Enhancing protein dynamics analysis with hydrophilic polyethylene glycol cross-linkers.
Brief Bioinform
; 25(2)2024 Jan 22.
Article
en En
| MEDLINE
| ID: mdl-38343324
ABSTRACT
Cross-linkers play a critical role in capturing protein dynamics in chemical cross-linking mass spectrometry techniques. Various types of cross-linkers with different backbone features are widely used in the study of proteins. However, it is still not clear how the cross-linkers' backbone affect their own structure and their interactions with proteins. In this study, we systematically characterized and compared methylene backbone and polyethylene glycol (PEG) backbone cross-linkers in terms of capturing protein structure and dynamics. The results indicate the cross-linker with PEG backbone have a better ability to capture the inter-domain dynamics of calmodulin, adenylate kinase, maltodextrin binding protein and dual-specificity protein phosphatase. We further conducted quantum chemical calculations and all-atom molecular dynamics simulations to analyze thermodynamic and kinetic properties of PEG backbone and methylene backbone cross-linkers. Solution nuclear magnetic resonance was employed to validate the interaction interface between proteins and cross-linkers. Our findings suggest that the polarity distribution of PEG backbone enhances the accessibility of the cross-linker to the protein surface, facilitating the capture of sites located in dynamic regions. By comprehensively benchmarking with disuccinimidyl suberate (DSS)/bis-sulfosuccinimidyl-suberate(BS3), bis-succinimidyl-(PEG)2 revealed superior advantages in protein dynamic conformation analysis in vitro and in vivo, enabling the capture of a greater number of cross-linking sites and better modeling of protein dynamics. Furthermore, our study provides valuable guidance for the development and application of PEG backbone cross-linkers.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Polietilenglicoles
/
Proteínas
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Brief Bioinform
Asunto de la revista:
BIOLOGIA
/
INFORMATICA MEDICA
Año:
2024
Tipo del documento:
Article
País de afiliación:
China