CryoFold 2.0: Cryo-EM Structure Determination with MELD.
J Phys Chem A
; 127(17): 3906-3913, 2023 May 04.
Article
em En
| MEDLINE
| ID: mdl-37084537
ABSTRACT
Cryo-electron microscopy data are becoming more prevalent and accessible at higher resolution levels, leading to the development of new computational tools to determine the atomic structure of macromolecules. However, while existing tools adapted from X-ray crystallography are suitable for the highest-resolution maps, new tools are needed for lower-resolution levels and to account for map heterogeneity. In this article, we introduce CryoFold 2.0, an integrative physics-based approach that combines Bayesian inference and the ability to handle multiple data sources with the molecular dynamics flexible fitting (MDFF) approach to determine the structures of macromolecules by using cryo-EM data. CryoFold 2.0 is incorporated into the MELD (modeling employing limited data) plugin, resulting in a pipeline that is more computationally efficient and accurate than running MELD or MDFF alone. The approach requires fewer computational resources and shorter simulation times than the original CryoFold, and it minimizes manual intervention. We demonstrate the effectiveness of the approach on eight different systems, highlighting its various benefits.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Física
/
Simulação de Dinâmica Molecular
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article