The Use of Large-Scale Chemically-Induced Transcriptome Data Acquired from LINCS to Study Small Molecules

2018 ◽  
pp. 189-203 ◽  
Author(s):  
Michio Iwata ◽  
Yoshihiro Yamanishi
Keyword(s):  
Small Molecules ◽  
Large Scale ◽  
Transcriptome Data ◽  
Chemically Induced

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>

scholarly journals A novel ligand of the translationally controlled tumor protein (TCTP) identified by virtual drug screening for cancer differentiation therapy

2021 ◽  
Author(s):  
Nicolas Fischer ◽  
Ean-Jeong Seo ◽  
Sara Abdelfatah ◽  
Edmond Fleischer ◽  
Anette Klinger ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Virtual Screening ◽  
Small Molecules ◽  
Large Scale ◽  
Differentiation Therapy ◽  
P53 Expression ◽  
Microscale Thermophoresis ◽  
Cycle Arrest ◽  
G1 Cell Cycle Arrest ◽  
Mcf 7

SummaryIntroduction Differentiation therapy is a promising strategy for cancer treatment. The translationally controlled tumor protein (TCTP) is an encouraging target in this context. By now, this field of research is still at its infancy, which motivated us to perform a large-scale screening for the identification of novel ligands of TCTP. We studied the binding mode and the effect of TCTP blockade on the cell cycle in different cancer cell lines. Methods Based on the ZINC-database, we performed virtual screening of 2,556,750 compounds to analyze the binding of small molecules to TCTP. The in silico results were confirmed by microscale thermophoresis. The effect of the new ligand molecules was investigated on cancer cell survival, flow cytometric cell cycle analysis and protein expression by Western blotting and co-immunoprecipitation in MOLT-4, MDA-MB-231, SK-OV-3 and MCF-7 cells. Results Large-scale virtual screening by PyRx combined with molecular docking by AutoDock4 revealed five candidate compounds. By microscale thermophoresis, ZINC10157406 (6-(4-fluorophenyl)-2-[(8-methoxy-4-methyl-2-quinazolinyl)amino]-4(3H)-pyrimidinone) was identified as TCTP ligand with a KD of 0.87 ± 0.38. ZINC10157406 revealed growth inhibitory effects and caused G0/G1 cell cycle arrest in MOLT-4, SK-OV-3 and MCF-7 cells. ZINC10157406 (2 × IC50) downregulated TCTP expression by 86.70 ± 0.44% and upregulated p53 expression by 177.60 ± 12.46%. We validated ZINC10157406 binding to the p53 interaction site of TCTP and replacing p53 by co-immunoprecipitation. Discussion ZINC10157406 was identified as potent ligand of TCTP by in silico and in vitro methods. The compound bound to TCTP with a considerably higher affinity compared to artesunate as known TCTP inhibitor. We were able to demonstrate the effect of TCTP blockade at the p53 binding site, i.e. expression of TCTP decreased, whereas p53 expression increased. This effect was accompanied by a dose-dependent decrease of CDK2, CDK4, CDK, cyclin D1 and cyclin D3 causing a G0/G1 cell cycle arrest in MOLT-4, SK-OV-3 and MCF-7 cells. Our findings are supposed to stimulate further research on TCTP-specific small molecules for differentiation therapy in oncology.

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.

Affecting RNA biology genome-wide by binding small molecules and chemically induced proximity

2021 ◽  
Vol 62 ◽  
pp. 119-129
Author(s):  
Jared T. Baisden ◽  
Jessica L. Childs-Disney ◽  
Lucas S. Ryan ◽  
Matthew D. Disney
Keyword(s):  
Small Molecules ◽  
Genome Wide ◽  
Chemically Induced ◽  
Rna Biology

scholarly journals Molecular and Clinical Characterization of PD-1 in Breast Cancer Using Large-Scale Transcriptome Data

2020 ◽  
Vol 11 ◽  
Author(s):  
Qiang Liu ◽  
Ran Cheng ◽  
Xiangyi Kong ◽  
Zhongzhao Wang ◽  
Yi Fang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Large Scale ◽  
Transcriptome Data

scholarly journals Recent Advances in the Application of Metabolomics for Nutrition and Health

2019 ◽  
Vol 10 (1) ◽  
pp. 479-519 ◽  
Author(s):  
Diana González-Peña ◽  
Lorraine Brennan
Keyword(s):  
Small Molecules ◽  
Biological Samples ◽  
Large Scale ◽  
Dietary Assessment ◽  
Personalized Nutrition ◽  
Nutrition And Health ◽  
Successful Development ◽  
Nutrition Research ◽  
Epidemiology Studies ◽  
Further Development

Metabolomics is the study of small molecules called metabolites in biological samples. Application of metabolomics to nutrition research has expanded in recent years, with emerging literature supporting multiple applications. Key examples include applications of metabolomics in the identification and development of objective biomarkers of dietary intake, in developing personalized nutrition strategies, and in large-scale epidemiology studies to understand the link between diet and health. In this review, we provide an overview of the current applications and identify key challenges that need to be addressed for the further development of the field. Successful development of metabolomics for nutrition research has the potential to improve dietary assessment, help deliver personalized nutrition, and enhance our understanding of the link between diet and health.

scholarly journals A comprehensive RNA handling and transcriptomics guide for high-throughput processing of Plasmodium blood-stage samples

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Michal Kucharski ◽  
Jaishree Tripathi ◽  
Sourav Nayak ◽  
Lei Zhu ◽  
Grennady Wirjanata ◽  
...  
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Rna Extraction ◽  
Transcriptome Data ◽  
High Quality ◽  
Diverse Range ◽  
Human Haemoglobin ◽  
Infected Blood ◽  
Blood Samples ◽  
Total Rna

Abstract Background Sequencing technology advancements opened new opportunities to use transcriptomics for studying malaria pathology and epidemiology. Even though in recent years the study of whole parasite transcriptome proved to be essential in understanding parasite biology there is no compiled up-to-date reference protocol for the efficient generation of transcriptome data from growing number of samples. Here, a comprehensive methodology on how to preserve, extract, amplify, and sequence full-length mRNA transcripts from Plasmodium-infected blood samples is presented that can be fully streamlined for high-throughput studies. Results The utility of various commercially available RNA-preserving reagents in a range of storage conditions was evaluated. Similarly, several RNA extraction protocols were compared and the one most suitable method for the extraction of high-quality total RNA from low-parasitaemia and low-volume blood samples was established. Furthermore, the criteria needed to evaluate the quality and integrity of Plasmodium RNA in the presence of human RNA was updated. Optimization of SMART-seq2 amplification method to better suit AT-rich Plasmodium falciparum RNA samples allowed us to generate high-quality transcriptomes from as little as 10 ng of total RNA and a lower parasitaemia limit of 0.05%. Finally, a modified method for depletion of unwanted human haemoglobin transcripts using in vitro CRISPR-Cas9 treatment was designed, thus improving parasite transcriptome coverage in low parasitaemia samples. To prove the functionality of the pipeline for both laboratory and field strains, the highest  2-hour resolution RNA-seq transcriptome for P. falciparum 3D7 intraerythrocytic life cycle available to  date was generated, and the entire protocol was applied to create the largest transcriptome data from Southeast Asian field isolates. Conclusions Overall, the presented methodology is an inclusive pipeline for generation of good quality transcriptomic data from a diverse range of Plasmodium-infected blood samples with varying parasitaemia and RNA inputs. The flexibility of this pipeline to be adapted to robotic handling will facilitate both small and large-scale future transcriptomic studies in the field of malaria.

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