Identification and characterization of a glycosaminoglycan binding site on interleukin-10 via molecular simulation methods.
J Mol Graph Model
; 62: 97-104, 2015 Nov.
Article
en En
| MEDLINE
| ID: mdl-26409190
The biological function of the pleiotropic cytokine interleukin-10 (IL-10), which has an essential role in inflammatory processes, is known to be affected by glycosaminoglycans (GAGs). GAGs are essential constituents of the extracellular matrix with an important role in modulating the biological function of many proteins. The molecular mechanisms governing the IL-10-GAG interaction, though, are unclear so far. In particular, detailed knowledge about GAG binding sites and recognition mode on IL-10 is lacking, despite of its imminent importance for understanding the functional consequences of IL-10-GAG interaction. In the present work, we report a GAG binding site on IL-10 identified by applying computational methods based on Coulomb potential calculations and specialized molecular dynamics simulations. The identified GAG binding site is constituted of several positively charged residues, which are conserved among species. Exhaustive conformational space sampling of a series of GAG ligands binding to IL-10 led to the observation of two GAG binding modes in the predicted binding site, and to the identification of IL-10 residues R104, R106, R107, and K119 as being most important for molecular GAG recognition. In silico mutation as well as single-residue energy decomposition and detailed analysis of hydrogen-bonding behavior led to the conclusion that R107 is most essential and assumes a unique role in IL-10-GAG interaction. This structural and dynamic characterization of GAG-binding to IL-10 represents an important step for further understanding the modulation of the biological function of IL-10.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Interleucina-10
/
Glicosaminoglicanos
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
J Mol Graph Model
Asunto de la revista:
BIOLOGIA MOLECULAR
Año:
2015
Tipo del documento:
Article
País de afiliación:
Alemania
Pais de publicación:
Estados Unidos