Fatty amines and 1-monoglycerides with cytotoxic activity serve as ligands for a multipurpose receptor CD36

Cluster of differentiation 36 (CD36) is a cell-surface receptor that exhibits multifunctional properties with diverse ligands. A short segment of CD36, consisting of amino acids 149-168 (CD36149-168), has been shown to constitute a site for recognizing its lipid ligands (e.g., distinct forms of oxidized phospholipids). Recently, lauric acid was found to bind to the CD36 segment. Of interest, the fatty acid and some of its derivatives such as laurylamine and 1-monolaurin are well known to have a cytotoxic activity. This study aimed to assess whether lipids with cytotoxicity, including lauric acid derivatives, could be CD36 ligands by conducting an assay in which a fluorescently-labeled peptide containing human CD36149-168 was utilized. The assay results indicated that laurylamine and 1-monolaurin could bind to CD36149-168. Conversely, no evidence was obtained for non-cytotoxic derivatives (e.g., lauryl mercaptan) interacting with the CD36 segment. Other cytotoxic fatty amines (e.g., myristylamine) and 1-monoglycerides (e.g., 1-monocaprin) were also shown to be recognized by CD36149-168. Identification of these lipids offers an additional category for CD36 ligands, namely, "cytotoxic lipids," which further supports the role of this receptor as a multipurpose player.

Authors

Institutions

Publication Details

Journal
Biomedical Research
Published
2025-09-26
DOI
https://doi.org/10.2220/biomedres.46.189
Primary Topic
Receptor Mechanisms and Signaling
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fatty amines and 1-monoglycerides with cytotoxic activity serve as ligands for a multipurpose receptor CD36

Tatsuya Sugawara, Tsutomu Sasaki, Yuki Manabe, Mayuko Toyoda et al.
Biomedical Research
Receptor Mechanisms and Signaling
article

Fatty amines and 1-monoglycerides with cytotoxic activity serve as ligands for a multipurpose receptor CD36

Tatsuya Sugawara, Tsutomu Sasaki, Yuki Manabe, Mayuko Toyoda, Masayuki Yamasaki, Satoshi Tsuzuki, Kimihiko Mizutani
article en

Abstract

Cluster of differentiation 36 (CD36) is a cell-surface receptor that exhibits multifunctional properties with diverse ligands. A short segment of CD36, consisting of amino acids 149-168 (CD36149-168), has been shown to constitute a site for recognizing its lipid ligands (e.g., distinct forms of oxidized phospholipids). Recently, lauric acid was found to bind to the CD36 segment. Of interest, the fatty acid and some of its derivatives such as laurylamine and 1-monolaurin are well known to have a cytotoxic activity. This study aimed to assess whether lipids with cytotoxicity, including lauric acid derivatives, could be CD36 ligands by conducting an assay in which a fluorescently-labeled peptide containing human CD36149-168 was utilized. The assay results indicated that laurylamine and 1-monolaurin could bind to CD36149-168. Conversely, no evidence was obtained for non-cytotoxic derivatives (e.g., lauryl mercaptan) interacting with the CD36 segment. Other cytotoxic fatty amines (e.g., myristylamine) and 1-monoglycerides (e.g., 1-monocaprin) were also shown to be recognized by CD36149-168. Identification of these lipids offers an additional category for CD36 ligands, namely, "cytotoxic lipids," which further supports the role of this receptor as a multipurpose player.

Biomedical ResearchVol. 46(5)
Ryukoku University (JP), Kyoto University (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 77%
Receptor Mechanisms and Signaling
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.