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A Deep Learning based Efficacy Prediction System for Drug Discovery [Trametinib]

ABSTRACT: Target protein-based drug and research compound discovery has been undeniably successful strategy in life science research, yet many diseases and biological processes lack obvious targets to enable these approaches. Here, to overcome this major challenge we have developed a deep-learning based efficacy prediction system (DLEPS) to identify potent agents to treat diverse diseases; DLEPS was trained using L1000 project chemical induced “changes of transcriptional profiles” (CTP) data as input. Strikingly, we found that the CTPs for previously unexamined molecules were precisely predicted (0.74 Pearson correlation coefficient). We used DLEPS to examine 4 disorders, and experimentally validated that perillen, chikusetsusaponin IV, trametinib, and liquiritin confer disease-relevant impacts against obesity, hyperuricemia, NASH, and COVID-19, respectively. Importantly, DLEPS also uncovered the biological insight that the MEK-ERK signaling pathway should be understood as a target for developing anti-NASH agents. Beyond illustrating that DLEPS is an effective tool for drug repurposing and development with diverse diseases (including those lacking targets), our study shows how diverse transcriptomics datasets can be harnessed to identify inhibitors and activator chemicals that can expand the scope of biological investigations well beyond mutant-bases analyses.

ORGANISM(S): Mus musculus

PROVIDER: GSE165174 | GEO | 2023/03/31

REPOSITORIES: GEO

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A Deep Learning based Efficacy Prediction System for Drug Discovery [Chikusetsusaponin IV]

Project description:Target protein-based drug and research compound discovery has been undeniably successful strategy in life science research, yet many diseases and biological processes lack obvious targets to enable these approaches. Here, to overcome this major challenge we have developed a deep-learning based efficacy prediction system (DLEPS) to identify potent agents to treat diverse diseases; DLEPS was trained using L1000 project chemical induced “changes of transcriptional profiles” (CTP) data as input. Strikingly, we found that the CTPs for previously unexamined molecules were precisely predicted (0.74 Pearson correlation coefficient). We used DLEPS to examine 4 disorders, and experimentally validated that perillen, chikusetsusaponin IV, trametinib, and liquiritin confer disease-relevant impacts against obesity, hyperuricemia, NASH, and COVID-19, respectively. Importantly, DLEPS also uncovered the biological insight that the MEK-ERK signaling pathway should be understood as a target for developing anti-NASH agents. Beyond illustrating that DLEPS is an effective tool for drug repurposing and development with diverse diseases (including those lacking targets), our study shows how diverse transcriptomics datasets can be harnessed to identify inhibitors and activator chemicals that can expand the scope of biological investigations well beyond mutant-bases analyses.

2023-03-31 | GSE165171 | GEO

A Deep Learning based Efficacy Prediction System for Drug Discovery [Perillen]

2023-03-31 | GSE165173 | GEO

Wolf_et_al

Project description:Metabolic activation of CD8+ and NKT-cells causes NASH and HCC through cross-talk with hepatocytes. Mice that devloped HCC or NASH were compared to work out genomic differences of the two diseases. In order to characterise the importance of CCR2 (activation of monocytes) in the development of NASH and HCC CCR2 double-mutant mice were compared to CCR2 wildtype mice.

2014-06-01 | E-MTAB-2469 | biostudies-arrayexpress

Fat body-specific reduction of CTPS alleviates HFD-induced obesity

Project description:High-fat diet (HFD)-induced obesity is a multi-factorial disease including genetic, physiological, behavioral, and environmental components. Drosophila has emerged as an effective metabolic disease model. Cytidine 5'-triphosphate synthase (CTPS) is a crucial enzyme for the de novo synthesis of CTP, governing the cellular level of CTP and phospholipid synthesis. CTPS has been found to form filaments known as cytoophidia, which are evolutionarily conserved in bacteria, archaea, and eukaryotes. Here, we show that CTPS functions in fat bodies to regulate body weight and starvation resistance in Drosophila. HFD-induced obesity enhances CTPS transcription and lengthens cytoophidia in larval adipocytes. CTPS depletion in the fat body prevented HFD-induced obesity, including body weight gain, adipocyte expansion, and lipid accumulation, by inhibiting the PI3K-Akt-SREBP axis. A dominant-negative form of CTPS also inhibits adipocyte expansion and down-regulates lipogenic genes. As a result, our findings not only establish a functional link between CTPS and lipid homeostasis but also highlight a potential role of CTPS manipulation in the treatment of HFD-induced obesity.

2023-08-30 | GSE221707 | GEO

Bacteria

Project description:Biological control of plant diseases

| PRJDB11063 | ENA

Project description:hyperuricemia

| PRJEB48022 | ENA

Histidine-dependent protein methylation is required for compartmentalization of CTP synthase

Project description:CTP synthase (CTPS) forms compartmentalized filaments in response to substrate availability and environmental nutrient status. However, the physiological role of filaments and mechanisms for filament assembly are not well understood. Here, we provide evidence that CTPS forms filaments in response to histidine influx during glutamine starvation. CTPS protein levels remained stable in the presence of histidine during nutrient deprivation, followed by rapid cell growth following nutrient replenishment. Tetramer conformation-based filament formation restricted CTPS enzyme activity duringnutrient deprivation. Furthermore, we demonstrated that filament formation controlled at two levels. Starvation stress/glutamine deficiency activates the GCN2/ATF4/MTHFD2 axis to accelerate the folate cycle in mitochondria for energy homeostasis. In addition, histidine promotes re-methylation of homocysteine by donating one-carbon to the cytosolic folate cycle. CTPS filament formation induced by histidine-mediated methylation maybe a strategy usedby cancer cells to maintain homeostasis and ensure a growth advantage in adverse environments.

2018-08-29 | GSE105251 | GEO

Identification of CTPS1 Filament Interacting Proteins_2019 dataset

Project description:CTP synthase (CTPS) catalyzes the formation of CTP in de novo pyrimidine biosynthesis pathway. Compartmentalization of CTPS into filamentous structure is evolutionarily conserved from E.coli, yeast, Drosophila, mice to humans. Previously, we demonstrated that histidine (His) mediated methylation promotes the formation of CTPS filament to suppress the enzymatic activity and preserve CTPS protein under Gln deprivation, which promotes cancer cell growth after stress alleviation. However, it remains unclear where and how these enigmatic structures are assembled. Here we used APEX2-mediated in vivo proximity labeling to identify proteins involve in the formation of human CTPS filaments.

2020-03-24 | PXD015507 | Pride

Identification of CTPS1 Filament Interacting Proteins

Project description:CTP synthase (CTPS) catalyzes the formation of CTP in de novo pyrimidine biosynthesis pathway. Compartmentalization of CTPS into filamentous structure is evolutionarily conserved from E.coli, yeast, Drosophila, mice to humans. Recently, we have demonstrated that histidine-mediated protein methylation promotes the formation of CTPS filament under glutamine and/or serum deprivation, which reduces its enzymatic activity and protects it from degradation. However, it is still unclear how the filament assembly takes place. In the current study, we used APEX2-mediated in vivo proximity labeling to identify proteins involved in CTPS filament formation.

2020-03-24 | PXD010921 | Pride

A woody plant degrading pathogen effector targets host glucose signaling protein VvRHIP1 to promote virulence

Project description:Lasiodiplodia theobromae is one of the causal agents of Grapevine trunk diseases, which becomes a tremendous threat to the grapevine production worldwide. Plant pathogens secrete diverse effectors to suppress host immune responses or regulate the host metabolism to promote diseases. Our results suggest that L. theobromae LtCre1 targets host VvRHIP1 to manipulate the sugar signaling pathway, through disrupting the association of VvRHIP1 and VvRGS1 complex.

2023-05-12 | GSE189162 | GEO

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