Identification of a selective G1-phase benzimidazolone inhibitor by a senescence-targeted virtual screen using artificial neural networks

Cellular senescence is a barrier to tumorigenesis in normal cells and tumour cells undergo senescence responses to genotoxic stimuli, which is a potential target phenotype for cancer therapy. However, in this setting, mixed-mode responses are common with apoptosis the dominant effect. Hence, more selective senescence inducers are required. Here we report a machine learning-based in silico screen to identify potential senescence agonists. We built profiles of differentially affected biological process networks from expression data obtained under induced telomere dysfunction conditions in colorectal cancer cells and matched these to a panel of 17 protein targets with confirmatory screening data in PubChem. We trained a neural network using 3517 compounds identified as active or inactive against these targets. The resulting classification model was used to screen a virtual library of ~2M lead-like compounds. 147 virtual hits were acquired for validation in growth inhibition and senescence-associated β-galactosidase (SA-β-gal) assays. Among the found hits a benzimidazolone compound, CB-20903630, had low micromolar IC50 for growth inhibition of HCT116 cells and selectively induced SA-β-gal activity in the entire treated cell population without cytotoxicity or apoptosis induction. Growth suppression was mediated by G1 blockade involving increased p21 expression and suppressed cyclin B1, CDK1 and CDC25C. Additionally, the compound inhibited growth of multicellular spheroids and caused severe retardation of population kinetics in long term treatments. Preliminary structure-activity and structure clustering analyses are reported and expression analysis of CB-20903630 against other cell cycle suppressor compounds suggested a PI3K/AKT-inhibitor-like profile in normal cells, with different pathways affected in cancer cells

Genome-wide assessment of the carriers involved in the cellular uptake of drugs: a model system in yeast.

BACKGROUND: The uptake of drugs into cells has traditionally been considered to be predominantly via passive diffusion through the bilayer portion of the cell membrane. The recent recognition that drug uptake is mostly carrier-mediated raises the question of which drugs use which carriers. RESULTS: To answer this, we have constructed a chemical genomics platform built upon the yeast gene deletion collection, using competition experiments in batch fermenters and robotic automation of cytotoxicity screens, including protection by 'natural' substrates. Using these, we tested 26 different drugs and identified the carriers required for 18 of the drugs to gain entry into yeast cells. CONCLUSIONS: As well as providing a useful platform technology, these results further substantiate the notion that the cellular uptake of pharmaceutical drugs normally occurs via carrier-mediated transport and indicates that establishing the identity and tissue distribution of such carriers should be a major consideration in the design of safe and effective drugs.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Patient-specific hiPSC bioprocessing for drug screening: Bioprocess economics and optimisation

This paper describes a decisional tool that is designed to identify cost-effective process designs for drug screening products derived from human induced pluripotent stem cells (hiPSC). The decisional tool comprises a bioprocess economics model linked to a search algorithm to assess the financial impact of manual and automated bioprocessing strategies that use 2D-planar tissue culture technologies. The tool was applied to a case study that examines the production of patient-specific iPSC-derived neurons for drug screening. The production strategies were compared across three analytical drug screening methods, each requiring cell production at a distinct scale (manual patch-clamp analysis, high throughput screening and plate-based pharmacology), as well as different annual cell line utilization requirements ('throughputs') (between 10 and 100 lines) so as to represent different industry scenarios. The tool determined the critical cell line throughput where the most cost-effective production strategy switched from the manual to automated workflow. The key process economics driver was the number of iPSC expansion stages required. Stochastic modelling of the bioprocess illustrated that the automated was more robust than the manual workflow in the scenarios investigated. The tool predicted the level of performance improvements required in iPSC expansion and differentiation as well as reductions in indirect costs and media costs so as to achieve an acceptable cost of goods (COG)

Mathematical model of a telomerase transcriptional regulatory network developed by cell-based screening: analysis of inhibitor effects and telomerase expression mechanisms

Cancer cells depend on transcription of telomerase reverse transcriptase (TERT). Many transcription factors affect TERT, though regulation occurs in context of a broader network. Network effects on telomerase regulation have not been investigated, though deeper understanding of TERT transcription requires a systems view. However, control over individual interactions in complex networks is not easily achievable. Mathematical modelling provides an attractive approach for analysis of complex systems and some models may prove useful in systems pharmacology approaches to drug discovery. In this report, we used transfection screening to test interactions among 14 TERT regulatory transcription factors and their respective promoters in ovarian cancer cells. The results were used to generate a network model of TERT transcription and to implement a dynamic Boolean model whose steady states were analysed. Modelled effects of signal transduction inhibitors successfully predicted TERT repression by Src-family inhibitor SU6656 and lack of repression by ERK inhibitor FR180204, results confirmed by RT-QPCR analysis of endogenous TERT expression in treated cells. Modelled effects of GSK3 inhibitor 6-bromoindirubin-3′-oxime (BIO) predicted unstable TERT repression dependent on noise and expression of JUN, corresponding with observations from a previous study. MYC expression is critical in TERT activation in the model, consistent with its well known function in endogenous TERT regulation. Loss of MYC caused complete TERT suppression in our model, substantially rescued only by co-suppression of AR. Interestingly expression was easily rescued under modelled Ets-factor gain of function, as occurs in TERT promoter mutation. RNAi targeting AR, JUN, MXD1, SP3, or TP53, showed that AR suppression does rescue endogenous TERT expression following MYC knockdown in these cells and SP3 or TP53 siRNA also cause partial recovery. The model therefore successfully predicted several aspects of TERT regulation including previously unknown mechanisms. An extrapolation suggests that a dominant stimulatory system may programme TERT for transcriptional stability

A 'synthetic-sickness' screen for senescence re-engagement targets in mutant cancer backgrounds.

Senescence is a universal barrier to immortalisation and tumorigenesis. As such, interest in the use of senescence-induction in a therapeutic context has been gaining momentum in the past few years; however, senescence and immortalisation remain underserved areas for drug discovery owing to a lack of robust senescence inducing agents and an incomplete understanding of the signalling events underlying this complex process. In order to address this issue we undertook a large-scale morphological siRNA screen for inducers of senescence phenotypes in the human melanoma cell line A375P. Following rescreen and validation in a second cancer cell line, HCT116 colorectal carcinoma, a panel of 16 of the most robust hits were selected for further validation based on significance and the potential to be targeted by drug-like molecules. Using secondary assays for detection of senescence biomarkers p21, 53BP1 and senescence associated beta-galactosidase (SAβGal) in a panel of HCT116 cell lines carrying cancer-relevant mutations, we show that partial senescence phenotypes can be induced to varying degrees in a context dependent manner, even in the absence of p21 or p53 expression. However, proliferation arrest varied among genetic backgrounds with predominantly toxic effects in p21 null cells, while cells lacking PI3K mutation failed to arrest. Furthermore, we show that the oncogene ECT2 induces partial senescence phenotypes in all mutant backgrounds tested, demonstrating a dependence on activating KRASG13D for growth suppression and a complete senescence response. These results suggest a potential mechanism to target mutant KRAS signalling through ECT2 in cancers that are reliant on activating KRAS mutations and remain refractory to current treatments

A novel pyrazolopyrimidine ligand of human PGK1 and stress sensor DJ1 modulates the shelterin complex and telomere length regulation

Telomere signaling and metabolic dysfunction are hallmarks of cell aging. New agents targeting these processes might provide therapeutic opportunities, including chemoprevention strategies against cancer predisposition. We report identification and characterization of a pyrazolopyrimidine compound series identified from screens focused on cell immortality and whose targets are glycolytic kinase PGK1 and oxidative stress sensor DJ1. We performed structure–activity studies on the series to develop a photoaffinity probe to deconvolute the cellular targets. In vitro binding and structural analyses confirmed these targets, suggesting that PGK1/DJ1 interact, which we confirmed by immunoprecipitation. Glucose homeostasis and oxidative stress are linked to telomere signaling and exemplar compound CRT0063465 blocked hypoglycemic telomere shortening. Intriguingly, PGK1 and DJ1 bind to TRF2 and telomeric DNA. Compound treatment modulates these interactions and also affects Shelterin complex composition, while conferring cellular protection from cytotoxicity due to bleomycin and desferroxamine. These results demonstrate therapeutic potential of the compound series

The Discovery of a Potent, Selective, and Peripherally Restricted Pan-Trk Inhibitor (PF-06273340) for the Treatment of Pain

The neurotrophin family of growth factors, comprised of nerve growth factor (NGF), brain derived neurotrophic factor (BDNF), neurotrophin 3 (NT3), and neurotrophin 4 (NT4), is implicated in the physiology of chronic pain. Given the clinical efficacy of anti-NGF monoclonal antibody (mAb) therapies, there is significant interest in the development of small molecule modulators of neurotrophin activity. Neurotrophins signal through the tropomyosin related kinase (Trk) family of tyrosine kinase receptors, hence Trk kinase inhibition represents a potentially “druggable” point of intervention. To deliver the safety profile required for chronic, nonlife threatening pain indications, highly kinase-selective Trk inhibitors with minimal brain availability are sought. Herein we describe how the use of SBDD, 2D QSAR models, and matched molecular pair data in compound design enabled the delivery of the highly potent, kinase-selective, and peripherally restricted clinical candidate PF-06273340

The HOG Pathway Dictates the Short-Term Translational Response after Hyperosmotic Shock

In the global osmoshock translational response in yeast, some gene products were translationally mobilized without transcriptional up-regulation. Conversely, other transcriptionally up-regulated mRNAs were translationally inhibited. Analogous changes occurred on the protein level. These translational responses were strongly dependent on Hog1 and Rck2