Pragmatic Coarse-Graining of Proteins: Models and Applications

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving larg...

Full description

Saved in:
Bibliographic Details
Published in:Journal of chemical theory and computation 2023-10, Vol.19 (20), p.7112-7135
Main Authors: Borges-Araújo, Luís, Patmanidis, Ilias, Singh, Akhil P., Santos, Lucianna H. S., Sieradzan, Adam K., Vanni, Stefano, Czaplewski, Cezary, Pantano, Sergio, Shinoda, Wataru, Monticelli, Luca, Liwo, Adam, Marrink, Siewert J., Souza, Paulo C. T.
Format: Article
Language:English
Subjects:
Biochemistry, Molecular Biology
Biological activity
Biophysics
Chemical Sciences
Computer Science
Granulation
Life Sciences
Modeling and Simulation
or physical chemistry
Parameterization
Proteins
Theoretical and
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.
ISSN:1549-9618
1549-9626
DOI:10.1021/acs.jctc.3c00733