problems remaining are therelative lack of strongly validated kinase targets for complexdiseases outside the cancer area, and our poor understandingof the nature of kinase-mediated toxicity.

6. Expert opinion: kinase system-basedresearch

Thirteen years have passed since the term ‘systems-basedresearch’ was first applied to protein kinases [69] and imple-mented at GlaxoSmithKline. Other terms have been used fora similar concept: the recognition that the chemical connected-ness of inhibitors of the protein kinase family enables the targetclass to be prosecuted with much greater efficiency than by thetraditional ‘one target for one disease’ approach [118,119]. Thefirst component of GSK’s system-based approach (Figure 5)was the routine cross-screening of compound libraries againstmultiple kinases. The composition of the assay panel evolvedover time, but in 2007 -- 2008 all new kinase compoundswere screened in about 20 assays, targets and perceived liabilitykinases. A greater number of other screens, both internal andexternal, ran on a less frequent basis. A second componentwas the creation of a Kinase Compound Set (KCS) containingthe cumulative diversity of known kinase chemical space, to bescreened when new assays were added to the panel. The KCSwas also used to prioritise target selection, in which screeningagainst multiple kinases was performed in parallel. The quan-tity, quality and selectivity of hits were used to add a tractabilityassessment to other target considerations. The third feature wasa lead-generation chemistry culture in which opportunitieswere actively sought to generate novel kinase-targeted com-pounds through piggy-backing on ongoing chemistry. Theapproach proved highly effective at enabling both rationaland serendipitous lead discovery. From 2002 to 2009, almost

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70% of new kinase leads in GSK were discovered eitherthrough the weekly cross-screen or through the KCS, withabout 20% coming from knowledge-based design includingvirtual screening or fragment-based discovery. Diversityscreening still played a role, making up the remaining 10% ofleads discovered.Using the substantial X-ray structural knowledge-base to

guide rational discovery within the system-based framework,it has been possible to alleviate early concerns that selectiveinhibition of many protein kinases would be impossible andthat toxicity would inevitably result. Recent advances inmethodology have enabled an expansion of kinome screeningpanel size, such that it is now possible to generate interpret-able data for a significant number of compounds againstover half of all human kinases and many disease mutants, ata cost which is still significant but reducing [120]. It is likelythat the goal of panels covering the great majority of thekinome will be achieved in the near future. Anticipating thissituation, researchers will face a new challenge: to decide

what selectivity profile they really need, and what off-targetkinase activities are acceptably safe.

Unfortunately, despite the successes in oncology, it seemsthat our understanding of which kinases are good targets formany other complex diseases still lags behind. This situationis likely to improve gradually as academic research continuesto produce new insights into disease biology. The industrialsector can assist by more actively providing pre-competitivetools for target validation, as there is considerable room forincreasing the quantity of available chemical probes, but thedifficulty of producing molecules of the required qualityshould not be underestimated.

To avoid competition from generic medicines, the pharma-ceutical industry must discover more first-in-class drugs, butthe current focus upon single diseases as the starting pointfor every drug discovery effort is wasteful, as most targethypotheses are only invalidated after much time and effort.Failed targets and compounds are usually abandoned. Thevalue of repurposing failed clinical compounds for other

HTS

Target A

Target B

Target C

Med-chem Assay

Selectivitypanel

Lower throughputassays: cellular,

physchem, PK etc.

Lower throughputassays: cellular,

physchem, PK etc.

KCS

Newtarget

Weeklypanel

monthlypanel

Profiles

SAR leading togreater understanding

Accumulated KCSdata used to select

chemotypes fornew targets

Kinomeprofile

Med-chem optimisation against multiple targetsmultiple chemotypes in parallel

Data

Figure 5. The traditional (upper) versus kinase system-based approach as implemented in GlaxoSmithKline (lower).

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indications is increasingly apparent [121]. Consistent with this,the ‘common mechanisms’ strategy [122] is an approach to dis-eases and targets that advocates that earlier-stage compoundsshould be advanced in parallel through phenotypic assaysacross multiple therapeutic areas. To do this systematicallywould require coordinated effort to produce and makeavailable a range of genuinely predictive disease models.Because this would involve cooperation across traditionaltherapeutic area divisions, there are significant organisationalas well as scientific barriers. However, for kinase inhibitors,which possess unique potential for polypharmacology,such an approach early in the drug discovery process hasgreat opportunity to discover unexpected uses. Coupledwith our demonstrated ability to generate kinase inhibitors

of interest, and increasing ability to profile their activitiesmore thoroughly, the benefits of this approach for moreeffective target discovery seem clear.

Acknowledgements

Thanks to S Davidas for thoughtful comments on trendsin published patents, and J Christopher, C-W Chung andD Miller for careful reading of the draft manuscript.

Declaration of interest

P Bamborough is employed by and owns shares ofGlaxoSmithKline.

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AffiliationPaul Bamborough

Computational and Structural Chemistry,

Molecular Discovery Research,

GlaxoSmithKline Medicines Research Centre,

Gunnels Wood Road,

Stevenage, Hertfordshire SG1 2NY, UK

Tel: +44 0 1438 745745;

Fax: +44 1438 763352;

E-mail: Paul.A.Bamborough@gsk.com

P. Bamborough

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