Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Chemical proteomics reveals the target landscape of 1,000 kinase inhibitor tool compounds

ABSTRACT: Here, we profiled the targets of 1,184 compounds from drug discovery projects in lysates of cancer cell lines using the Kinobeads approach. The resulting 500,000 compound-target interactions are available in ProteomicsDB and we exemplify how this molecular resource may be used for research. We anticipate that this molecular resource will aid drug discovery and chemical biology.

INSTRUMENT(S): Orbitrap Fusion Lumos, Q Exactive HF

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Bernhard Kuster

PROVIDER: MSV000092248 | MassIVE | Fri Jun 23 01:31:00 BST 2023

SECONDARY ACCESSION(S): PXD043230

REPOSITORIES: MassIVE

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Sun2019 - Predictive models of aqueous solubility of organic compounds.

Project description:Kinetic aqueous solubility (μg/mL) was experimentally determined using the same SOP in over 200 NCATS drug discovery projects. A final dataset of 11780 non-redundant molecules and their associated solubility was used to train a SVM classifier. Model Type: Predictive machine learning model. Model Relevance: Predicting the aqueous solubility of a chemical compound. Model Encoded by: Pauline (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos74bo

2024-04-22 | MODEL2404220003 | BioModels

Mass spectrometry based draft of the human proteome

Project description:This PXD project contains two projects published on ProteomicsDB (https://www.proteomicsDB.org) as integral part of the publication. The first project entitled 'human body map' (https://www.proteomicsdb.org/#projects/42) involves the analysis of 36 different human tissues and body fluids. The second project entitled 'Cellzome adopted' includes a collection of raw files which comprises identifications of 'missing proteins'.

2014-05-28 | PXD000865 | Pride

A CellAge epigenetic clock for expedited discovery of anti-ageing compounds in vitro

Project description:We aim to improve anti-ageing drug discovery, currently achieved through laborious and lengthy longevity analysis. Recent studies demonstrated that the most accurate molecular method to measure human age is based on CpG methylation profiles, as exemplified by several epigenetics clocks that can accurately predict an individual’s age. Here, we developed CellAge, a new epigenetic clock that measures subtle ageing changes in primary human cells in vitro. As such it provides a unique tool to measure effects of relatively short pharmacological treatments on ageing. We validated our CellAge clock against known longevity drugs such as rapamycin and trametinib. Moreover, we uncovered novel anti-ageing drugs, torin2 and Dactolisib (BEZ-235), demonstrating the value of our approach as a screening and discovery platform for anti-ageing strategies. CellAge outperforms other epigenetic clocks in measuring subtle ageing changes in primary human cells in culture. The tested drug treatments reduced senescence and other ageing markers, further consolidating our approach as a screening platform. Finally, we showed that the novel anti-ageing drugs we uncovered in vitro, indeed increased longevity in vivo. Our method expands the scope of CpG methylation profiling from measuring human chronological and biological age from human samples in years, to accurately and rapidly detecting anti-ageing potential of drugs using human cells in vitro, providing a novel accelerated discovery platform to test sought after geroprotectors.

2021-10-01 | E-MTAB-8327 | biostudies-arrayexpress

Benchmarking pathway analysis methods offer novel prognostic cancer biomarkers and therapeutics: application in bladder cancer

Project description:The pathogenesis of cancer is typically driven by alterations in multiple cellular pathways that are challenging to identify and target. However, it is unclear how suitable the existing pathway analysis tools are for unbiased discovery and ranking of dysregulated and/or cancer-specific pathways. Here, we created a new platform called Benchmark to evaluate the potential of pathway analysis tools for discovery under experimental conditions. Unexpectedly, we found that despite wide-spread success in confirming hypothesized dysregulated pathways, common pathway analysis tools are less than ideal for unbiased discovery. Nevertheless, our pathway ensemble tool (PET) that combines the rank statistics from the exisiting methods significantly enhanced discovery. We applied PET to transcriptomics data from 12 independent tumor types to identify prognostic pathways. We showed that the genes from prognostic pathways are excellent biomarkers and can define cancer molecular subtypes. Moreover, drug prediction to normalize genes from prognostic pathways identified effective known and novel drugs. Finally, in vitro and/or a xenograft models of bladder cancer treated with the top predicted drug significantly restricted tumor cells. We anticipate that our unbiased approach for pathway discovery will have tangible impacts on cancer management.

2024-06-03 | GSE222567 | GEO

Mycobacterium tuberculosis microarray to screen anti-tuberculosis compounds

Project description:Feature reduction of microarray data from mycobacteria treated with a variety of various clinical and investigational drugs We are using feature reduction to demonstrate that subsets of biomarker genes representative of the whole genome are sufficient for MOA classification and deconvolution in a medium-throughput microfluidic format ultimately leading to a cost effective and rapid tool for routine antibacterial drug-discovery programs.

2013-04-24 | E-GEOD-46212 | biostudies-arrayexpress

ProteomeTools - Building ProteomeTools based on a complete synthetic human proteome

Project description:The ProteomeTools project aims to derive molecular and digital tools from the human proteome to facilitate biomedical and life science research. Here, we describe the generation and multimodal LC-MS/MS analysis of >350,000 synthetic tryptic peptides representing nearly all canonical human gene products. This resource will be extended to 1.4 million peptides within two years and all data will be made available to the public in ProteomicsDB.

2017-02-09 | PXD004732 | Pride

ProteomeTools – Part II - Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning

Project description:"The ProteomeTools project aims to derive molecular and digital tools from the human proteome to facilitate biomedical and life science research. Here, we describe the second iteration of the generation and multimodal LC-MS/MS analysis of >220,000 synthetic tryptic peptides representing nearly all canonical human gene products. This resource will be extended to 1.4 million peptides and all data will be made available to the public in ProteomicsDB."

2019-05-21 | PXD010595 | Pride

RA-MAP: mapping the molecular immunological landscape in early rheumatoid arthritis with vaccine controls

Project description:<p>Rheumatoid arthritis (RA) is a chronic inflammatory disorder with poorly defined aetiology characterised by synovial inflammation with variable disease severity and drug responsiveness. To investigate the peripheral blood immune cell landscape of RA, we performed comprehensive clinical and molecular profiling of 267 RA patients and 52 healthy vaccine recipients for up to 18 months to establish a high quality sample biobank including plasma, serum, peripheral blood cells, urine, genomic DNA, RNA from whole blood, lymphocyte and monocyte subsets. We have performed extensive multi-omic immune phenotyping, including genomic, metabolomic, proteomic, transcriptomic and autoantibody profiling. We anticipate that these detailed clinical and molecular data will serve as a fundamental resource offering insights into immune-mediated disease pathogenesis, progression and therapeutic response, ultimately contributing to the development and application of targeted therapies for RA.</p>

2021-06-16 | MTBLS1497 | MetaboLights

A cross-disease human microglial framework identifies disease-enriched subsets and tool compounds for microglial polarization.

Project description:Human microglia play a pivotal role in neurological diseases, but few targeted therapies that directly modulate microglial state or function exist due to an incomplete understanding of microglial heterogeneity. We use single-cell RNA sequencing to profile live human microglia from autopsies or surgical resections across diverse neurological diseases and central nervous system regions. We observe a central divide between oxidative and heterocyclic metabolism and identify subsets associated with antigen presentation, motility, and proliferation. Specific subsets are enriched in susceptibility genes for neurodegenerative diseases or the disease-associated microglial signature. We validate subtypes in situ with an RNAscope-immunofluorescence pipeline and leverage our dataset as a classification resource, finding that iPSC model systems recapitulate substantial in vivo heterogeneity. Finally, we identify and validate candidates for chemically inducing subtype-specific states in vitro, showing that Camptothecin downregulates the transcriptional signature of disease-enriched subsets and upregulates a signature previously shown to be depleted in Alzheimer’s.

2024-10-18 | GSE202556 | GEO