The Lipid Interactome: An interactive and open access platform for exploring cellular lipid-protein interactomes.
Lipid-protein interactions play essential roles in cellular signaling and membrane dynamics, yet their systematic characterization has long been hindered by the inherent biochemical properties of lipids. Recent advances in functionalized lipid probes - equipped with photoactivatable crosslinkers, affinity handles, and photocleavable protecting groups - have enabled proteomics-based identification of lipid interacting proteins with unprecedented specificity and resolution. Despite the growing number of published lipid interactomes, there remains no centralized effort to harmonize, compare, or integrate these datasets. The Lipid Interactome addresses this gap by providing a structured, interactive web portal that adheres to FAIR data principles - ensuring that lipid interactome studies are Findable, Accessible, Interoperable, and Reusable. Through standardized data formatting, interactive visualizations, and direct cross-study comparisons, this resource enables researchers to systematically explore the protein-binding partners of diverse bioactive lipids. By consolidating and curating lipid interactome proteomics data from multiple studies, the Lipid Interactome database serves as a critical tool for deciphering the biological functions of lipids in cellular systems.
Authors
- Gaelen Guzman (ORCID: https://orcid.org/0000-0002-7696-6034)
- Fikadu Tafesse (ORCID: https://orcid.org/0000-0002-8575-4164)
- Jeremy M. Baskin (ORCID: https://orcid.org/0000-0003-2939-3138)
- Frank Stein (ORCID: https://orcid.org/0000-0001-9695-1692)
- Carsten Schultz (ORCID: https://orcid.org/0000-0002-5824-2171)
- André Nadler (ORCID: https://orcid.org/0000-0001-6329-3910)
Institutions
- Oregon Health & Science University (US)
- Cornell University (US)
- European Molecular Biology Laboratory (DE)
- Max Planck Institute of Molecular Cell Biology and Genetics (DE)
Publication Details
- Journal
- PubMed
- Published
- 2025-07-30
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00