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PXD041587-1

PXD041587 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleLarge-scale chemoproteomics expedites ligand discovery and predicts ligand behavior in cells
DescriptionChemical modulation of protein function enables a mechanistic understanding of biological circuits and represents the foundation of most medicines. However, despite major efforts over decades of research, around 80% of the human proteome still lack functional ligands. Chemical proteomics allowed the advancement of fragment-based ligand discovery (FBLD) towards cellular systems and emerged as a promising strategy to detect reversible fragment-protein interactions that can be furnished into bioactive chemical probes. Limitations in scale and throughput have, however, stymied the interpretation of the resulting ligandability maps, thus complicating the identification of specific and actionable fragment-protein interactions. Here, we report reversible, global ligandability maps for 435 structurally different fragments, collectively representing 6739 discrete interactions. We benchmark the dataset by showing that identified fragments can be advanced to active chemical probes. Integrating multi-layered ligandability portraits with artificial intelligence (AI) and machine learning (ML) enabled quantitative and qualitative predictions of fragment interactomes via chemically interpretable models. The resulting, interactive catalogue of fragment-protein interactions and predictive models is expected to expedite ligand discovery efforts in a community-wide fashion and should facilitate the pursuit of hitherto undrugged target proteins.
HostingRepositoryPRIDE
AnnounceDate2024-05-07
AnnouncementXMLSubmission_2024-05-07_09:36:56.875.xml
DigitalObjectIdentifierhttps://dx.doi.org/10.6019/PXD041587
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportSupported dataset by repository
PrimarySubmitterNara Marella
SpeciesList scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationListphosphorylated residue; L-methionine removal; acetylated residue; monohydroxylated residue; iodoacetamide derivatized residue
InstrumentOrbitrap Fusion Lumos
Dataset History
RevisionDatetimeStatusChangeLog Entry
02023-04-17 13:30:44ID requested
12024-05-07 09:36:57announced
Publication List
10.6019/PXD041587;
Offensperger F, Tin G, Duran-Frigola M, Hahn E, Dobner S, Ende CWA, Strohbach JW, Rukavina A, Brennsteiner V, Ogilvie K, Marella N, Kladnik K, Ciuffa R, Majmudar JD, Field SD, Bensimon A, Ferrari L, Ferrada E, Ng A, Zhang Z, Degliesposti G, Boeszoermenyi A, Martens S, Stanton R, M, ΓΌ, ller AC, Hannich JT, Hepworth D, Superti-Furga G, Kubicek S, Schenone M, Winter GE, Large-scale chemoproteomics expedites ligand discovery and predicts ligand behavior in cells. Science, 384(6694):eadk5864(2024) [pubmed]
10.1126/science.adk5864;
Keyword List
submitter keyword: machine learning, bioactive, drug, Screening, chemical probe, fragment-protein interaction, FBLD, AI,Chemical Proteomics, Ligandability
Contact List
Georg Winter
contact affiliationCenter for Molecular Medicine of the Austrian Academy of Sciences (CeMM)
contact emailGWinter@cemm.oeaw.ac.at
lab head
Nara Marella
contact affiliationCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences
contact emailnara.marella@outlook.com
dataset submitter
Full Dataset Link List
Dataset FTP location
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