MPLID: Membrane Protein-Lipid Interface Dataset v2.0.0

A large-scale dataset of experimentally validated lipid contact residues derived from experimentally determined structures in the Protein Data Bank. 100% EXPERIMENTAL LABELS - NO COMPUTATIONAL DATABASE DEPENDENCIES Dataset Statistics (v2.0.0) Proteins: 4,704 Total residues: 8,055,325 Contact residues: 80,439 Contact rate: 1.00% Sequence clusters: 813 (30% identity) Lipid codes recognized: 117 Train/Validation/Test Splits Train: 2,578 proteins, 4,907,696 residues Val: 1,051 proteins, 1,403,838 residues Test: 1,075 proteins, 1,743,791 residues Key Features Labels derived 100% from experimentally resolved lipids in PDB structures 4.0 Angstrom all-atom heavy-atom distance cutoff 4,704 proteins across all membrane protein classes Cluster-aware splits prevent data leakage Fully reproducible from public PDB data GitHub: https://github.com/omagebright/MPLID

Funded by São Paulo Research Foundation (FAPESP) grants 2023/02691-2 and 2025/23708-6.

Keywords

PDB, machine learning, lipid interactions, structural biology, membrane proteins, protein structure, training dataset, crystallography

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

Found an issue? Give us feedback

0

Average