The Use of Informer Sets in Screening: Perspectives on an Efficient Strategy to Identify New Probes

2021 ◽  
pp. 247255522110194
Author(s):  
Paul A. Clemons ◽  
Joshua A. Bittker ◽  
Florence F. Wagner ◽  
Allison Hands ◽  
Vlado Dančík ◽  
...  
Keyword(s):  
Small Molecules ◽  
Small Molecule ◽  
Chemical Structure ◽  
Large Scale ◽  
Diversity Oriented Synthesis ◽  
Limited Success ◽  
Entire Collection ◽  
Shed Light ◽  
Large Scale Screening ◽  
Missed Opportunity

Small-molecule discovery typically involves large-scale screening campaigns, spanning multiple compound collections. However, such activities can be cost- or time-prohibitive, especially when using complex assay systems, limiting the number of compounds tested. Further, low hit rates can make the process inefficient. Sparse coverage of chemical structure or biological activity space can lead to limited success in a primary screen and represents a missed opportunity by virtue of selecting the “wrong” compounds to test. Thus, the choice of screening collections becomes of paramount importance. In this perspective, we discuss the utility of generating “informer sets” for small-molecule discovery, and how this strategy can be leveraged to prioritize probe candidates. While many researchers may assume that informer sets are focused on particular targets (e.g., kinases) or processes (e.g., autophagy), efforts to assemble informer sets based on historical bioactivity or successful human exposure (e.g., repurposing collections) have shown promise as well. Another method for generating informer sets is based on chemical structure, particularly when the compounds have unknown activities and targets. We describe our efforts to screen an informer set representing a collection of 100,000 small molecules synthesized through diversity-oriented synthesis (DOS). This process enables researchers to identify activity early and more extensively screen only a few chemical scaffolds, rather than the entire collection. This elegant and economic outcome is a goal of the informer set approach. Here, we aim not only to shed light on this process, but also to promote the use of informer sets more widely in small-molecule discovery projects.

scholarly journals STEM-20. A CANCER STEM CELL-SELECTIVE APOPTOSIS-INDUCING SMALL MOLECULE FOR THE TREATMENT OF GBM

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii200-ii200
Author(s):  
Stephen Skirboll ◽  
Natasha Lucki ◽  
Genaro Villa ◽  
Naja Vergani ◽  
Michael Bollong ◽  
...  
Keyword(s):  
Stem Cells ◽  
Cancer Stem Cells ◽  
Small Molecules ◽  
Small Molecule ◽  
Large Scale ◽  
Critical Role ◽  
Tumor Formation ◽  
Cell Type ◽  
Caspase 1 ◽  
Activation Assay

Abstract INTRODUCTION Glioblastoma multiforme (GBM) is the most aggressive form of primary brain cancer. A subpopulation of multipotent cells termed GBM cancer stem cells (CSCs) play a critical role in tumor initiation and maintenance, drug resistance, and recurrence following surgery. New therapeutic strategies for the treatment of GBM have recently focused on targeting CSCs. Here we have used an unbiased large-scale screening approach to identify drug-like small molecules that induce apoptosis in GBM CSCs in a cell type-selective manner. METHODS A luciferase-based survival assay of patient-derived GBM CSC lines was established to perform a large-scale screen of ∼one million drug-like small molecules with the goal of identifying novel compounds that are selectively toxic to chemoresistant GBM CSCs. Compounds found to kill GBM CSC lines as compared to control cell types were further characterized. A caspase activation assay was used to evaluate the mechanism of induced cell death. A xenograft animal model using patient-derived GBM CSCs was employed to test the leading candidate for suppression of in vivo tumor formation. RESULTS We identified a small molecule, termed RIPGBM, from the cell-based chemical screen that induces apoptosis in primary patient-derived GBM CSC cultures. The cell type-dependent selectivity of RIPGBM appears to arise at least in part from redox-dependent formation of a proapoptotic derivative, termed cRIPGBM, in GBM CSCs. cRIPGBM induces caspase 1-dependent apoptosis by binding to receptor-interacting protein kinase 2 (RIPK2) and acting as a molecular switch, which reduces the formation of a prosurvival RIPK2/TAK1 complex and increases the formation of a proapoptotic RIPK2/caspase 1 complex. In an intracranial GBM xenograft mouse model, RIPGBM was found to significantly suppress tumor formation. CONCLUSIONS Our chemical genetics-based approach has identified a small molecule drug candidate and a potential drug target that selectively targets cancer stem cells and provides an approach for the treatment of GBMs.

In depth analysis of kinase cross screening data to identify chemical starting points for inhibition of the nek family of kinases

2017 ◽  
Author(s):  
Carrow I. Wells ◽  
Nirav R. Kapadia ◽  
Rafael M. Couñago ◽  
David H. Drewry
Keyword(s):  
Drug Discovery ◽  
Small Molecules ◽  
Small Molecule ◽  
Kinase Inhibitors ◽  
Biological Functions ◽  
Chemical Probes ◽  
High Quality ◽  
Depth Analysis ◽  
Number Of Citations ◽  
Shed Light

AbstractPotent, selective, and cell active small molecule kinase inhibitors are useful tools to help unravel the complexities of kinase signaling. As the biological functions of individual kinases become better understood, they can become targets of drug discovery efforts. The small molecules used to shed light on function can also then serve as chemical starting points in these drug discovery efforts. The Nek family of kinases has received very little attention, as judged by number of citations in PubMed, yet they appear to play many key roles and have been implicated in disease. Here we present our work to identify high quality chemical starting points that have emerged due to the increased incidence of broad kinome screening. We anticipate that this analysis will allow the community to progress towards the generation of chemical probes and eventually drugs that target members of the Nek family.

A Robust Screening Assay For Diamond Blackfan Anemia Candidate Drugs

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2472-2472
Author(s):  
Kavitha Siva ◽  
Fredrik Ek ◽  
Hanna Axelsson ◽  
Abdul Ghani Alattar ◽  
Svetlana Soboleva ◽  
...  
Keyword(s):  
Cell Lines ◽  
Small Molecule ◽  
Large Scale ◽  
Fetal Liver ◽  
Assay Development ◽  
Erythroid Progenitors ◽  
Cell Numbers ◽  
Drug Candidates ◽  
Diamond Blackfan Anemia ◽  
Large Scale Screening

Abstract Diamond-Blackfan anemia (DBA) is a bone marrow failure syndrome associated with ribosomal protein (RP) deficiency caused by mutations in RP genes. 25% of patients carry mutations in the RPS19 gene. A salient feature of DBA is proliferative arrest of erythroid progenitors. It is still not clear how defects in RPs, which are essential to all cell types, affect the erythroid compartment more severely than the others. Today, DBA patients are treated with glucocorticoids and/or blood transfusions, often for long periods, causing severe adverse effects. We hypothesize that novel drugs with more disease-specific therapeutic mechanisms can be developed and that such drugs will be superior to current therapies. Towards this aim we have developed a method for screening chemical libraries to identify novel drug candidates. Use of DBA patient cells is not feasible as their limited availability severely limits the size of the applied screening library. Immortalized cell lines are also less suitable since the disease mechanism involves TP53 activation and most cell lines have perturbations in the TP53 pathway. Hence, primary c-Kit+ E14.5-15.5 fetal liver erythroid progenitor cells from a mouse model of DBA with doxycycline inducible expression of rps19-shRNA were used (Jaako et. al. Blood, 2011). The DBA phenotype is induced by adding doxycycline to the culture medium which reduces erythroid proliferation >80%. Rescue of this proliferation defect is a simple and relevant readout for large-scale screening. Assay development in 96 well microtiter plates allowed rational liquid handling. Firstly, the proliferation readout method was optimized. Use of CellTiter-Glö Luminescent Cell Viability Assay generated data with superior linear correlation with cell numbers compared to Prestobluë and high content screening microscopy approaches. To enable large-scale screening, the assay was further optimized for cell numbers per well, media composition, culture duration, doxycycline concentration and timing of induction and of addition of test chemicals. We also controlled for evaporation during incubation to significantly reduce plate edge effects. During these optimizations, luminescence readout from uninduced cells was set to represent 100% rescue and readout from doxycycline-induced controls to represent 0% recue. This allows reliable normalization between plates and gives toxic chemicals a negative value and chemicals rescuing proliferation a positive value with 100% meaning complete rescue. To objectively quantify how changes of different parameters improved variability in both induced and uninduced cells, we calculated the Z factor as described by Zhang et. al. (JBS, 1999). The Z factor takes into consideration both the range and variability of data to calculate the suitability of an assay for high throughput screening. It is represented as: (SD: Standard Deviation). Where Z value is meaningful in the range of -1 < Z ² 1. The larger the value of Z, the higher is the data quality and a Z-factor above 0.5 is considered very robust. After assay development we arrived at the conditions shown in the table, resulting in the Z factor of 0.7:Culture medium100 ng/ml mSCF, 2 U/ml Epo, 100 nM dexamethasone in serum-free medium. (doxycycline: 0.5 μg/ml).Culture days4 (addition of test chemicals 24 hours after doxycycline induction)Cells per well2000 (murine cKit+ fetal liver cells with inducible rps19-shRNA)ReadoutLuciferase based ATP detection (CellTiter-Glo¨). For screening involving small molecule based libraries we added the compounds 24 hours after cell seeding and doxycycline addition, which allows for the induction of the proliferation perturbed phenotype. We have pharmacologically validated the assay by testing and quantifying the impact of IL-3, a cytokine known to have a positive effect on erythroid progenitors. IL-3 had a 25% rescue value in our assay. Ongoing experiments (>11,000 compounds screened to date) show that more than 50% of compounds with >20% rescue score in the screen could be confirmed to rescue proliferation in dose-dependent experiments. In conclusion, we have established a robust scalable assay for screening molecules that rescue proliferation arrest caused by Rps19-deficiency in mouse erythroid progenitors. We are currently using this assay to screen small molecule libraries in our search for novel tool compounds for DBA research and drug candidates for DBA treatment. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Growth Suppressing Activity of Lhx2 in Human T Cell Acute Lymphoblastic Leukemia (T-ALL)-Derived Cells and Large-Scale Screening of a Lead Compounds Targeting T-ALL

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 2813-2813
Author(s):  
Kazuya Miyashita ◽  
Noritaka Kagaya ◽  
Miho Izumikawa ◽  
Kenji Kitajima ◽  
Kyoko Watakabe-Inamoto ◽  
...  
Keyword(s):  
Acute Lymphoblastic Leukemia ◽  
T Cell ◽  
Cell Line ◽  
Cell Lines ◽  
Peripheral Blood ◽  
Chemical Structure ◽  
Large Scale ◽  
Lymphoblastic Leukemia ◽  
B Lymphoma ◽  
Large Scale Screening

Abstract Acute lymphoblastic leukemia (ALL) is one of the most frequently occurring cancers in infants and young children. For patients suffering from CD20-positive B-cell ALL (B-ALL) and Ph-positive ALL, overall survival rates have been greatly improved after clinical introduction of rituximab and imatinib, respectively. However, T-cell ALL (T-ALL) patients still exhibit poor prognosis, since there is no such an efficient molecular-targeted drug. It is known that LIM-only transcriptional co-factor LMO2 and its target gene HHEX are essential for self-renewal of T cell precursors and onset of T-ALL. LMO2 directly associates with LDB1 in a large DNA-containing nuclear complex and controls the transcription of T-ALL-related downstream genes. Recently, we reported that overexpression of LIM-homeodomain transcription factor Lhx2 results in liberation of Lmo2 protein from the Lmo2-Ldb1 complex followed by degradation by ubiquitin-proteasome system. We found that proliferation of 5 different human T-ALL-derived cell lines including CCRF-CEM was significantly suppressed by retroviral overexpression of Lhx2. In contrast, enforced overexpression of Lhx2 did not reduce the growth rate of B lymphoma-derived cell line Raji, oral cancer-derived cell line HSC-3, and osteosarcoma-derived cell line Saos-2. Majority of the Lhx2-transduced CCRF-CEM cells was arrested in G0 phase and subsequently underwent apoptosis. Expression of LMO2 protein and HHEX mRNA was repressed by the Lhx2 transduction. Importantly, the Lhx2-mediated growth inhibition was partially rescued by the simultaneous overexpression of Lmo2. However, both C-terminal LIM-domain and homeodomain of Lhx2 were required for the growth-suppressive activity. These data indicated that Lhx2 is capable to blocking proliferation of T-ALL-derived cells in LMO2-dependent and independent fashions. Lhx2 would be a useful molecular tool for designing a new type of anti-T-ALL drug. In order to develop a new drug that mimics the aforementioned activity of Lhx2, we performed large-scale screening of natural compound libraries to find out a compound that suppresses the proliferation of T-ALL cell line CCRF-CEM, but does not inhibit the growth of B lymphoma cell line Raji. Among 150,000 different compounds, we successfully identified 3 low-molecular-weight compounds (44D-L008, 31D-F005, 21D-D016) that fulfilled the above criteria. 44D-L008 and 31D-F005 possessed a common chemical structure. In the presence of 5μM of 44D-L008 and 31D-F005, proliferation of 5 human T-ALL cell lines including CCRF-CEM was severely blocked. On the other hand, Raji, HSC-3 and Saos-2 were completely resistant to both compounds in the same experimental settings. Intriguingly, 44D-L008 decreased viability of human skin fibroblasts in culture, whereas 31D-F005 displayed no such negative effects on skin fibroblasts, peripheral blood mononuclear cells, and peripheral blood T cells of human origin. These results indicated that small differences in the chemical structure between 44D-L008 and 31D-F005 are responsible for the side effect on normal cells. Finally, we collaborated with a hospital and found that 0.5 μM of 31D-F005 efficiently suppressed the in vitro growth of primary cancer cells of a T-ALL patient. Taken together, theses data demonstrated that 31D-F005 is a promising lead compound for a new anti-T-ALL drug. Disclosures No relevant conflicts of interest to declare.

scholarly journals Constructing and characterizing a bioactive small molecule and microRNA association network for Alzheimer's disease

2014 ◽  
Vol 11 (92) ◽  
pp. 20131057 ◽  
Author(s):  
Fanlin Meng ◽  
Enyu Dai ◽  
Xuexin Yu ◽  
Yan Zhang ◽  
Xiaowen Chen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Small Molecules ◽  
Small Molecule ◽  
Large Scale ◽  
Neurodegenerative Disorder ◽  
Expression Patterns ◽  
Association Network ◽  
Multiple Perspectives ◽  
Mirna Targets

Alzheimer's disease (AD) is an incurable neurodegenerative disorder. Much effort has been devoted to developing effective therapeutic agents. Recently, targeting microRNAs (miRNAs) with small molecules has become a novel therapy for human diseases. In this study, we present a systematic computational approach to construct a bioactive Small molecule and miRNA association Network in AD (SmiRN-AD), which is based on the gene expression signatures of bioactive small molecule perturbation and AD-related miRNA regulation. We also performed topological and functional analysis of the SmiRN-AD from multiple perspectives. At the significance level of p ≤ 0.01, 496 small molecule–miRNA associations, including 25 AD-related miRNAs and 275 small molecules, were recognized and used to construct the SmiRN-AD. The drugs that were connected with the same miRNA tended to share common drug targets ( p = 1.72 × 10 −4 ) and belong to the same therapeutic category ( p = 4.22 × 10 −8 ). The miRNAs that were linked to the same small molecule regulated more common miRNA targets ( p = 6.07 × 10 −3 ). Further analysis of the positive connections (quinostatin and miR-148b, amantadine and miR-15a) and the negative connections (melatonin and miR-30e-5p) indicated that our large-scale predictions afforded specific biological insights into AD pathogenesis and therapy. This study proposes a holistic strategy for deciphering the associations between small molecules and miRNAs in AD, which may be helpful for developing a novel effective miRNA-associated therapeutic strategy for AD. A comprehensive database for the SmiRN-AD and the differential expression patterns of the miRNA targets in AD is freely available at http://bioinfo.hrbmu.edu.cn/SmiRN-AD/ .

Training Aides to Screen Children for Speech and Language Problems

1976 ◽  
Vol 7 (4) ◽  
pp. 236-241 ◽  
Author(s):  
Marisue Pickering ◽  
William R. Dopheide
Keyword(s):  
Rural Areas ◽  
Large Scale ◽  
School Personnel ◽  
School Age Children ◽  
Speech And Language ◽  
Elementary School Age ◽  
Evaluation Procedures ◽  
Language Problems ◽  
Competency Based ◽  
Large Scale Screening

This report deals with an effort to begin the process of effectively identifying children in rural areas with speech and language problems using existing school personnel. A two-day competency-based workshop for the purpose of training aides to conduct a large-scale screening of speech and language problems in elementary-school-age children is described. Training strategies, implementation, and evaluation procedures are discussed.

Epigenetic Target Prediction with Accurate Machine Learning Models

2021 ◽  
Author(s):  
Norberto Sánchez-Cruz ◽  
Jose L. Medina-Franco
Keyword(s):  
Machine Learning ◽  
Small Molecules ◽  
Predictive Models ◽  
Large Scale ◽  
Target Prediction ◽  
Quantitative Measure ◽  
Learning Models ◽  
Discovery Research ◽  
Drug Discovery Research ◽  
Machine Learning Models

<p>Epigenetic targets are a significant focus for drug discovery research, as demonstrated by the eight approved epigenetic drugs for treatment of cancer and the increasing availability of chemogenomic data related to epigenetics. This data represents a large amount of structure-activity relationships that has not been exploited thus far for the development of predictive models to support medicinal chemistry efforts. Herein, we report the first large-scale study of 26318 compounds with a quantitative measure of biological activity for 55 protein targets with epigenetic activity. Through a systematic comparison of machine learning models trained on molecular fingerprints of different design, we built predictive models with high accuracy for the epigenetic target profiling of small molecules. The models were thoroughly validated showing mean precisions up to 0.952 for the epigenetic target prediction task. Our results indicate that the herein reported models have considerable potential to identify small molecules with epigenetic activity. Therefore, our results were implemented as freely accessible and easy-to-use web application.</p>

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