Machine learned coarse-grained protein force-fields: Are we there yet?
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 …
includes the learning of flexible and accurate atomic-level force-fields for materials and …
Fuzziness and frustration in the energy landscape of protein folding, function, and assembly
S Gianni, MI Freiberger, P Jemth… - Accounts of chemical …, 2021 - ACS Publications
Conspectus Are all protein interactions fully optimized? Do suboptimal interactions
compromise specificity? What is the functional impact of frustration? Why does evolution not …
compromise specificity? What is the functional impact of frustration? Why does evolution not …
Machine learning of coarse-grained molecular dynamics force fields
Atomistic or ab initio molecular dynamics simulations are widely used to predict
thermodynamics and kinetics and relate them to molecular structure. A common approach to …
thermodynamics and kinetics and relate them to molecular structure. A common approach to …
[HTML][HTML] Coarse graining molecular dynamics with graph neural networks
Coarse graining enables the investigation of molecular dynamics for larger systems and at
longer timescales than is possible at an atomic resolution. However, a coarse graining …
longer timescales than is possible at an atomic resolution. However, a coarse graining …
Machine learning coarse-grained potentials of protein thermodynamics
A generalized understanding of protein dynamics is an unsolved scientific problem, the
solution of which is critical to the interpretation of the structure-function relationships that …
solution of which is critical to the interpretation of the structure-function relationships that …
Machine learning for protein folding and dynamics
Highlights•Advances in machine learning are changing the study of protein folding and
dynamics.•Machine learning is having a large impact in protein structure …
dynamics.•Machine learning is having a large impact in protein structure …
Native contacts determine protein folding mechanisms in atomistic simulations
The recent availability of long equilibrium simulations of protein folding in atomistic detail for
more than 10 proteins allows us to identify the key interactions driving folding. We find that …
more than 10 proteins allows us to identify the key interactions driving folding. We find that …
Perspective: Coarse-grained models for biomolecular systems
WG Noid - The Journal of chemical physics, 2013 - pubs.aip.org
By focusing on essential features, while averaging over less important details, coarse-
grained (CG) models provide significant computational and conceptual advantages with …
grained (CG) models provide significant computational and conceptual advantages with …
Improvements in Markov state model construction reveal many non-native interactions in the folding of NTL9
CR Schwantes, VS Pande - Journal of chemical theory and …, 2013 - ACS Publications
Markov State Models (MSMs) provide an automated framework to investigate the dynamical
properties of high-dimensional molecular simulations. These models can provide a human …
properties of high-dimensional molecular simulations. These models can provide a human …
Flow-matching: Efficient coarse-graining of molecular dynamics without forces
Coarse-grained (CG) molecular simulations have become a standard tool to study molecular
processes on time and length scales inaccessible to all-atom simulations. Parametrizing CG …
processes on time and length scales inaccessible to all-atom simulations. Parametrizing CG …