Comparative kinase and cancer cell panel profiling of kinase inhibitors approved for clinical use from 2018 to 2020.

During the last two decades, kinase inhibitors have become the major drug class for targeted cancer therapy. Although the number of approved kinase inhibitors increases rapidly, comprehensive in vitro profiling and comparison of inhibitor activities is often lacking in the public domain. Here we report the extensive profiling and comparison of 21 kinase inhibitors approved by the FDA for oncology indications since June 2018 and 13 previously approved comparators on panels of 255 biochemical kinase assays and 134 cancer cell line viability assays. Comparison of the cellular inhibition profiles of the EGFR inhibitors gefitinib, dacomitinib, and osimertinib identified the uncommon EGFR p.G719S mutation as a common response marker for EGFR inhibitors. Additionally, the FGFR inhibitors erdafitinib, infigratinib, and pemigatinib potently inhibited the viability of cell lines which harbored oncogenic alterations in FGFR1-3, irrespective of the specific clinical indications of the FGFR inhibitors. These results underscore the utility of in vitro kinase inhibitor profiling in cells for identifying new potential stratification markers for patient selection. Furthermore, comparison of the in vitro inhibition profiles of the RET inhibitors pralsetinib and selpercatinib revealed they had very similar biochemical and cellular selectivity. As an exception, an NTRK3 fusion-positive cell line was potently inhibited by pralsetinib but not by selpercatinib, which could be explained by the targeting of TRK kinases in biochemical assays by pralsetinib but not selpercatinib. This illustrates that unexpected differences in cellular activities between inhibitors that act through the same primary target can be explained by subtle differences in biochemical targeting. Lastly, FLT3-mutant cell lines were responsive to both FLT3 inhibitors gilteritinib and midostaurin, and the PI3K inhibitor duvelisib. Biochemical profiling revealed that the FLT3 and PI3K inhibitors targeted distinct kinases, indicating that unique dependencies can be identified by combined biochemical and cellular profiling of kinase inhibitors. This study provides the first large scale kinase assay or cell panel profiling study for newly approved kinase inhibitors, and shows that comprehensive in vitro profiling of kinase inhibitors can provide rationales for therapy selection and indication expansion of approved kinase inhibitors.

Pharmacological validation of TDO as a target for Parkinson's disease.

Parkinson's disease patients suffer from both motor and nonmotor impairments. There is currently no cure for Parkinson's disease, and the most commonly used treatment, levodopa, only functions as a temporary relief of motor symptoms. Inhibition of the expression of the L-tryptophan-catabolizing enzyme tryptophan 2,3-dioxygenase (TDO) has been shown to inhibit aging-related α-synuclein toxicity in Caenorhabditis elegans. To evaluate TDO inhibition as a potential therapeutic strategy for Parkinson's disease, a brain-penetrable, small molecule TDO inhibitor was developed, referred to as NTRC 3531-0. This compound potently inhibits human and mouse TDO in biochemical and cell-based assays and is selective over IDO1, an evolutionary unrelated enzyme that catalyzes the same reaction. In mice, NTRC 3531-0 increased plasma and brain L-tryptophan levels after oral administration, demonstrating inhibition of TDO activity in vivo. The effect on Parkinson's disease symptoms was evaluated in a rotenone-induced Parkinson's disease mouse model. A structurally dissimilar TDO inhibitor, LM10, was evaluated in parallel. Both inhibitors had beneficial effects on rotenone-induced motor and cognitive dysfunction as well as rotenone-induced dopaminergic cell loss and neuroinflammation in the substantia nigra. Moreover, both inhibitors improved intestinal transit and enhanced colon length, which indicates a reduction of the rotenone-induced intestinal dysfunction. Consistent with this, mice treated with TDO inhibitor showed decreased expression of rotenone-induced glial fibrillary acidic protein, which is a marker of enteric glial cells, and decreased α-synuclein accumulation in the enteric plexus. Our data support TDO inhibition as a potential therapeutic strategy to decrease motor, cognitive, and gastrointestinal symptoms in Parkinson's disease.

Structural insights into human Arginase-1 pH dependence and its inhibition by the small molecule inhibitor CB-1158.

Arginase-1 is a manganese-dependent metalloenzyme that catalyzes the hydrolysis of L-arginine into L-ornithine and urea. Arginase-1 is abundantly expressed by tumor-infiltrating myeloid cells that promote tumor immunosuppression, which is relieved by inhibition of Arginase-1. We have characterized the potencies of the Arginase-1 reference inhibitors (2S)-2-amino-6-boronohexanoic acid (ABH) and N ω-hydroxy-nor-L-arginine (nor-NOHA), and studied their pH-dependence and binding kinetics. To gain a better understanding of the structural changes underlying the high pH optimum of Arginase-1 and its pH-dependent inhibition, we determined the crystal structure of the human Arginase-1/ABH complex at pH 7.0 and 9.0. These structures revealed that at increased pH, the manganese cluster assumes a more symmetrical coordination structure, which presumably contributes to its increase in catalytic activity. Furthermore, we show that binding of ABH involves the presence of a sodium ion close to the manganese cluster. We also studied the investigational new drug CB-1158 (INCB001158). This inhibitor has a low-nanomolar potency at pH 7.4 and increases the thermal stability of Arginase-1 more than ABH and nor-NOHA. Moreover, CB-1158 displays slow association and dissociation kinetics at both pH 9.5 and 7.4, as indicated by surface plasmon resonance. The potent character of CB-1158 is presumably due to its increased rigidity compared to ABH as well as the formation of an additional hydrogen-bond network as observed by resolution of the Arginase-1/CB-1158 crystal structure.

High-Throughput Fluorescence-Based Activity Assay for Arginase-1.

Arginase-1, which converts the amino acid L-arginine into L-ornithine and urea, is a promising new drug target for cancer immunotherapy, as it has a role in the regulation of T-cell immunity in the tumor microenvironment. To enable the discovery of small-molecule Arginase-1 inhibitors by high-throughput screening, we developed a novel homogeneous (mix-and-measure) fluorescence-based activity assay. The assay measures the conversion of L-arginine into L-ornithine by a decrease in fluorescent signal due to quenching of a fluorescent probe, Arginase Gold. This way, inhibition of Arginase-1 results in a gain of signal when compared with the uninhibited enzyme. Side-by-side profiling of reference inhibitors in the fluorescence-based assay and a colorimetric urea formation assay revealed similar potencies and the same potency rank order among the two assay formats. The fluorescence-based assay was successfully automated for high-throughput screening of a small-molecule library in 384-well format with a good Z'-factor and hit confirmation rate. Finally, we show that the assay can be used to study the binding kinetics of inhibitors.

Targeting Indoleamine 2,3-Dioxygenase in Cancer Models Using the Novel Small Molecule Inhibitor NTRC 3883-0.

Indoleamine 2,3-dioxygenase (IDO1) is a key regulator of immune suppression by catalyzing the oxidation of L-tryptophan. IDO1 expression has been related to poor prognosis in several cancers and to resistance to checkpoint immunotherapies. We describe the characterization of a novel small molecule IDO1 inhibitor, NTRC 3883-0, in a panel of biochemical and cell-based assays, and various cancer models. NTRC 3883-0 released the inhibitory effect of IDO1 on CD8-positive T cell proliferation in co-cultures of IDO1-overexpressing cells with healthy donor lymphocytes, demonstrating its immune modulatory activity. In a syngeneic mouse model using IDO1-overexpressing B16F10 melanoma cells, NTRC 3883-0 effectively counteracted the IDO1-induced modulation of L-tryptophan and L-kynurenine levels, demonstrating its in vivo target modulation. Finally, we studied the expression and activity of IDO1 in primary cell cultures established from the malignant ascites of ovarian cancer patients. In these cultures, IDO1 expression was induced upon stimulation with IFNγ, and its activity could be inhibited by NTRC 3883-0. Based on these results, we propose the use of ascites cell-based functional assays for future patient stratification. Our results are discussed in light of the recent discontinuation of clinical trials of more advanced IDO1 inhibitors and the reconsideration of IDO1 as a valid drug target.

Combined Cellular and Biochemical Profiling to Identify Predictive Drug Response Biomarkers for Kinase Inhibitors Approved for Clinical Use between 2013 and 2017.

Kinase inhibitors form the largest class of precision medicine. From 2013 to 2017, 17 have been approved, with 8 different mechanisms. We present a comprehensive profiling study of all 17 inhibitors on a biochemical assay panel of 280 kinases and proliferation assays of 108 cancer cell lines. Drug responses of the cell lines were related to the presence of frequently recurring point mutations, insertions, deletions, and amplifications in 15 well-known oncogenes and tumor-suppressor genes. In addition, drug responses were correlated with basal gene expression levels with a focus on 383 clinically actionable genes. Cell lines harboring actionable mutations defined in the FDA labels, such as mutant BRAF(V600E) for cobimetinib, or ALK gene translocation for ALK inhibitors, are generally 10 times more sensitive compared with wild-type cell lines. This sensitivity window is more narrow for markers that failed to meet endpoints in clinical trials, for instance CDKN2A loss for CDK4/6 inhibitors (2.7-fold) and KRAS mutation for cobimetinib (2.3-fold). Our data underscore the rationale of a number of recently opened clinical trials, such as ibrutinib in ERBB2- or ERBB4-expressing cancers. We propose and validate new response biomarkers, such as mutation in FBXW7 or SMAD4 for EGFR and HER2 inhibitors, ETV4 and ETV5 expression for MEK inhibitors, and JAK3 expression for ALK inhibitors. Potentially, these new markers could be combined to improve response rates. This comprehensive overview of biochemical and cellular selectivities of approved kinase inhibitor drugs provides a rich resource for drug repurposing, basket trial design, and basic cancer research.

TTK Inhibitors as a Targeted Therapy for CTNNB1 (ß-catenin) Mutant Cancers.

The spindle assembly checkpoint kinase TTK (Mps1) is a key regulator of chromosome segregation and is the subject of novel targeted therapy approaches by small-molecule inhibitors. Although the first TTK inhibitors have entered phase I dose escalating studies in combination with taxane chemotherapy, a patient stratification strategy is still missing. With the aim to identify a genomic biomarker to predict the response of tumor cells to TTK inhibitor therapy, we profiled a set of preclinical and clinical TTK inhibitors from different chemical series on a panel of 66 genetically characterized cell lines derived from different tumors (Oncolines). Cell lines harboring activating mutations in the CTNNB1 gene, encoding the Wnt pathway signaling regulator ß-catenin, were on average up to five times more sensitive to TTK inhibitors than cell lines wild-type for CTNNB1 The association of CTNNB1-mutant status and increased cancer cell line sensitivity to TTK inhibition was confirmed with isogenic cell line pairs harboring either mutant or wild-type CTNNB1 Treatment of a xenograft model of a CTNNB1-mutant cell line with the TTK inhibitor NTRC 0066-0 resulted in complete inhibition of tumor growth. Mutations in CTNNB1 occur at relatively high frequency in endometrial cancer and hepatocellular carcinoma, which are known to express high TTK levels. We propose mutant CTNNB1 as a prognostic drug response biomarker, enabling the selection of patients most likely to respond to TTK inhibitor therapy in proof-of-concept clinical trials. Mol Cancer Ther; 16(11); 2609-17. ©2017 AACR.

Target Residence Time-Guided Optimization on TTK Kinase Results in Inhibitors with Potent Anti-Proliferative Activity.

The protein kinase threonine tyrosine kinase (TTK; also known as Mps1) is a critical component of the spindle assembly checkpoint and a promising drug target for the treatment of aggressive cancers, such as triple negative breast cancer. While the first TTK inhibitors have entered clinical trials, little is known about how the inhibition of TTK with small-molecule compounds affects cellular activity. We studied the selective TTK inhibitor NTRC 0066-0, which was developed in our own laboratory, together with 11 TTK inhibitors developed by other companies, including Mps-BAY2b, BAY 1161909, BAY 1217389 (Bayer), TC-Mps1-12 (Shionogi), and MPI-0479605 (Myrexis). Parallel testing shows that the cellular activity of these TTK inhibitors correlates with their binding affinity to TTK and, more strongly, with target residence time. TTK inhibitors are therefore an example where target residence time determines activity in in vitro cellular assays. X-ray structures and thermal stability experiments reveal that the most potent compounds induce a shift of the glycine-rich loop as a result of binding to the catalytic lysine at position 553. This "lysine trap" disrupts the catalytic machinery. Based on these insights, we developed TTK inhibitors, based on a (5,6-dihydro)pyrimido[4,5-e]indolizine scaffold, with longer target residence times, which further exploit an allosteric pocket surrounding Lys553. Their binding mode is new for kinase inhibitors and can be classified as hybrid Type I/Type III. These inhibitors have very potent anti-proliferative activity that rivals classic cytotoxic therapy. Our findings will open up new avenues for more applications for TTK inhibitors in cancer treatment.

Stable aneuploid tumors cells are more sensitive to TTK inhibition than chromosomally unstable cell lines.

Inhibition of the spindle assembly checkpoint kinase TTK causes chromosome mis-segregation and tumor cell death. However, high levels of TTK correlate with chromosomal instability (CIN), which can lead to aneuploidy. We show that treatment of tumor cells with the selective small molecule TTK inhibitor NTRC 0066-0 overrides the mitotic checkpoint, irrespective of cell line sensitivity. In stable aneuploid cells NTRC 0066-0 induced acute CIN, whereas in cells with high levels of pre-existing CIN there was only a small additional fraction of cells mis-segregating their chromosomes. In proliferation assays stable aneuploid cells were more sensitive than cell lines with pre-existing CIN. Tetraploids are thought to be an intermediate between diploid and unstable aneuploid cells. TTK inhibitors had the same potency on post-tetraploid and parental diploid cells, which is remarkable because the post-tetraploids are more resistant to mitotic drugs. Finally, we confirm that the reference compound reversine is a TTK inhibitor and like NTRC 0066-0, inhibits the proliferation of patient-derived colorectal cancer organoids. In contrast, treatment with TTK inhibitor did not reduce the viability of non-proliferating T cell acute lymphoblastic leukemia cells samples. Consequently, TTK inhibitor therapy is expected to spare non-dividing cells, and may be used to target stable aneuploid tumors.

Compound Selectivity and Target Residence Time of Kinase Inhibitors Studied with Surface Plasmon Resonance.

Target residence time (τ) has been suggested to be a better predictor of the biological activity of kinase inhibitors than inhibitory potency (IC50) in enzyme assays. Surface plasmon resonance binding assays for 46 human protein and lipid kinases were developed. The association and dissociation constants of 80 kinase inhibitor interactions were determined. τ and equilibrium affinity constants (KD) were calculated to determine kinetic selectivity. Comparison of τ and KD or IC50 values revealed a strikingly different view on the selectivity of several kinase inhibitors, including the multi-kinase inhibitor ponatinib, which was tested on 10 different kinases. In addition, known pan-Aurora inhibitors resided much longer on Aurora B than on Aurora A, despite having comparable affinity for Aurora A and B. Furthermore, the γ/δ-selective PI3K inhibitor duvelisib and the δ-selective drug idelalisib had similar 20-fold selectivity for δ- over γ-isoform but duvelisib resided much longer on both targets.

Identification of an evolutionary conserved structural loop that is required for the enzymatic and biological function of tryptophan 2,3-dioxygenase.

The enzyme TDO (tryptophan 2,3-dioxygenase; TDO-2 in Caenorhabditis elegans) is a potential therapeutic target to cancer but is also thought to regulate proteotoxic events seen in the progression of neurodegenerative diseases. To better understand its function and develop specific compounds that target TDO we need to understand the structure of this molecule. In C. elegans we compared multiple different CRISPR/Cas9-induced tdo-2 deletion mutants and identified a motif of three amino acids (PLD) that is required for the enzymatic conversion of tryptophan to N-formylkynurenine. Loss of TDO-2's enzymatic activity in PDL deletion mutants was accompanied by an increase in motility during aging and a prolonged lifespan, which is in line with the previously observed phenotypes induced by a knockdown of the full enzyme. Comparison of sequence structures suggests that blocking this motif might interfere with haem binding, which is essential for the enzyme's activity. The fact that these three residues are situated in an evolutionary conserved structural loop of the enzyme suggests that the findings can be translated to humans. The identification of this specific loop region in TDO-2-essential for its catalytic function-will aid in the design of novel inhibitors to treat diseases in which the TDO enzyme is overexpressed or hyperactive.

Cell Panel Profiling Reveals Conserved Therapeutic Clusters and Differentiates the Mechanism of Action of Different PI3K/mTOR, Aurora Kinase and EZH2 Inhibitors.

Cancer cell line panels are important tools to characterize the in vitro activity of new investigational drugs. Here, we present the inhibition profiles of 122 anticancer agents in proliferation assays with 44 or 66 genetically characterized cancer cell lines from diverse tumor tissues (Oncolines). The library includes 29 cytotoxics, 68 kinase inhibitors, and 11 epigenetic modulators. For 38 compounds this is the first comparative profiling in a cell line panel. By strictly maintaining optimized assay protocols, biological variation was kept to a minimum. Replicate profiles of 16 agents over three years show a high average Pearson correlation of 0.8 using IC50 values and 0.9 using GI50 values. Good correlations were observed with other panels. Curve fitting appears a large source of variation. Hierarchical clustering revealed 44 basic clusters, of which 26 contain compounds with common mechanisms of action, of which 9 were not reported before, including TTK, BET and two clusters of EZH2 inhibitors. To investigate unexpected clusterings, sets of BTK, Aurora and PI3K inhibitors were profiled in biochemical enzyme activity assays and surface plasmon resonance binding assays. The BTK inhibitor ibrutinib clusters with EGFR inhibitors, because it cross-reacts with EGFR. Aurora kinase inhibitors separate into two clusters, related to Aurora A or pan-Aurora selectivity. Similarly, 12 inhibitors in the PI3K/AKT/mTOR pathway separated into different clusters, reflecting biochemical selectivity (pan-PI3K, PI3Kßγδ-isoform selective or mTOR-selective). Of these, only allosteric mTOR inhibitors preferentially targeted PTEN-mutated cell lines. This shows that cell line profiling is an excellent tool for the unbiased classification of antiproliferative compounds. Mol Cancer Ther; 15(12); 3097-109. ©2016 AACR.

Selective Targeting of CTNBB1-, KRAS- or MYC-Driven Cell Growth by Combinations of Existing Drugs.

The aim of combination drug treatment in cancer therapy is to improve response rate and to decrease the probability of the development of drug resistance. Preferably, drug combinations are synergistic rather than additive, and, ideally, drug combinations work synergistically only in cancer cells and not in non-malignant cells. We have developed a workflow to identify such targeted synergies, and applied this approach to selectively inhibit the proliferation of cell lines with mutations in genes that are difficult to modulate with small molecules. The approach is based on curve shift analysis, which we demonstrate is a more robust method of determining synergy than combination matrix screening with Bliss-scoring. We show that the MEK inhibitor trametinib is more synergistic in combination with the BRAF inhibitor dabrafenib than with vemurafenib, another BRAF inhibitor. In addition, we show that the combination of MEK and BRAF inhibitors is synergistic in BRAF-mutant melanoma cells, and additive or antagonistic in, respectively, BRAF-wild type melanoma cells and non-malignant fibroblasts. This combination exemplifies that synergistic action of drugs can depend on cancer genotype. Next, we used curve shift analysis to identify new drug combinations that specifically inhibit cancer cell proliferation driven by difficult-to-drug cancer genes. Combination studies were performed with compounds that as single agents showed preference for inhibition of cancer cells with mutations in either the CTNNB1 gene (coding for ß-catenin), KRAS, or cancer cells expressing increased copy numbers of MYC. We demonstrate that the Wnt-pathway inhibitor ICG-001 and trametinib acted synergistically in Wnt-pathway-mutant cell lines. The ERBB2 inhibitor TAK-165 was synergistic with trametinib in KRAS-mutant cell lines. The EGFR/ERBB2 inhibitor neratinib acted synergistically with the spindle poison docetaxel and with the Aurora kinase inhibitor GSK-1070916 in cell lines with MYC amplification. Our approach can therefore efficiently discover novel drug combinations that selectively target cancer genes.

High-throughput fluorescence-based screening assays for tryptophan-catabolizing enzymes.

Indoleamine 2,3-dioxygenase (IDO1) and tryptophan 2,3-dioxygenase (TDO) are two structurally different enzymes that have a different tissue distribution and physiological roles, but both catalyze the conversion of tryptophan to N-formylkynurenine (NFK). IDO1 has been clinically validated as a small-molecule drug target for cancer, while preclinical studies indicate that TDO may be a target for cancer immunotherapy and neurodegenerative disease. We have developed a high-throughput screening assay for IDO1 and TDO based on a novel chemical probe, NFK Green, that reacts specifically with NFK to form a green fluorescent molecule with an excitation wavelength of 400 nm and an emission wavelength of 510 nm. We provide the first side-by-side comparison of a number of published inhibitors of IDO1 and TDO and reveal that the preclinical IDO1 inhibitor Compound 5l shows significant cross-reactivity with TDO, while the relative selectivity of other published inhibitors was confirmed. The suitability for high-throughput screening of the assays was demonstrated by screening a library of 87,000 chemical substances in 384- or 1536-well format. Finally, we demonstrate that the assay can also be used to measure the capacity of cells to metabolize tryptophan and to measure the cellular potency of IDO1 and TDO inhibitors.

Comparison of the cancer gene targeting and biochemical selectivities of all targeted kinase inhibitors approved for clinical use.

The anti-proliferative activities of all twenty-five targeted kinase inhibitor drugs that are in clinical use were measured in two large assay panels: (1) a panel of proliferation assays of forty-four human cancer cell lines from diverse tumour tissue origins; and (2) a panel of more than 300 kinase enzyme activity assays. This study provides a head-on comparison of all kinase inhibitor drugs in use (status Nov. 2013), and for six of these drugs, the first kinome profiling data in the public domain. Correlation of drug activities with cancer gene mutations revealed novel drug sensitivity markers, suggesting that cancers dependent on mutant CTNNB1 will respond to trametinib and other MEK inhibitors, and cancers dependent on SMAD4 to small molecule EGFR inhibitor drugs. Comparison of cellular targeting efficacies reveals the most targeted inhibitors for EGFR, ABL1 and BRAF(V600E)-driven cell growth, and demonstrates that the best targeted agents combine high biochemical potency with good selectivity. For ABL1 inhibitors, we computationally deduce optimized kinase profiles for use in a next generation of drugs. Our study shows the power of combining biochemical and cellular profiling data in the evaluation of kinase inhibitor drug action.

A guide to picking the most selective kinase inhibitor tool compounds for pharmacological validation of drug targets.

To establish the druggability of a target, genetic validation needs to be supplemented with pharmacological validation. Pharmacological studies, especially in the kinase field, are hampered by the fact that many reference inhibitors are not fully selective for one target. Fortunately, the initial trickle of selective inhibitors released in the public domain has steadily swelled into a stream. However, rationally picking the most selective tool compound out of the increasing amounts of available inhibitors has become progressively difficult due to the lack of accurate quantitative descriptors of drug selectivity. A recently published approach, termed 'selectivity entropy', is an improved way of expressing selectivity as a single-value parameter and enables rank ordering of inhibitors. We provide a guide to select the best tool compounds for pharmacological validation experiments of candidate drug targets using selectivity entropy. In addition, we recommend which inhibitors to use for studying the biology of the 20 most investigated kinases that are clinically relevant: Abl (ABL1), AKT1, ALK, Aurora A/B, CDKs, MET, CSF1R (FMS), EGFR, FLT3, ERBB2 (HER2), IKBKB (IKK2), JAK2/3, JNK1/2/3 (MAPK8/9/10), MEK1/2, PLK1, PI3Ks, p38α (MAPK14), BRAF, SRC and VEGFR2 (KDR).

Multidimensional profiling of CSF1R screening hits and inhibitors: assessing cellular activity, target residence time, and selectivity in a higher throughput way.

Over the past years, improvements in high-throughput screening (HTS) technology and compound libraries have resulted in a dramatic increase in the amounts of good-quality screening hits, and there is a growing need for follow-on hit profiling assays with medium throughput to further triage hits. Here the authors present such assays for the colony-stimulating factor 1 receptor (CSF1R, Fms), including tests for cellular activity and a homogeneous assay to measure affinity for inactive CSF1R. They also present a high-throughput assay to measure target residence time, which is based on competitive binding kinetics. To better fit k(off) rates, they present a modified mathematical model for competitive kinetics. In all assays, they profiled eight reference inhibitors (imatinib, sorafenib, sunitinib, tandutinib, dasatinib, GW2580, Ki20227, and J&J's pyrido[2,3-d]pyrimidin-5-one). Using the known biochemical selectivities of these inhibitors, which can be quantified using metrics such as the selectivity entropy, the authors have determined which assay readout best predicts hit selectivity. Their profiling shows surprisingly that imatinib has a preference for the active form of CSF1R and that Ki20227 has an unusually slow target dissociation rate. This confirms that follow-on hit profiling is essential to ensure that the best hits are selected for lead optimization.

A theoretical entropy score as a single value to express inhibitor selectivity.

BACKGROUND: Designing maximally selective ligands that act on individual targets is the dominant paradigm in drug discovery. Poor selectivity can underlie toxicity and side effects in the clinic, and for this reason compound selectivity is increasingly monitored from very early on in the drug discovery process. To make sense of large amounts of profiling data, and to determine when a compound is sufficiently selective, there is a need for a proper quantitative measure of selectivity. RESULTS: Here we propose a new theoretical entropy score that can be calculated from a set of IC(50) data. In contrast to previous measures such as the 'selectivity score', Gini score, or partition index, the entropy score is non-arbitary, fully exploits IC(50) data, and is not dependent on a reference enzyme. In addition, the entropy score gives the most robust values with data from different sources, because it is less sensitive to errors. We apply the new score to kinase and nuclear receptor profiling data, and to high-throughput screening data. In addition, through analyzing profiles of clinical compounds, we show quantitatively that a more selective kinase inhibitor is not necessarily more drug-like. CONCLUSIONS: For quantifying selectivity from panel profiling, a theoretical entropy score is the best method. It is valuable for studying the molecular mechanisms of selectivity, and to steer compound progression in drug discovery programs.

Bet hedging based cooperation can limit kin selection and form a basis for mutualism.

Mutualism is a mechanism of cooperation in which partners that differ help each other. As such, mutualism opposes mechanisms of kin selection and tag-based selection (for example the green beard mechanism), which are based on giving exclusive help to partners that are related or carry the same tag. In contrast to kin selection, which is a basis for parochialism and intergroup warfare, mutualism can therefore be regarded as a mechanism that drives peaceful coexistence between different groups and individuals. Here the competition between mutualism and kin (tag) selection is studied. In a model where kin selection and tag-based selection are dominant, mutualism is promoted by introducing environmental fluctuations. These fluctuations cause reduction in reproductive success by the mechanism of variance discount. The best strategy to counter variance discount is to share with agents who experience the most anticorrelated fluctuations, a strategy called bet hedging. In this way, bet hedging stimulates cooperation with the most unrelated partners, which is a basis for mutualism. Analytic results and simulations reveal that, if this effect is large enough, mutualistic strategies can dominate kin selective strategies. In addition, mutants of these mutualistic strategies that experience fluctuations that are more anticorrelated to their partner, can outcompete wild type, which can lead to the evolution of specialization. In this way, the evolutionary success of mutualistic strategies can be explained by bet hedging-based cooperation.