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PXD015446 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleLiP-Quant, an automated chemoproteomic approach to identify drug targets in complex proteomes
DescriptionChemoproteomics is a key technology to characterize the mode of action of drugs, as it directly identifies the protein targets of bioactive compounds and aids in developing optimized leads. We have developed a drug target deconvolution approach with an automated data analysis pipeline, based on limited proteolysis coupled with mass spectrometry that works across species including in human cells (LiP-Quant). Here we demonstrate drug target identification by LiP-Quant across compound classes, including with drugs targeting kinases and phosphatases . We demonstrate that LiP-Quant identifies drug binding sites, a unique feature of this approach, and that it can be used to estimate drug EC50s in whole cell lysates . LiP-Quant identifies targets of both selective and promiscuous drugs and correctly discriminates drug binding to homologous proteins. We finally show that the LiP-Quant technology identifies targets of a novel research compound of biotechnological interest.
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterIlaria Piazza
SpeciesList scientific name: Botryotinia fuckeliana (Noble rot fungus) (Botrytis cinerea); NCBI TaxID: 40559; scientific name: Homo sapiens (Human); NCBI TaxID: 9606; scientific name: Saccharomyces cerevisiae (Baker's yeast); NCBI TaxID: 4932;
ModificationListmonohydroxylated residue; acetylated residue; iodoacetamide derivatized residue
InstrumentQ Exactive
Dataset History
RevisionDatetimeStatusChangeLog Entry
02019-09-13 04:56:16ID requested
12020-09-09 04:07:17announced
22022-02-13 16:34:05announced2022-02-14: Updated project metadata.
Publication List
Piazza I, Beaton N, Bruderer R, Knobloch T, Barbisan C, Chandat L, Sudau A, Siepe I, Rinner O, de Souza N, Picotti P, Reiter L, A machine learning-based chemoproteomic approach to identify drug targets and binding sites in complex proteomes. Nat Commun, 11(1):4200(2020) [pubmed]
Keyword List
ProteomeXchange project tag: EPIC-XS
curator keyword: Technical, Biomedical
submitter keyword: limited proteolysis, DIA-MS, LiP-MS,Drug identification
Contact List
Dr. Lukas Reiter and Prof. Dr. Paola Picotti
contact affiliationBiognosys AG, Schlieren, Switzerland (Dr. Lukas Reiter, lukas.reiter@biognosys.com) Institute of Molecular System Biology, ETH Zurich, Zurich, Switzerland (Prof. Dr. Paola Picotti, picotti@imsb.biol.ethz.ch)
contact emaillukas.reiter@biognosys.com
lab head
Ilaria Piazza
contact affiliationETH Zurich
contact emaililaria.piazza@bc.biol.ethz.ch
dataset submitter
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Dataset FTP location
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