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1.  Analysis of multiple compound–protein interactions reveals novel bioactive molecules 
The authors use machine learning of compound-protein interactions to explore drug polypharmacology and to efficiently identify bioactive ligands, including novel scaffold-hopping compounds for two pharmaceutically important protein families: G-protein coupled receptors and protein kinases.
We have demonstrated that machine learning of multiple compound–protein interactions is useful for efficient ligand screening and for assessing drug polypharmacology.This approach successfully identified novel scaffold-hopping compounds for two pharmaceutically important protein families: G-protein-coupled receptors and protein kinases.These bioactive compounds were not detected by existing computational ligand-screening methods in comparative studies.The results of this study indicate that data derived from chemical genomics can be highly useful for exploring chemical space, and this systems biology perspective could accelerate drug discovery processes.
The discovery of novel bioactive molecules advances our systems-level understanding of biological processes and is crucial for innovation in drug development. Perturbations of biological systems by chemical probes provide broader applications not only for analysis of complex systems but also for intentional manipulations of these systems. Nevertheless, the lack of well-characterized chemical modulators has limited their use. Recently, chemical genomics has emerged as a promising area of research applicable to the exploration of novel bioactive molecules, and researchers are currently striving toward the identification of all possible ligands for all target protein families (Wang et al, 2009). Chemical genomics studies have shown that patterns of compound–protein interactions (CPIs) are too diverse to be understood as simple one-to-one events. There is an urgent need to develop appropriate data mining methods for characterizing and visualizing the full complexity of interactions between chemical space and biological systems. However, no existing screening approach has so far succeeded in identifying novel bioactive compounds using multiple interactions among compounds and target proteins.
High-throughput screening (HTS) and computational screening have greatly aided in the identification of early lead compounds for drug discovery. However, the large number of assays required for HTS to identify drugs that target multiple proteins render this process very costly and time-consuming. Therefore, interest in using in silico strategies for screening has increased. The most common computational approaches, ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS; Oprea and Matter, 2004; Muegge and Oloff, 2006; McInnes, 2007; Figure 1A), have been used for practical drug development. LBVS aims to identify molecules that are very similar to known active molecules and generally has difficulty identifying compounds with novel structural scaffolds that differ from reference molecules. The other popular strategy, SBVS, is constrained by the number of three-dimensional crystallographic structures available. To circumvent these limitations, we have shown that a new computational screening strategy, chemical genomics-based virtual screening (CGBVS), has the potential to identify novel, scaffold-hopping compounds and assess their polypharmacology by using a machine-learning method to recognize conserved molecular patterns in comprehensive CPI data sets.
The CGBVS strategy used in this study was made up of five steps: CPI data collection, descriptor calculation, representation of interaction vectors, predictive model construction using training data sets, and predictions from test data (Figure 1A). Importantly, step 1, the construction of a data set of chemical structures and protein sequences for known CPIs, did not require the three-dimensional protein structures needed for SBVS. In step 2, compound structures and protein sequences were converted into numerical descriptors. These descriptors were used to construct chemical or biological spaces in which decreasing distance between vectors corresponded to increasing similarity of compound structures or protein sequences. In step 3, we represented multiple CPI patterns by concatenating these chemical and protein descriptors. Using these interaction vectors, we could quantify the similarity of molecular interactions for compound–protein pairs, despite the fact that the ligand and protein similarity maps differed substantially. In step 4, concatenated vectors for CPI pairs (positive samples) and non-interacting pairs (negative samples) were input into an established machine-learning method. In the final step, the classifier constructed using training sets was applied to test data.
To evaluate the predictive value of CGBVS, we first compared its performance with that of LBVS by fivefold cross-validation. CGBVS performed with considerably higher accuracy (91.9%) than did LBVS (84.4%; Figure 1B). We next compared CGBVS and SBVS in a retrospective virtual screening based on the human β2-adrenergic receptor (ADRB2). Figure 1C shows that CGBVS provided higher hit rates than did SBVS. These results suggest that CGBVS is more successful than conventional approaches for prediction of CPIs.
We then evaluated the ability of the CGBVS method to predict the polypharmacology of ADRB2 by attempting to identify novel ADRB2 ligands from a group of G-protein-coupled receptor (GPCR) ligands. We ranked the prediction scores for the interactions of 826 reported GPCR ligands with ADRB2 and then analyzed the 50 highest-ranked compounds in greater detail. Of 21 commercially available compounds, 11 showed ADRB2-binding activity and were not previously reported to be ADRB2 ligands. These compounds included ligands not only for aminergic receptors but also for neuropeptide Y-type 1 receptors (NPY1R), which have low protein homology to ADRB2. Most ligands we identified were not detected by LBVS and SBVS, which suggests that only CGBVS could identify this unexpected cross-reaction for a ligand developed as a target to a peptidergic receptor.
The true value of CGBVS in drug discovery must be tested by assessing whether this method can identify scaffold-hopping lead compounds from a set of compounds that is structurally more diverse. To assess this ability, we analyzed 11 500 commercially available compounds to predict compounds likely to bind to two GPCRs and two protein kinases. Functional assays revealed that nine ADRB2 ligands, three NPY1R ligands, five epidermal growth factor receptor (EGFR) inhibitors, and two cyclin-dependent kinase 2 (CDK2) inhibitors were concentrated in the top-ranked compounds (hit rate=30, 15, 25, and 10%, respectively). We also evaluated the extent of scaffold hopping achieved in the identification of these novel ligands. One ADRB2 ligand, two NPY1R ligands, and one CDK2 inhibitor exhibited scaffold hopping (Figure 4), indicating that CGBVS can use this characteristic to rationally predict novel lead compounds, a crucial and very difficult step in drug discovery. This feature of CGBVS is critically different from existing predictive methods, such as LBVS, which depend on similarities between test and reference ligands, and focus on a single protein or highly homologous proteins. In particular, CGBVS is useful for targets with undefined ligands because this method can use CPIs with target proteins that exhibit lower levels of homology.
In summary, we have demonstrated that data mining of multiple CPIs is of great practical value for exploration of chemical space. As a predictive model, CGBVS could provide an important step in the discovery of such multi-target drugs by identifying the group of proteins targeted by a particular ligand, leading to innovation in pharmaceutical research.
The discovery of novel bioactive molecules advances our systems-level understanding of biological processes and is crucial for innovation in drug development. For this purpose, the emerging field of chemical genomics is currently focused on accumulating large assay data sets describing compound–protein interactions (CPIs). Although new target proteins for known drugs have recently been identified through mining of CPI databases, using these resources to identify novel ligands remains unexplored. Herein, we demonstrate that machine learning of multiple CPIs can not only assess drug polypharmacology but can also efficiently identify novel bioactive scaffold-hopping compounds. Through a machine-learning technique that uses multiple CPIs, we have successfully identified novel lead compounds for two pharmaceutically important protein families, G-protein-coupled receptors and protein kinases. These novel compounds were not identified by existing computational ligand-screening methods in comparative studies. The results of this study indicate that data derived from chemical genomics can be highly useful for exploring chemical space, and this systems biology perspective could accelerate drug discovery processes.
PMCID: PMC3094066  PMID: 21364574
chemical genomics; data mining; drug discovery; ligand screening; systems chemical biology
2.  Deciphering the Arginine-Binding Preferences at the Substrate-Binding Groove of Ser/Thr Kinases by Computational Surface Mapping 
PLoS Computational Biology  2011;7(11):e1002288.
Protein kinases are key signaling enzymes that catalyze the transfer of γ-phosphate from an ATP molecule to a phospho-accepting residue in the substrate. Unraveling the molecular features that govern the preference of kinases for particular residues flanking the phosphoacceptor is important for understanding kinase specificities toward their substrates and for designing substrate-like peptidic inhibitors. We applied ANCHORSmap, a new fragment-based computational approach for mapping amino acid side chains on protein surfaces, to predict and characterize the preference of kinases toward Arginine binding. We focus on positions P−2 and P−5, commonly occupied by Arginine (Arg) in substrates of basophilic Ser/Thr kinases. The method accurately identified all the P−2/P−5 Arg binding sites previously determined by X-ray crystallography and produced Arg preferences that corresponded to those experimentally found by peptide arrays. The predicted Arg-binding positions and their associated pockets were analyzed in terms of shape, physicochemical properties, amino acid composition, and in-silico mutagenesis, providing structural rationalization for previously unexplained trends in kinase preferences toward Arg moieties. This methodology sheds light on several kinases that were described in the literature as having non-trivial preferences for Arg, and provides some surprising departures from the prevailing views regarding residues that determine kinase specificity toward Arg. In particular, we found that the preference for a P−5 Arg is not necessarily governed by the 170/230 acidic pair, as was previously assumed, but by several different pairs of acidic residues, selected from positions 133, 169, and 230 (PKA numbering). The acidic residue at position 230 serves as a pivotal element in recognizing Arg from both the P−2 and P−5 positions.
Author Summary
Protein kinases are key signaling enzymes and major drug targets that catalyze the transfer of phosphate group to a phospho-accepting residue in the substrate. Unraveling molecular features that govern the preference of kinases for particular residues flanking the phosphoacceptor (substrate consensus sequence, SCS) is important for understanding kinase-substrates specificities and for designing peptidic inhibitors. Current methods used to predict this set of essential residues usually rely on linking between experimentally determined SCSs to kinase sequences. As such, these methods are less sensitive when specificity is dictated by subtle or kinase-unique sequence/structural features. In this study, we took a different approach for studying kinases specificities, by applying a new fragment-based method for mapping amino acid side chains on protein surfaces. We predicted and characterized the preference of Ser/Thr kinases toward Arginine binding, using the unbound kinase structures. The method produced high quality predictions and was able to provide novel insights and interesting departures from the prevailing views regarding the specificity-determining elements governing specificity toward Arginine. This work paves the way for studying the kinase binding preferences for other amino acids, for predicting protein-peptide structures, for facilitating the design of novel inhibitors, and for re-engineering of kinase specificities.
PMCID: PMC3219626  PMID: 22125489
3.  Applying Ligands Profiling Using Multiple Extended Electron Distribution Based Field Templates and Feature Trees Similarity Searching in the Discovery of New Generation of Urea-Based Antineoplastic Kinase Inhibitors 
PLoS ONE  2012;7(11):e49284.
This study provides a comprehensive computational procedure for the discovery of novel urea-based antineoplastic kinase inhibitors while focusing on diversification of both chemotype and selectivity pattern. It presents a systematic structural analysis of the different binding motifs of urea-based kinase inhibitors and the corresponding configurations of the kinase enzymes. The computational model depends on simultaneous application of two protocols. The first protocol applies multiple consecutive validated virtual screening filters including SMARTS, support vector-machine model (ROC = 0.98), Bayesian model (ROC = 0.86) and structure-based pharmacophore filters based on urea-based kinase inhibitors complexes retrieved from literature. This is followed by hits profiling against different extended electron distribution (XED) based field templates representing different kinase targets. The second protocol enables cancericidal activity verification by using the algorithm of feature trees (Ftrees) similarity searching against NCI database. Being a proof-of-concept study, this combined procedure was experimentally validated by its utilization in developing a novel series of urea-based derivatives of strong anticancer activity. This new series is based on 3-benzylbenzo[d]thiazol-2(3H)-one scaffold which has interesting chemical feasibility and wide diversification capability. Antineoplastic activity of this series was assayed in vitro against NCI 60 tumor-cell lines showing very strong inhibition of GI50 as low as 0.9 uM. Additionally, its mechanism was unleashed using KINEX™ protein kinase microarray-based small molecule inhibitor profiling platform and cell cycle analysis showing a peculiar selectivity pattern against Zap70, c-src, Mink1, csk and MeKK2 kinases. Interestingly, it showed activity on syk kinase confirming the recent studies finding of the high activity of diphenyl urea containing compounds against this kinase. Allover, the new series, which is based on a new kinase scaffold with interesting chemical diversification capabilities, showed that it exhibits its “emergent” properties by perturbing multiple unexplored kinase pathways.
PMCID: PMC3502486  PMID: 23185312
4.  The SH2 Domain Regulates c-Abl Kinase Activation by a Cyclin-Like Mechanism and Remodulation of the Hinge Motion 
PLoS Computational Biology  2014;10(10):e1003863.
Regulation of the c-Abl (ABL1) tyrosine kinase is important because of its role in cellular signaling, and its relevance in the leukemiogenic counterpart (BCR-ABL). Both auto-inhibition and full activation of c-Abl are regulated by the interaction of the catalytic domain with the Src Homology 2 (SH2) domain. The mechanism by which this interaction enhances catalysis is not known. We combined computational simulations with mutagenesis and functional analysis to find that the SH2 domain conveys both local and global effects on the dynamics of the catalytic domain. Locally, it regulates the flexibility of the αC helix in a fashion reminiscent of cyclins in cyclin-dependent kinases, reorienting catalytically important motifs. At a more global level, SH2 binding redirects the hinge motion of the N and C lobes and changes the conformational equilibrium of the activation loop. The complex network of subtle structural shifts that link the SH2 domain with the activation loop and the active site may be partially conserved with other SH2-domain containing kinases and therefore offer additional parameters for the design of conformation-specific inhibitors.
Author Summary
The Abl kinase is a key player in many crucial cellular processes. It is also an important anti-cancer drug target, because a mutation leading to the fusion protein Bcr-Abl is the main cause for chronic myeloid leukemia (CML). Abl inhibitors are currently the only pharmaceutical treatment for CML. There are two main difficulties associated with the development of kinase inhibitors: the high similarity between active sites of different kinases, which makes selectivity a challenge, and mutations leading to resistance, which make it mandatory to search for alternative drugs. One important factor controlling Abl is the interplay between the catalytic domain and an SH2 domain. We used computer simulations to understand how the interactions between the domains modify the dynamic of the kinase and detected both local and global effects. Based on our computer model, we suggested mutations that should alter the domain-domain interplay. Consequently, we tested the mutants experimentally and found that they support our hypothesis. We propose that our findings can be of help for the development of new classes of Abl inhibitors, which would modify the domain-domain interplay instead of interfering directly with the active site.
PMCID: PMC4191882  PMID: 25299346
5.  Toward a Molecular Understanding of the Interaction of Dual Specificity Phosphatases with Substrates: Insights from Structure-Based Modeling and High Throughput Screening 
Current Medicinal Chemistry  2008;15(25):2536-2544.
Dual-specificity phosphatases (DSPs) are important, but poorly understood, cell signaling enzymes that remove phosphate groups from tyrosine and serine/threonine residues on their substrate. Deregulation of DSPs has been implicated in cancer, obesity, diabetes, inflammation, and Alzheimer’s disease. Due to their biological and biomedical significance, DSPs have increasingly become the subject of drug discovery high-throughput screening (HTS) and focused compound library development efforts. Progress in identifying selective and potent DSP inhibitors has, however, been restricted by the lack of sufficient structural data on inhibitor-bound DSPs. The shallow, almost flat, substrate binding sites in DSPs have been a major factor in hampering the rational design and the experimental development of active site inhibitors. Recent experimental and virtual HTS studies, as well as advances in molecular modeling, provide new insights into the potential mechanisms for substrate recognition and binding by this important class of enzymes. We present herein an overview of the progress, along with a brief description of applications to two types of DSPs: Cdc25 and MAP kinase phosphatase (MKP) family members. In particular, we focus on combined computational and experimental efforts for designing Cdc25B and MKP-1 inhibitors and understanding their mechanisms of interactions with their target proteins. These studies emphasize the utility of developing computational models and methods that meet the two major challenges currently faced in structure-based in silico design of lead compounds: the conformational flexibility of the target protein and the entropic contribution to the selection and stabilization of particular bound conformers.
PMCID: PMC2764859  PMID: 18855677
Dual-specificity phosphatases; computer-aided drug discovery; high throughput screening; structure-based virtual screening; molecular docking; intrinsic dynamics; focused library design.
6.  An Unbiased Cell Morphology–Based Screen for New, Biologically Active Small Molecules 
PLoS Biology  2005;3(5):e128.
We have implemented an unbiased cell morphology–based screen to identify small-molecule modulators of cellular processes using the Cytometrix (TM) automated imaging and analysis system. This assay format provides unbiased analysis of morphological effects induced by small molecules by capturing phenotypic readouts of most known classes of pharmacological agents and has the potential to read out pathways for which little is known. Four human-cancer cell lines and one noncancerous primary cell type were treated with 107 small molecules comprising four different protein kinase–inhibitor scaffolds. Cellular phenotypes induced by each compound were quantified by multivariate statistical analysis of the morphology, staining intensity, and spatial attributes of the cellular nuclei, microtubules, and Golgi compartments. Principal component analysis was used to identify inhibitors of cellular components not targeted by known protein kinase inhibitors. Here we focus on a hydroxyl-substituted analog (hydroxy-PP) of the known Src-family kinase inhibitor PP2 because it induced cell-specific morphological features distinct from all known kinase inhibitors in the collection. We used affinity purification to identify a target of hydroxy-PP, carbonyl reductase 1 (CBR1), a short-chain dehydrogenase-reductase. We solved the X-ray crystal structure of the CBR1/hydroxy-PP complex to 1.24 Å resolution. Structure-based design of more potent and selective CBR1 inhibitors provided probes for analyzing the biological function of CBR1 in A549 cells. These studies revealed a previously unknown function for CBR1 in serum-withdrawal-induced apoptosis. Further studies indicate CBR1 inhibitors may enhance the effectiveness of anticancer anthracyclines. Morphology-based screening of diverse cancer cell types has provided a method for discovering potent new small-molecule probes for cell biological studies and anticancer drug candidates.
An imaging-based screen, followed by structural and functional analysis, led to the discovery of new inhibitors of carbonyl reductase 1, a potential anticancer target
PMCID: PMC1073692  PMID: 15799708
7.  Induction of BIM Is Essential for Apoptosis Triggered by EGFR Kinase Inhibitors in Mutant EGFR-Dependent Lung Adenocarcinomas 
PLoS Medicine  2007;4(10):e294.
Mutations in the epidermal growth factor receptor (EGFR) gene are associated with increased sensitivity of lung cancers to kinase inhibitors like erlotinib. Mechanisms of cell death that occur after kinase inhibition in these oncogene-dependent tumors have not been well delineated. We sought to improve understanding of this process in order to provide insight into mechanisms of sensitivity and/or resistance to tyrosine kinase inhibitors and to uncover new targets for therapy.
Methods and Findings
Using a panel of human lung cancer cell lines that harbor EGFR mutations and a variety of biochemical, molecular, and cellular techniques, we show that EGFR kinase inhibition in drug-sensitive cells provokes apoptosis via the intrinsic pathway of caspase activation. The process requires induction of the proapoptotic BH3-only BCL2 family member BIM (i.e., BCL2-like 11, or BCL2L11); erlotinib dramatically induces BIM levels in sensitive but not in resistant cell lines, and knockdown of BIM expression by RNA interference virtually eliminates drug-induced cell killing in vitro. BIM status is regulated at both transcriptional and posttranscriptional levels and is influenced by the extracellular signal-regulated kinase (ERK) signaling cascade downstream of EGFR. Consistent with these findings, lung tumors and xenografts from mice bearing mutant EGFR-dependent lung adenocarcinomas display increased concentrations of Bim after erlotinib treatment. Moreover, an inhibitor of antiapoptotic proteins, ABT-737, enhances erlotinib-induced cell death in vitro.
In drug-sensitive EGFR mutant lung cancer cells, induction of BIM is essential for apoptosis triggered by EGFR kinase inhibitors. This finding implies that the intrinsic pathway of caspase activation may influence sensitivity and/or resistance of EGFR mutant lung tumor cells to EGFR kinase inhibition. Manipulation of the intrinsic pathway could be a therapeutic strategy to enhance further the clinical outcomes of patients with EGFR mutant lung tumors.
Using a panel of human drug-sensitive EGFR mutant lung cancer cells, William Pao and colleagues show that induction of BIM, a member of the BCL2 family, is essential for apoptosis triggered by EGFR kinase inhibitors.
Editors' Summary
Lung cancer, a common type of cancer, has a very low cure rate. Like all cancers, it occurs when cells begin to divide uncontrollably because of changes (mutations) in their genes. Chemotherapy drugs kill these rapidly dividing cells but, because some normal tissues are sensitive to these agents, it is hard to destroy the cancer without causing serious side effects. Recently, “targeted” therapies have brought new hope to some patients with cancer. These therapies attack the changes in cancer cells that allow them to divide uncontrollably but leave normal cells unscathed. One of the first molecules for which a targeted therapy was developed was the epidermal growth factor receptor (EGFR). In normal cells, messenger proteins bind to EGFR and activate its “tyrosine kinase,” an enzyme that sticks phosphate groups on tyrosine (an amino acid) in other proteins. These proteins then tell the cell to divide. Alterations to this signaling system drive uncontrolled cell division in some cancers so blocking the EGFR signaling pathway should stop these cancers growing. Indeed, some lung cancers with mutations in the tyrosine kinase of EGFR shrink dramatically when treated with gefitinib or erlotinib, two tyrosine kinase inhibitors (TKIs).
Why Was This Study Done?
TKI-sensitive lung cancers shrink when treated with TKIs because of drug-induced cell death, but what are the molecular mechanisms underlying this death? A better understanding of how TKIs kill cancer cells might provide new insights into why not all cancer cells with mutations in EGFR (the gene from which EGFR is made) are sensitive to TKIs. It might also uncover new targets for therapy. TKIs do not completely kill lung cancers, but if the mechanism of TKI-induced cell death were understood, it might be possible to enhance their effects. In this study, the researchers have investigated how cell death occurs after kinase inhibition in a panel of human lung cancer cell lines (cells isolated from human tumors that grow indefinitely in dishes) that carry EGFR mutations.
What Did the Researchers Do and Find?
The researchers show, first, that erlotinib induces a type of cell death called apoptosis in erlotinib-sensitive cell lines but not in resistant cell lines. Apoptosis can be activated by two major pathways. In this instance, the researchers report, the so-called “intrinsic” pathway activates apoptosis. This pathway is stimulated by proapoptotic members of the BCL2 family of proteins and is blocked by antiapoptotic members, so the researchers examined the effect of erlotinib treatment on the expression of BCL2 family members in the EGFR mutant cell lines. Erlotinib treatment increased the expression of the proapoptotic protein BIM in sensitive but not in resistant cell lines. It also removed phosphate groups from BIM—dephosphorylated BIM is a more potent proapoptotic protein. Conversely, blocking BIM expression using a technique called RNA interference virtually eliminated the ability of erlotinib to kill EGFR mutant cell lines. The researchers also report that erlotinib treatment increased BIM expression in erlotinib-sensitive lung tumors growing in mice and that an inhibitor of the anti-apoptotic protein BCL2 enhanced erlotinib-induced death in drug-sensitive cells growing in dishes.
What Do These Findings Mean?
These findings indicate that BIM activity is essential for the apoptosis triggered by TKIs in drug-sensitive lung cancer cells that carry EGFR mutations, and that treatment of these cells with TKIs induces both the expression and dephosphorylation of BIM. The finding that the intrinsic pathway of apoptosis activation is involved in TKI-induced cell death suggests that changes in this pathway (possibly mutations in some of its components) might influence the sensitivity of EGFR mutant lung cancers to TKIs. Finally, these findings suggest that giving drugs that affect the intrinsic pathway of apoptosis activation at the same time as TKIs might further improve the clinical outcome for patients with EGFR mutant tumors. Such combinations will have to be tested in clinical trials before being used routinely.
Additional Information.
Please access these Web sites via the online version of this summary at
US National Cancer Institute information for patients and professionals on lung cancer (in English and Spanish)
Information for patients from Cancer Research UK on lung cancer including information on treatment with TKIs
Wikipedia pages on apoptosis, epidermal growth factor receptor, and BCL-2 proteins (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
Information for patients from Cancerbackup on erlotinib and gefitinib
PMCID: PMC2001209  PMID: 17927446
8.  Identification of a Kinase Profile that Predicts Chromosome Damage Induced by Small Molecule Kinase Inhibitors 
PLoS Computational Biology  2009;5(7):e1000446.
Kinases are heavily pursued pharmaceutical targets because of their mechanistic role in many diseases. Small molecule kinase inhibitors (SMKIs) are a compound class that includes marketed drugs and compounds in various stages of drug development. While effective, many SMKIs have been associated with toxicity including chromosomal damage. Screening for kinase-mediated toxicity as early as possible is crucial, as is a better understanding of how off-target kinase inhibition may give rise to chromosomal damage. To that end, we employed a competitive binding assay and an analytical method to predict the toxicity of SMKIs. Specifically, we developed a model based on the binding affinity of SMKIs to a panel of kinases to predict whether a compound tests positive for chromosome damage. As training data, we used the binding affinity of 113 SMKIs against a representative subset of all kinases (290 kinases), yielding a 113×290 data matrix. Additionally, these 113 SMKIs were tested for genotoxicity in an in vitro micronucleus test (MNT). Among a variety of models from our analytical toolbox, we selected using cross-validation a combination of feature selection and pattern recognition techniques: Kolmogorov-Smirnov/T-test hybrid as a univariate filter, followed by Random Forests for feature selection and Support Vector Machines (SVM) for pattern recognition. Feature selection identified 21 kinases predictive of MNT. Using the corresponding binding affinities, the SVM could accurately predict MNT results with 85% accuracy (68% sensitivity, 91% specificity). This indicates that kinase inhibition profiles are predictive of SMKI genotoxicity. While in vitro testing is required for regulatory review, our analysis identified a fast and cost-efficient method for screening out compounds earlier in drug development. Equally important, by identifying a panel of kinases predictive of genotoxicity, we provide medicinal chemists a set of kinases to avoid when designing compounds, thereby providing a basis for rational drug design away from genotoxicity.
Author Summary
Small molecule kinase inhibitors (SMKIs) are a class of chemicals that have successfully been used for the treatment of a number of oncological diseases that are now being pursued by the pharmaceutical industry for inflammatory diseases, such as rheumatoid arthritis. SMKIs are generally designed to specifically inhibit one kinase, but this is challenging due to the structural similarity of the ATP binding pocket amongst different members of the kinase family. The inability to selectively inhibit just one kinase can be problematic, as kinases play key roles in a number of cellular processes. Thus the unwanted inhibition of additional kinases can lead to undesirable toxicities that may halt drug development. One type of toxicity often observed with this class of compounds is damage to chromosomes, which can occur when kinases involved with cell cycle progression or chromosome dynamics are inhibited. Here we demonstrate that mathematical modeling can be used to identify kinases that correlate with chromosome damage, information which can assist medicinal chemists in avoiding certain kinases when synthesizing new chemicals. Generation of this type of information is one of the first steps in beginning to reduce toxicity-based attrition for this class of compounds.
PMCID: PMC2704959  PMID: 19629159
9.  Gefitinib-Induced Killing of NSCLC Cell Lines Expressing Mutant EGFR Requires BIM and Can Be Enhanced by BH3 Mimetics 
PLoS Medicine  2007;4(10):e316.
The epidermal growth factor receptor (EGFR) plays a critical role in the control of cellular proliferation, differentiation, and survival. Abnormalities in EGF-EGFR signaling, such as mutations that render the EGFR hyperactive or cause overexpression of the wild-type receptor, have been found in a broad range of cancers, including carcinomas of the lung, breast, and colon. EGFR inhibitors such as gefitinib have proven successful in the treatment of certain cancers, particularly non-small cell lung cancers (NSCLCs) harboring activating mutations within the EGFR gene, but the molecular mechanisms leading to tumor regression remain unknown. Therefore, we wished to delineate these mechanisms.
Methods and Findings
We performed biochemical and genetic studies to investigate the mechanisms by which inhibitors of EGFR tyrosine kinase activity, such as gefitinib, inhibit the growth of human NSCLCs. We found that gefitinib triggered intrinsic (also called “mitochondrial”) apoptosis signaling, involving the activation of BAX and mitochondrial release of cytochrome c, ultimately unleashing the caspase cascade. Gefitinib caused a rapid increase in the level of the proapoptotic BH3-only protein BIM (also called BCL2-like 11) through both transcriptional and post-translational mechanisms. Experiments with pharmacological inhibitors indicated that blockade of MEK–ERK1/2 (mitogen-activated protein kinase kinase–extracellular signal-regulated protein kinase 1/2) signaling, but not blockade of PI3K (phosphatidylinositol 3-kinase), JNK (c-Jun N-terminal kinase or mitogen-activated protein kinase 8), or AKT (protein kinase B), was critical for BIM activation. Using RNA interference, we demonstrated that BIM is essential for gefitinib-induced killing of NSCLC cells. Moreover, we found that gefitinib-induced apoptosis is enhanced by addition of the BH3 mimetic ABT-737.
Inhibitors of the EGFR tyrosine kinase have proven useful in the therapy of certain cancers, in particular NSCLCs possessing activating mutations in the EGFR kinase domain, but the mechanisms of tumor cell killing are still unclear. In this paper, we demonstrate that activation of the proapoptotic BH3-only protein BIM is essential for tumor cell killing and that shutdown of the EGFR–MEK–ERK signaling cascade is critical for BIM activation. Moreover, we demonstrate that addition of a BH3 mimetic significantly enhances killing of NSCLC cells by the EGFR tyrosine kinase inhibitor gefitinib. It appears likely that this approach represents a paradigm shared by many, and perhaps all, oncogenic tyrosine kinases and suggests a powerful new strategy for cancer therapy.
Andreas Strasser and colleagues demonstrate that activation of the proapoptotic BH3-only protein BIM is essential for tumor cell killing and that shutdown of the EGFR−MEK−ERK signaling cascade is critical for BIM activation.
Editors' Summary
Normally, cell division (which produces new cells) and cell death are finely balanced to keep the human body in good working order. But sometimes cells acquire changes (mutations) in their genetic material that allow them to divide uncontrollably to form cancers—life-threatening, disorganized masses of cells. One protein with a critical role in cell division that is often mutated in tumors is the epidermal growth factor receptor (EGFR). In normal cells, protein messengers bind to EGFR and activate its tyrosine kinase. This enzyme then adds phosphate groups to tyrosine (an amino acid) in proteins that form part of signaling cascades (for example, the MEK–ERK signaling cascade) that tell the cell to divide. In cancers that have mutations in EGFR, signaling is overactive so the cancer cells divide much more than they should. Some non-small cell lung cancers (NSCLC, the commonest type of lung cancer), for example, have activating mutations within the EGFR tyrosine kinase. Treatment with EGFR tyrosine kinase inhibitors (TKIs) such as gefitinib and erlotinib induces the cells in these tumors to stop growing and die. This cell death causes tumor shrinkage (regression) and increases the life expectancy of patients with this type of NSCLC.
Why Was This Study Done?
Unfortunately, treatment with TKIs rarely cures NSCLC, so it would be useful to find a way to augment the effect that TKIs have on cancer cells. To do this, the molecular mechanisms that cause cancer-cell death and tumor regression in response to these drugs need to be fully understood. In this study, the researchers have used a combination of biochemical and genetic approaches to investigate how gefitinib kills NSCLC cells with mutated EGFR.
What Did the Researchers Do and Find?
The researchers first measured the sensitivity of NSCLC cell lines (tumor cells that grow indefinitely in dishes) to gefitinib-induced apoptosis. Gefitinib caused extensive apoptosis in two cell lines expressing mutant EGFR but not in one expressing normal EGFR. Next, they investigated the mechanism of gefitinib-induced apoptosis in the most sensitive cell line (H3255). Apoptosis is activated via two major pathways. Hallmarks of the “intrinsic” pathway include activation of a protein called BAX and cytochrome c release from subcellular compartments known as mitochondria. Gefitinib treatment induced both these events in H3255 cells. BAX (a proapoptotic member of the BCL-2 family of proteins) is activated when proapoptotic BH3-only BCL-2 proteins (for example, BIM; “BH3-only” describes the structure of these proteins) bind to antiapoptotic BCL2 proteins. Gefitinib treatment rapidly increased BIM activity in H3255 and HCC827 cells (but not in gefitinib-resistant cells) by increasing the production of BIM protein and the removal of phosphate groups from it, which increases BIM activity. Pharmacological blockade of the MEK–ERK signaling cascade, but not of other EGFR signaling cascades, also caused the accumulation of BIM. By contrast, blocking BIM expression using a technique called RNA interference reduced gefitinib-induced apoptosis. Finally, a combination of gefitinib and a BH3-mimicking compound called ABT-737 (which, like BIM, binds to antiapoptotic BCL-2 proteins) caused more apoptosis than gefitinib alone.
What Do These Findings Mean?
These findings (and those reported by Gong et al. and Costa et al.) indicate that activation of the proapoptotic BH3-only protein BIM is essential for gefitinib-induced killing of NSCLC cells that carry EGFR tyrosine kinase mutations. They also show that inhibition of the EGFR–MEK–ERK signaling cascade by gefitinib is essential for BIM activation. Because these findings come from studies on NSCLC cell lines, they need confirming in freshly isolated tumor cells and in tumors growing in people. However, the demonstration that a compound that mimics BH3 action enhances gefitinib-induced killing of NSCLC cells suggests that combinations of TKIs and drugs that affect the intrinsic pathway of apoptosis activation might provide a powerful strategy for treating cancers in which tyrosine kinase mutations drive tumor growth.
Additional Information.
Please access these Web sites via the online version of this summary at
A perspective by Ingo Mellinghoff discusses this article and two related research articles
Wikipedia pages on epidermal growth factor receptor, apoptosis, and BCL2 proteins (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
CancerQuest provides information on all aspects of cancer from Emory University (in several languages)
US National Cancer Institute information for patients and professionals on lung cancer (in English and Spanish)
Information for patients from Cancer Research UK on lung cancer including information on treatment with TKIs
Information for patients from Cancerbackup on erlotinib and gefitinib
PMCID: PMC2043013  PMID: 17973573
10.  New Challenges and Inspired Answers for Anticancer Drug Discovery and Development 
Many pharmaceutical companies worldwide specialize in oncology drug development and marketing. Among them, we have continued to take up the challenge of understanding the metabolism of pyrimidines as essential components of deoxyribonucleic acid for many years, and have provided unique products such as UFT® and TS-1 for cancer patients. Using our cumulative experience and knowledge, we are currently developing novel agents such as TAS-114, a dual inhibitor of deoxyuridine triphosphatase and dihydropyrimidine dehydrogenase, and TAS-102, a unique pyrimidine derivative inducing deoxyribonucleic acid dysfunction in cancer cells. Regarding molecular-targeted drugs, we have made huge efforts to establish ideal drug discovery platforms for the last several years. For kinase inhibitors, we established three core platforms such as a kinase-directed chemical library, a kinase assay panel and a target selection informatics system. The core platforms were further combined with peripheral technologies to measure essential parameters such as physicochemical properties, pharmacokinetics, efficacy and toxicities. Unique drug candidates have been identified at an early stage by assessing all important parameters. Several promising programs are proceeding simultaneously in the clinical or preclinical development stage such as TAS-115, a dual inhibitor of c-Met and vascular endothelial growth factor receptor, TAS-2104, a selective Aurora A inhibitor, TAS-117, an allosteric Akt inhibitor, TAS-2985, an irreversible fibroblast growth factor receptor inhibitor and TAS-2913, a T790M mutant selective epidermal growth factor receptor inhibitor. Other than kinase inhibitors, another drug discovery engine was established based on the fragment-based drug discovery technology. TAS-116, a new class of Hsp-90α/β inhibitor, is one of the products. Taiho's final goal is to provide innovative anticancer drugs together with companion diagnostics that are truly beneficial for patients.
PMCID: PMC3787805  PMID: 24014883
GI medicine; lung-Med; new technology/instruments; immunology; breast medicine
11.  Structural Basis for the Regulation Mechanism of the Tyrosine Kinase CapB from Staphylococcus aureus 
PLoS Biology  2008;6(6):e143.
Bacteria were thought to be devoid of tyrosine-phosphorylating enzymes. However, several tyrosine kinases without similarity to their eukaryotic counterparts have recently been identified in bacteria. They are involved in many physiological processes, but their accurate functions remain poorly understood due to slow progress in their structural characterization. They have been best characterized as copolymerases involved in the synthesis and export of extracellular polysaccharides. These compounds play critical roles in the virulence of pathogenic bacteria, and bacterial tyrosine kinases can thus be considered as potential therapeutic targets. Here, we present the crystal structures of the phosphorylated and unphosphorylated states of the tyrosine kinase CapB from the human pathogen Staphylococcus aureus together with the activator domain of its cognate transmembrane modulator CapA. This first high-resolution structure of a bacterial tyrosine kinase reveals a 230-kDa ring-shaped octamer that dissociates upon intermolecular autophosphorylation. These observations provide a molecular basis for the regulation mechanism of the bacterial tyrosine kinases and give insights into their copolymerase function.
Author Summary
An idiosyncratic new class of bacterial enzymes, bacterial tyrosine-kinases (BY-kinases), has been characterized. These enzymes, which are involved in an increasing number of physiological processes ranging from stress resistance to pathogenicity, share no sequence similarities with eukaryotic kinases, and their function remains largely unknown. They have nevertheless been described to undergo autophosphorylation on a C-terminal tyrosine cluster and to phosphorylate endogenous protein substrates. We describe here the first crystal structure of a bacterial tyrosine kinase, namely CapB from the pathogen Staphylococcus aureus, in complex with the cytoplasmic domain of the transmembrane stimulatory protein CapA. Our data explain the activation mechanism of CapB by CapA and allow us to propose a regulatory mechanism based on intermolecular autophosphorylation. These results also give new insights onto the phosphorylation of the endogenous substrate CapO, an enzyme involved in the synthesis of polysaccharide precursors. CapA and CapB, among others, are involved as copolymerases in the synthesis of extracellular polysaccharides that are thought to be potent virulence factors. Thus, these structural data provide the basis for designing specific inhibitors for these enzymes, which constitute an original and attractive target for the development of new drugs to treat infectious diseases.
Structural analysis of a conserved bacterial tyrosine kinase fromStaphylococcus aureus provides the basis for deciphering its regulatory mechanism, leading to a model for its implication in extracellular polysaccharide synthesis.
PMCID: PMC2422856  PMID: 18547145
12.  Adaptive Responses to Dasatinib-Treated Lung Squamous Cell Cancer Cells Harboring DDR2 Mutations 
Cancer research  2014;74(24):7217-7228.
DDR2 mutations occur in ~4% of lung squamous cell cancer (SCC) where the tyrosine kinase inhibitor dasatinib has emerged as a new therapeutic option. We found that ERK and AKT phosphorylation was weakly inhibited by dasatinib in DDR2-mutant lung SCC cells, suggesting that dasatinib inhibits survival signals distinct from other oncogenic RTKs and/or compensatory signals exist that dampen dasatinib activity. To gain better insight into dasatinib’s action in these cells, we assessed altered global tyrosine phosphorylation (pY) after dasatinib exposure, employing a mass spectrometry (MS)-based quantitative phosphoproteomics approach. Overlaying protein-protein interaction relationships upon this dasatinib-regulated pY network revealed decreased phosphorylation of Src family kinases and their targets. Conversely, dasatinib enhanced tyrosine phosphorylation in a panel of receptor tyrosine kinases (RTK) and their signaling adaptor complexes, including EGFR, MET/GAB1, and IGF-1R/IRS2, implicating a RTK-driven adaptive response associated with dasatinib. To address the significance of this observation, these results were further integrated with results from a small molecule chemical library screen. We found that dasatinib combined with MET and IGF-1R inhibitors had a synergistic effect and ligand stimulation of EGFR and MET rescued DDR2-mutant lung SCC cells from dasatinib-induced loss of cell viability. Importantly, we observed high levels of tyrosine-phosphorylated EGFR and MET in a panel of human lung SCC tissues harboring DDR2 mutations. Our results highlight potential RTK-driven adaptive resistant mechanisms upon DDR2 targeting, and they suggest new, rationale co-targeting strategies for DDR2-mutant lung SCC.
PMCID: PMC4326029  PMID: 25348954
DDR2; phosphoproteomics; squamous cell lung cancer; dasatinib; adaptive response
13.  Tyrosine Kinase Syk Non-Enzymatic Inhibitors and Potential Anti-Allergic Drug-Like Compounds Discovered by Virtual and In Vitro Screening 
PLoS ONE  2011;6(6):e21117.
In the past decade, the spleen tyrosine kinase (Syk) has shown a high potential for the discovery of new treatments for inflammatory and autoimmune disorders. Pharmacological inhibitors of Syk catalytic site bearing therapeutic potential have been developed, with however limited specificity towards Syk. To address this topic, we opted for the design of drug-like compounds that could impede the interaction of Syk with its cellular partners while maintaining an active kinase protein. To achieve this challenging task, we used the powerful potential of intracellular antibodies for the modulation of cellular functions in vivo, combined to structure-based in silico screening. In our previous studies, we reported the anti-allergic properties of the intracellular antibody G4G11. With the aim of finding functional mimics of G4G11, we developed an Antibody Displacement Assay and we isolated the drug-like compound C-13, with promising in vivo anti-allergic activity. The likely binding cavity of this compound is located at the close vicinity of G4G11 epitope, far away from the catalytic site of Syk. Here we report the virtual screen of a collection of 500,000 molecules against this new cavity, which led to the isolation of 1000 compounds subsequently evaluated for their in vitro inhibitory effects using the Antibody Displacement Assay. Eighty five compounds were selected and evaluated for their ability to inhibit the liberation of allergic mediators from mast cells. Among them, 10 compounds inhibited degranulation with IC50 values ≤10 µM. The most bioactive compounds combine biological activity, significant inhibition of antibody binding and strong affinity for Syk. Moreover, these molecules show a good potential for oral bioavailability and are not kinase catalytic site inhibitors. These bioactive compounds could be used as starting points for the development of new classes of non-enzymatic inhibitors of Syk and for drug discovery endeavour in the field of inflammation related disorders.
PMCID: PMC3118801  PMID: 21701581
14.  Uncovering Molecular Bases Underlying Bone Morphogenetic Protein Receptor Inhibitor Selectivity 
PLoS ONE  2015;10(7):e0132221.
Abnormal alteration of bone morphogenetic protein (BMP) signaling is implicated in many types of diseases including cancer and heterotopic ossifications. Hence, small molecules targeting BMP type I receptors (BMPRI) to interrupt BMP signaling are believed to be an effective approach to treat these diseases. However, lack of understanding of the molecular determinants responsible for the binding selectivity of current BMP inhibitors has been a big hindrance to the development of BMP inhibitors for clinical use. To address this issue, we carried out in silico experiments to test whether computational methods can reproduce and explain the high selectivity of a small molecule BMP inhibitor DMH1 on BMPRI kinase ALK2 vs. the closely related TGF-β type I receptor kinase ALK5 and vascular endothelial growth factor receptor type 2 (VEGFR2) tyrosine kinase. We found that, while the rigid docking method used here gave nearly identical binding affinity scores among the three kinases; free energy perturbation coupled with Hamiltonian replica-exchange molecular dynamics (FEP/H-REMD) simulations reproduced the absolute binding free energies in excellent agreement with experimental data. Furthermore, the binding poses identified by FEP/H-REMD led to a quantitative analysis of physical/chemical determinants governing DMH1 selectivity. The current work illustrates that small changes in the binding site residue type (e.g. pre-hinge region in ALK2 vs. ALK5) or side chain orientation (e.g. Tyr219 in caALK2 vs. wtALK2), as well as a subtle structural modification on the ligand (e.g. DMH1 vs. LDN193189) will cause distinct binding profiles and selectivity among BMP inhibitors. Therefore, the current computational approach represents a new way of investigating BMP inhibitors. Our results provide critical information for designing exclusively selective BMP inhibitors for the development of effective pharmacotherapy for diseases caused by aberrant BMP signaling.
PMCID: PMC4489870  PMID: 26133550
15.  Targeted polypharmacology: Discovery of dual inhibitors of tyrosine and phosphoinositide kinases 
Nature chemical biology  2008;4(11):691-699.
The clinical success of multitargeted kinase inhibitors has stimulated efforts to identify promiscuous drugs with optimal selectivity profiles. It remains unclear to what extent such drugs can be rationally designed, particularly for combinations of targets that are structurally divergent. Here we report the systematic discovery of molecules that potently inhibit both tyrosine kinases and PI3-Ks, two protein families that are among the most intensely pursued cancer drug targets. Through iterative chemical synthesis, X-ray crystallography, and kinome-level biochemical profiling, we identify compounds that inhibit a spectrum of novel target combinations in these two families. Crystal structures reveal that the dual selectivity of these molecules is controlled by a hydrophobic pocket conserved in both enzyme classes and accessible through a rotatable bond in the drug skeleton. We show that one compound, PP121, blocks the proliferation of tumor cells by direct inhibition of oncogenic tyrosine kinases and PI3-Ks. These molecules demonstrate the feasibility of accessing a chemical space that intersects two families of oncogenes.
PMCID: PMC2880455  PMID: 18849971
Epidermal growth factor receptor (EGFR) protein tyrosine kinases (PTKs) are known for its role in cancer. Quinazoline have been reported to be the molecules of interest, with potent anticancer activity and they act by binding to ATP site of protein kinases. ATP binding site of protein kinases provides an extensive opportunity to design newer analogs. With this background, we report an attempt to discern the structural and physicochemical requirements for inhibition of EGFR tyrosine kinase. The k-Nearest Neighbor Molecular Field Analysis (kNN-MFA), a three dimensional quantitative structure activity relationship (3D- QSAR) method has been used in the present case to study the correlation between the molecular properties and the tyrosine kinase (EGFR) inhibitory activities on a series of quinazoline derivatives. kNNMFA calculations for both electrostatic and steric field were carried out. The master grid maps derived from the best model has been used to display the contribution of electrostatic potential and steric field. The statistical results showed significant correlation coefficient r2 (q2) of 0.846, r2 for external test set (pred_r2) 0.8029, coefficient of correlation of predicted data set (pred_r2se) of 0.6658, degree of freedom 89 and k nearest neighbor of 2. Therefore, this study not only casts light on binding mechanism between EGFR and its inhibitors, but also provides hints for the design of new EGFR inhibitors with observable structural diversity
PMCID: PMC3979194  PMID: 24825983
Quinazoline; Tyrosine kinase (E GFR); k-Nearest Neighbor Molecular Field Analysis (kNN-MFA)
17.  A Novel Quantitative Kinase Assay Using Bacterial Surface Display and Flow Cytometry 
PLoS ONE  2013;8(11):e80474.
The inhibition of tyrosine kinases is a successful approach for the treatment of cancers and the discovery of kinase inhibitor drugs is the focus of numerous academic and pharmaceutical laboratories. With this goal in mind, several strategies have been developed to measure kinase activity and to screen novel tyrosine kinase inhibitors. Nevertheless, a general non-radioactive and inexpensive approach, easy to implement and adapt to a range of applications, is still missing. Herein, using Bcr-Abl tyrosine kinase, an oncogenic target and a model protein for cancer studies, we describe a novel cost-effective high-throughput screening kinase assay. In this approach, named the BacKin assay, substrates displayed on a Bacterial cell surface are incubated with Kinase and their phosphorylation is examined and quantified by flow cytometry. This approach has several advantages over existing approaches, as using bacteria (i.e. Escherichia coli) to display peptide substrates provides a self renewing solid support that does not require laborious chemical strategies. Here we show that the BacKin approach can be used for kinetic and mechanistic studies, as well as a platform to characterize and identify small-molecule or peptide-based kinase inhibitors with potential applications in drug development.
PMCID: PMC3829888  PMID: 24260399
18.  Quantification and Kinetic Analysis of Grb2-EGFR Interaction on Micro-Patterned Surfaces for the Characterization of EGFR-Modulating Substances 
PLoS ONE  2014;9(3):e92151.
The identification of the epidermal growth factor receptor (EGFR) as an oncogene has led to the development of several anticancer therapeutics directed against this receptor tyrosine kinase. However, drug resistance and low efficacy remain a severe challenge, and have led to a demand for novel systems for an efficient identification and characterization of new substances. Here we report on a technique which combines micro-patterned surfaces and total internal reflection fluorescence (TIRF) microscopy (μ-patterning assay) for the quantitative analysis of EGFR activity. It does not simply measure the phosphorylation of the receptor, but instead quantifies the interaction of the key signal transmitting protein Grb2 (growth factor receptor-bound protein 2) with the EGFR in a live cell context. It was possible to demonstrate an EGF dependent recruitment of Grb2 to the EGFR, which was significantly inhibited in the presence of clinically tested EGFR inhibitors, including small tyrosine kinase inhibitors and monoclonal antibodies targeting the EGF binding site. Importantly, in addition to its potential use as a screening tool, our experimental setup offers the possibility to provide insight into the molecular mechanisms of bait-prey interaction. Recruitment of the EGFR together with Grb2 to clathrin coated pits (CCPs) was found to be a key feature in our assay. Application of bleaching experiments enabled calculation of the Grb2 exchange rate, which significantly changed upon stimulation or the presence of EGFR activity inhibiting drugs.
PMCID: PMC3962377  PMID: 24658383
19.  Targeting Tyrosine Kinases and Autophagy in Prostate Cancer 
Hormones & Cancer  2010;2(1):38-46.
Tyrosine kinases play significant roles in tumor progression and therapy resistance. Inhibitors of tyrosine kinases are on the forefront of targeted therapy. For prostate cancer, tyrosine kinases play an additional role in the development of castration-resistant disease state, the most troubling aspect of prostate cancinogenesis which presently defies any effective treatment. Among the 30 or so tyrosine kinases expressed in a typical prostate cancer cell, nearly one third of them have been implicated in prostate carcinogenesis. Interestingly, most of them channel signals through a trio of non-receptor tyrosine kinases, Src/Etk/FAK, referred here as Src tyrosine kinase complex. This complex has been shown to play a significant role in the aberrant activation of androgen receptor (AR) mediated by growth factors (e.g., epidermal growth factor (EGF)), cytokines (interleukin (IL)-6), chemokines (IL-8), and neurokines (gastrin-releasing peptide). These factors are induced and released from the prostate cancer to the stromal cells upon androgen withdrawal. The Src kinase complex has the ability to phosphorylate androgen receptor, resulting in the nuclear translocation and stabilization of un-liganded androgen receptor. Indeed, tyrosine kinase inhibitors targeting Src can inhibit androgen-independent growth of prostate cancer cells in vitro and in preclinical xenograft model. While effective in inducing growth arrest and inhibiting metastasis of castration-resistant tumors, Src inhibitors rarely induce a significant level of apoptosis. This is also reflected by the general ineffectiveness of tyrosine kinase inhibitors as monotherapy in clinical trials. One of the underlying causes of apoptosis resistance is “autophagy,” which is induced by tyrosine kinase inhibitors and by androgen withdrawal. Autophagy is a self-digesting process to regenerate energy by removal of long-lived proteins and retired organelles to provide a survival mechanism to cells encountering stresses. Excessive autophagy, sometimes, could lead to type II programmed cell death. We demonstrated that autophagy blockade sensitizes prostate cancer cells toward Src tyrosine kinase inhibitor. Thus, a combination therapy based on Src tyrosine kinase inhibitor and autophagy modulator deserves further attention as a potential treatment for relapsed prostate cancer.
PMCID: PMC3020299  PMID: 21350583
Androgen receptor; Tyrosine kinase; Prostate Cancer; Autophagy; Src
20.  Data-Driven Modeling of Src Control on the Mitochondrial Pathway of Apoptosis: Implication for Anticancer Therapy Optimization 
PLoS Computational Biology  2013;9(4):e1003011.
Src tyrosine kinases are deregulated in numerous cancers and may favor tumorigenesis and tumor progression. We previously described that Src activation in NIH-3T3 mouse fibroblasts promoted cell resistance to apoptosis. Indeed, Src was found to accelerate the degradation of the pro-apoptotic BH3-only protein Bik and compromised Bax activation as well as subsequent mitochondrial outer membrane permeabilization. The present study undertook a systems biomedicine approach to design optimal anticancer therapeutic strategies using Src-transformed and parental fibroblasts as a biological model. First, a mathematical model of Bik kinetics was designed and fitted to biological data. It guided further experimental investigation that showed that Bik total amount remained constant during staurosporine exposure, and suggested that Bik protein might undergo activation to induce apoptosis. Then, a mathematical model of the mitochondrial pathway of apoptosis was designed and fitted to experimental results. It showed that Src inhibitors could circumvent resistance to apoptosis in Src-transformed cells but gave no specific advantage to parental cells. In addition, it predicted that inhibitors of Bcl-2 antiapoptotic proteins such as ABT-737 should not be used in this biological system in which apoptosis resistance relied on the deficiency of an apoptosis accelerator but not on the overexpression of an apoptosis inhibitor, which was experimentally verified. Finally, we designed theoretically optimal therapeutic strategies using the data-calibrated model. All of them relied on the observed Bax overexpression in Src-transformed cells compared to parental fibroblasts. Indeed, they all involved Bax downregulation such that Bax levels would still be high enough to induce apoptosis in Src-transformed cells but not in parental ones. Efficacy of this counterintuitive therapeutic strategy was further experimentally validated. Thus, the use of Bax inhibitors might be an unexpected way to specifically target cancer cells with deregulated Src tyrosine kinase activity.
Author Summary
Personalizing medicine on a molecular basis has proven its clinical benefits. The molecular study of the patient's tumor and healthy tissues allowed the identification of determinant mutations and the subsequent optimization of healthy and cancer cells specific response to treatments. Here, we propose a combined mathematical and experimental approach for the design of optimal therapeutics strategies tailored to the patient molecular profile. As an in vitro proof of concept, we used parental and Src-transformed NIH-3T3 fibroblasts as a biological model. Experimental study at a molecular level of those two cell populations demonstrated differences in the gene expression of key-controllers of the mitochondrial pathway of apoptosis thus suggesting potential therapeutic targets. Molecular mathematical models were built and fitted to existing experimental data. They guided further experimental investigation of the kinetics of the mitochondrial pathway of apoptosis which allowed their refinement. Finally, optimization procedures were applied to those data-calibrated models to determine theoretically optimal therapeutic strategies that would maximize the anticancer efficacy on Src-transformed cells under the constraint of a maximal allowed toxicity on parental cells.
PMCID: PMC3616992  PMID: 23592961
21.  Building and exploring an integrated human kinase network: Global organization and medical entry points☆ 
Journal of Proteomics  2014;107(100):113-127.
Biological matter is organized in functional networks of different natures among which kinase–substrate and protein–protein interactions play an important role. Large public data collections allowed us to compile an important corpus of interaction data around human protein kinases. One of the most interesting observations analyzing this network is that coherence in kinase functional activity relies on kinase substrate interactions primarily and not on which protein complexes are formed around them. Further dissecting the two types of interactions at the level of kinase groups (CMGCs, Tyrosine kinases, etc.) we show a prevalence of intra-group interconnectivity, which we can naturally relate to current scenarios of evolution of biological networks. Tracking publication dates we observe high correlation of kinase interaction research focus with general kinase research. We find a similar bias in the targets of kinase inhibitors that feature high redundancy. Finally, intersecting kinase inhibitor specificity with sets of kinases located at specific positions in the kinase network, we propose alternative options for future therapeutic strategies using these compounds.
Biological significance
Despite its importance for cellular regulation and the fact that protein kinases feature prominent targets of modern therapeutic approaches, the structure and logic of the global, integrated protein phosphorylation network have not been investigated intensively. To focus on the regulatory skeleton of the phosphorylation network, we contemplated a network consisting of kinases, their substrates, and publicly available physical protein interactions. Analysis of this network at multiple levels allowed establishing a series of interesting properties such as prevalence of kinase substrate interactions as opposed to general protein–protein interactions for establishing a holistic control over kinases activities. Kinases controlling many or a few only other kinases, in addition to non-kinases, were distributed in cellular compartments differently. They were also targeted by kinase inhibitors with distinct success rates. Non-kinases tightly regulated by a large number of kinases were involved in biological processes both specific and shared with their regulators while being preferably localized in the nucleus. Collectively, these observations may provide for a new perspective in the elaboration of pharmacological intervention strategies. We complemented our study of kinase interactions with a perspective of how this type of data is generated in comparison with general research about those enzymes. Namely, what was the temporal evolution of the research community attention for interaction versus non-interaction-based kinase experiments.
This article is part of a Special Issue entitled: 20 years of Proteomics in memory of Vitaliano Pallini. Guest Editors: Luca Bini, Juan J. Calvete, Natacha Turck, Denis Hochstrasser and Jean-Charles Sanchez.
Graphical abstract
•Comparison of human kinase–protein and kinase–substrate networks•Prevalence of kinase–substrate interactions•Relationship with kinase inhibitors•Potential new therapeutic approaches•How does kinase interaction research focuses its research.
PMCID: PMC4115268  PMID: 24704859
Bioinformatics; Kinases; Network; System biology; Drugs
22.  Profiling the tyrosine phosphoproteome of different mouse mammary tumour models reveals distinct, model-specific signalling networks and conserved oncogenic pathways 
Although aberrant tyrosine kinase signalling characterises particular breast cancer subtypes, a global analysis of tyrosine phosphorylation in mouse models of breast cancer has not been undertaken to date. This may identify conserved oncogenic pathways and potential therapeutic targets.
We applied an immunoaffinity/mass spectrometry workflow to three mouse models: murine stem cell virus-Neu, expressing truncated Neu, the rat orthologue of human epidermal growth factor receptor 2, Her2 (HER2); mouse mammary tumour virus-polyoma virus middle T antigen (PyMT); and the p53−/− transplant model (p53). Pathways and protein–protein interaction networks were identified by bioinformatics analysis. Molecular mechanisms underpinning differences in tyrosine phosphorylation were characterised by Western blot analysis and array comparative genomic hybridisation. The functional role of mesenchymal–epithelial transition factor (Met) in a subset of p53-null tumours was interrogated using a selective tyrosine kinase inhibitor (TKI), small interfering RNA (siRNA)–mediated knockdown and cell proliferation assays.
The three models could be distinguished on the basis of tyrosine phosphorylation signatures and signalling networks. HER2 tumours exhibited a protein–protein interaction network centred on avian erythroblastic leukaemia viral oncogene homologue 2 (Erbb2), epidermal growth factor receptor and platelet-derived growth factor receptor α, and they displayed enhanced tyrosine phosphorylation of ERBB receptor feedback inhibitor 1. In contrast, the PyMT network displayed significant enrichment for components of the phosphatidylinositol 3-kinase signalling pathway, whereas p53 tumours exhibited increased tyrosine phosphorylation of Met and components or regulators of the cytoskeleton and shared signalling network characteristics with basal and claudin-low breast cancer cells. A subset of p53 tumours displayed markedly elevated cellular tyrosine phosphorylation and Met expression, as well as Met gene amplification. Treatment of cultured p53-null cells exhibiting Met amplification with a selective Met TKI abrogated aberrant tyrosine phosphorylation and blocked cell proliferation. The effects on proliferation were recapitulated when Met was knocked down using siRNA. Additional subtypes of p53 tumours exhibited increased tyrosine phosphorylation of other oncogenes, including Peak1/SgK269 and Prex2.
This study provides network-level insights into signalling in the breast cancer models utilised and demonstrates that comparative phosphoproteomics can identify conserved oncogenic signalling pathways. The Met-amplified, p53-null tumours provide a new preclinical model for a subset of triple-negative breast cancers.
Electronic supplementary material
The online version of this article (doi:10.1186/s13058-014-0437-3) contains supplementary material, which is available to authorized users.
PMCID: PMC4303118  PMID: 25200860
23.  KRAS Testing for Anti-EGFR Therapy in Advanced Colorectal Cancer 
Executive Summary
In February 2010, the Medical Advisory Secretariat (MAS) began work on evidence-based reviews of the literature surrounding three pharmacogenomic tests. This project came about when Cancer Care Ontario (CCO) asked MAS to provide evidence-based analyses on the effectiveness and cost-effectiveness of three oncology pharmacogenomic tests currently in use in Ontario.
Evidence-based analyses have been prepared for each of these technologies. These have been completed in conjunction with internal and external stakeholders, including a Provincial Expert Panel on Pharmacogenomics (PEPP). Within the PEPP, subgroup committees were developed for each disease area. For each technology, an economic analysis was also completed by the Toronto Health Economics and Technology Assessment Collaborative (THETA) and is summarized within the reports.
The following reports can be publicly accessed at the MAS website at: or at
Gene Expression Profiling for Guiding Adjuvant Chemotherapy Decisions in Women with Early Breast Cancer: An Evidence-Based and Economic Analysis
Epidermal Growth Factor Receptor Mutation (EGFR) Testing for Prediction of Response to EGFR-Targeting Tyrosine Kinase Inhibitor (TKI) Drugs in Patients with Advanced Non-Small-Cell Lung Cancer: an Evidence-Based and Economic Analysis
K-RAS testing in Treatment Decisions for Advanced Colorectal Cancer: an Evidence-Based and Economic Analysis.
The objective of this systematic review is to determine the predictive value of KRAS testing in the treatment of metastatic colorectal cancer (mCRC) with two anti-EGFR agents, cetuximab and panitumumab. Economic analyses are also being conducted to evaluate the cost-effectiveness of KRAS testing.
Clinical Need: Condition and Target Population
Metastatic colorectal cancer (mCRC) is usually defined as stage IV disease according to the American Joint Committee on Cancer tumour node metastasis (TNM) system or stage D in the Duke’s classification system. Patients with advanced colorectal cancer (mCRC) either present with metastatic disease or develop it through disease progression.
KRAS (Kristen-RAS, a member of the rat sarcoma virus (ras) gene family of oncogenes) is frequently mutated in epithelial cancers such as colorectal cancer, with mutations occurring in mutational hotspots (codons 12 and 13) of the KRAS protein. Involved in EGFR-mediated signalling of cellular processes such as cell proliferation, resistance to apoptosis, enhanced cell motility and neoangiogenesis, a mutation in the KRAS gene is believed to be involved in cancer pathogenesis. Such a mutation is also hypothesized to be involved in resistance to targeted anti-EGFR (epidermal growth factor receptor with tyrosine kinase activity) treatments such as cetuximab and panitumumab, hence, the important in evaluating the evidence on the predictive value of KRAS testing in this context.
KRAS Mutation Testing in Advanced Colorectal Cancer
Both cetuximab and panitumumab are indicated by Health Canada in the treatment of patients with metastatic colorectal cancer whose tumours are WT for the KRAS gene. Cetuximab may be offered as monotherapy in patients intolerant to irinotecan-based chemotherapy or in patients who have failed both irinotecan and oxaliplatin-based regimens and who received a fluoropyrimidine. It can also be administered in combination with irinotecan in patients refractory to other irinotecan-based chemotherapy regimens. Panitumumab is only indicated as a single agent after failure of fluoropyrimidine-, oxaliplatin-, and irinotecan-containing chemotherapy regimens.
In Ontario, patients with advanced colorectal cancer who are refractory to chemotherapy may be offered the targeted anti-EGFR treatments cetuximab or panitumumab. Eligibility for these treatments is based on the KRAS status of their tumour, derived from tissue collected from surgical or biopsy specimens. It is believed that KRAS status is not affected by treatments, therefore, for patients for whom surgical tissue is available for KRAS testing, additional biopsies prior to treatment with these targeted agents is not necessary. For patients that have not undergone surgery or for whom surgical tissue is not available, a biopsy of either the primary or metastatic site is required to determine their KRAS status. This is possible as status at the metastatic and primary tumour sites is considered to be similar.
Research Question
To determine if there is predictive value of KRAS testing in guiding treatment decisions with anti-EGFR targeted therapies in advanced colorectal cancer patients refractory to chemotherapy.
Research Methods
Literature Search
The Medical Advisory Secretariat followed its standard procedures and on May 18, 2010, searched the following electronic databases: Ovid MEDLINE, EMBASE, Ovid MEDLINE In-Process & Other Non-Indexed Citations, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews and The International Network of Agencies for Health Technology Assessment database.
The subject headings and keywords searched included colorectal cancer, cetuximab, panitumumab, and KRAS testing. The search was further restricted to English-language articles published between January 1, 2009 and May 18, 2010 resulting in 1335 articles for review. Excluded were case reports, comments, editorials, nonsystematic reviews, and letters. Studies published from January 1, 2005 to December 31, 2008 were identified in a health technology assessment conducted by the Agency for Healthcare Research and Quality (AHRQ), published in 2010. In total, 14 observational studies were identified for inclusion in this EBA: 4 for cetuximab monotherapy, 7 for the cetuximab-irinotecan combination therapy, and 3 to be included in the review for panitumumab monotherapy
Inclusion Criteria
English-language articles, and English or French-language HTAs published from January 2005 to May 2010, inclusive.
Randomized controlled trials (RCTs) or observational studies, including single arm treatment studies that include KRAS testing.
Studies with data on main outcomes of interest, overall and progression-free survival.
Studies of third line treatment with cetuximab or panitumumab in patients with advanced colorectal cancer refractory to chemotherapy.
For the cetuximab-irinotecan evaluation, studies in which at least 70% of patients in the study received this combination therapy.
Exclusion Criteria
Studies whose entire sample was included in subsequent publications which have been included in this EBA.
Studies in pediatric populations.
Case reports, comments, editorials, or letters.
Outcomes of Interest
Overall survival (OS), median
Progression-free-survival (PFS), median.
Response rates.
Adverse event rates.
Quality of life (QOL).
Summary of Findings of Systematic Review
Cetuximab or Panitumumab Monotherapy
Based on moderate GRADE observational evidence, there is improvement in PFS and OS favouring patients without the KRAS mutation (KRAS wildtype, or KRAS WT) compared to those with the mutation.
Cetuximab-Irinotecan Combination Therapy
There is low GRADE evidence that testing for KRAS may optimize survival benefits in patients without the KRAS mutation (KRAS wildtype, or KRAS WT) compared to those with the mutation.
However, cetuximab-irinotecan combination treatments based on KRAS status discount any effect of cetuximab in possibly reversing resistance to irinotecan in patients with the mutation, as observed effects were lower than for patients without the mutation. Clinical experts have raised concerns about the biological plausibility of this observation and this conclusion would, therefore, be regarded as hypothesis generating.
Economic Analysis
Cost-effectiveness and budget impact analyses were conducted incorporating estimates of effectiveness from this systematic review. Evaluation of relative cost-effectiveness, based on a decision-analytic cost-utility analysis, assessed testing for KRAS genetic mutations versus no testing in the context of treatment with cetuximab monotherapy, panitumumab monotherapy, cetuximab in combination with irinotecan, and best supportive care.
Of importance to note is that the cost-effectiveness analysis focused on the impact of testing for KRAS mutations compared to no testing in the context of different treatment options, and does not assess the cost-effectiveness of the drug treatments alone.
KRAS status is predictive of outcomes in cetuximab and panitumumab monotherapy, and in cetuximab-irinotecan combination therapy.
While KRAS testing is cost-effective for all strategies considered, it is not equally cost-effective for all treatment options.
PMCID: PMC3377508  PMID: 23074403
24.  Combined HSP90 and kinase inhibitor therapy: Insights from The Cancer Genome Atlas 
Cell Stress & Chaperones  2015;20(5):729-741.
The merging of knowledge from genomics, cellular signal transduction and molecular evolution is producing new paradigms of cancer analysis. Protein kinases have long been understood to initiate and promote malignant cell growth and targeting kinases to fight cancer has been a major strategy within the pharmaceutical industry for over two decades. Despite the initial success of kinase inhibitors (KIs), the ability of cancer to evolve resistance and reprogram oncogenic signaling networks has reduced the efficacy of kinase targeting. The molecular chaperone HSP90 physically supports global kinase function while also acting as an evolutionary capacitor. The Cancer Genome Atlas (TCGA) has compiled a trove of data indicating that a large percentage of tumors overexpress or possess mutant kinases that depend on the HSP90 molecular chaperone complex. Moreover, the overexpression or mutation of parallel activators of kinase activity (PAKA) increases the number of components that promote malignancy and indirectly associate with HSP90. Therefore, targeting HSP90 is predicted to complement kinase inhibitors by inhibiting oncogenic reprogramming and cancer evolution. Based on this hypothesis, consideration should be given by both the research and clinical communities towards combining kinase inhibitors and HSP90 inhibitors (H90Ins) in combating cancer. The purpose of this perspective is to reflect on the current understanding of HSP90 and kinase biology as well as promote the exploration of potential synergistic molecular therapy combinations through the utilization of The Cancer Genome Atlas.
Electronic supplementary material
The online version of this article (doi:10.1007/s12192-015-0604-1) contains supplementary material, which is available to authorized users.
PMCID: PMC4529871  PMID: 26070366
Cancer; Drug resistance; HSP90; Kinase; Evolution; TCGA
25.  Staurosporine-derived inhibitors broaden the scope of analog-sensitive kinase technology 
Journal of the American Chemical Society  2013;135(48):18153-18159.
Analog-sensitive (AS) kinase technology is a powerful approach for studying phospho-signaling pathways in diverse organisms and physiological processes. The key feature of this technique is that a kinase-of-interest can be mutated to sensitize it to inhibitor analogs that do not target wild-type (WT) kinases. In theory, this enables specific inhibition of any kinase in cells and in mouse models of human disease. Typically these inhibitors are identified from a small library of molecules based on the pyrazolopyrimidine (PP) scaffold. However, we recently identified a subset of native human kinases, including the Ephrin A kinase family, that are sensitive to commonly used PP inhibitors. In an effort to develop a bioorthogonal AS-kinase inhibitor and to extend this technique to PP-sensitive kinases we sought an alternative inhibitor scaffold. Here we report the structure-based design of synthetically tractable, potent, and extremely selective AS-kinase inhibitors based on the natural product staurosporine. We demonstrate that these molecules, termed staralogs, potently target AS kinases in cells and we employ X-ray crystallography to elucidate their mechanism of efficacy. Finally, we demonstrate that staralogs target AS mutants of PP-sensitive kinases at concentrations where there is little to no inhibition of native human kinases. Thus, staralogs represent a new class of AS-kinase inhibitors and a core component of the chemical genetic tool kit for probing kinase-signaling pathways.
PMCID: PMC3938282  PMID: 24171479

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