Over the last few years, coarse-grained molecular dynamics has emerged as a way to model
large and complex systems in an efficient and inexpensive manner due to its lowered …

The traditional computational modeling of protein structure, dynamics, and interactions
remains difficult for many protein systems. It is mostly due to the size of protein …

The successful recent application of machine learning methods to scientific problems
includes the learning of flexible and accurate atomic-level force-fields for materials and …

The Martini model, a coarse-grained force field for biomolecular simulations, has found a
broad range of applications since its release a decade ago. Based on a building block …

Computational modeling of biological systems is challenging because of the multitude of
spatial and temporal scales involved. Replacing atomistic detail with lower resolution …

By focusing on essential features, while averaging over less important details, coarse-
grained (CG) models provide significant computational and conceptual advantages with …

The molecular details involved in the folding, dynamics, organization, and interaction of
proteins with other molecules are often difficult to assess by experimental techniques …

A new version of the coarse-grained (CG) SIRAH force field for proteins has been
developed. Modifications to bonded and non-bonded interactions on the existing molecular …

Modeling of macromolecular structures and interactions represents an important challenge
for computational biology, involving different time and length scales. However, this task can …

The aim of molecular coarse-graining approaches is to recover relevant physical properties
of the molecular system via a lower-resolution model that can be more efficiently simulated …