期刊
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
卷 19, 期 20, 页码 7112-7135出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jctc.3c00733
关键词
-
In this review, the authors provide an overview of pragmatic coarse-grained (CG) protein models, which combine physics-based implementation and top-down experimental approaches for parameterization. These CG models, with most protein residues represented by at least two beads, allow for some degree of chemical specificity. The review includes discussions on recent applications and future perspectives in the field.
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据