Unmasking crucial residues in adipose triglyceride lipase for coactivation with comparative gene identification-58.
J Lipid Res
; 65(1): 100491, 2024 01.
Article
en En
| MEDLINE
| ID: mdl-38135254
ABSTRACT
Lipolysis is an essential metabolic process that releases unesterified fatty acids from neutral lipid stores to maintain energy homeostasis in living organisms. Adipose triglyceride lipase (ATGL) plays a key role in intracellular lipolysis and can be coactivated upon interaction with the protein comparative gene identification-58 (CGI-58). The underlying molecular mechanism of ATGL stimulation by CGI-58 is incompletely understood. Based on analysis of evolutionary conservation, we used site directed mutagenesis to study a C-terminally truncated variant and full-length mouse ATGL providing insights in the protein coactivation on a per-residue level. We identified the region from residues N209-N215 in ATGL as essential for coactivation by CGI-58. ATGL variants with amino acids exchanges in this region were still able to hydrolyze triacylglycerol at the basal level and to interact with CGI-58, yet could not be activated by CGI-58. Our studies also demonstrate that full-length mouse ATGL showed higher tolerance to specific single amino acid exchanges in the N209-N215 region upon CGI-58 coactivation compared to C-terminally truncated ATGL variants. The region is either directly involved in protein-protein interaction or essential for conformational changes required in the coactivation process. Three-dimensional models of the ATGL/CGI-58 complex with the artificial intelligence software AlphaFold demonstrated that a large surface area is involved in the protein-protein interaction. Mapping important amino acids for coactivation of both proteins, ATGL and CGI-58, onto the 3D model of the complex locates these essential amino acids at the predicted ATGL/CGI-58 interface thus strongly corroborating the significance of these residues in CGI-58-mediated coactivation of ATGL.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Inteligencia Artificial
/
Lipasa
Límite:
Animals
Idioma:
En
Revista:
J Lipid Res
Año:
2024
Tipo del documento:
Article
País de afiliación:
Austria