Coarse-grained (CG) simulations reduce the complexity of the system and allow for longer time and large length scales comparable to experiments, not possible by atomistic models. In this regard, several CG force fields such as MARTINI, UNRES, SIRAH, etc. introduce effective interactions based on thermodynamics principles and the choice of the most relevant degrees-of-freedom. Several of these approaches when combined with structure-based models capture large-scale conformational changed of biomolecules, e.g., Go-MARTINI, supporting single-molecule force spectroscopy and expanding applications in mechanobiology. In addition, bottom-up approaches between different methods from quantum to mesoscopic approaches going through CG methods in a multiscale fashion has been employed to capture relevant features in each scale and build strategies for bridging the gap between them. This Research Topic aims to bring together theoretical and computational experts in quantum chemistry, molecular dynamics and continuum modelling, as well as interdisciplinary research aided by experimental data (i.e., SMFS, SAXS, NMR, etc.) and machine learning protocols.
Molecular simulation revolutionized our world by controlling the design of materials with outstanding properties for energy and data storage, drug discovery, etc. Describing the structure-function relationship in biomolecules (e.g., protein, polysaccharides, etc.) under a computational microscope had direct impact on applied research. Atomistic description of large-scale biomolecular conformational transitions still faces challenges as underlying time and length scales are beyond traditional scales in all-atom molecular dynamics (MD). Development of novel methodologies aided by coarse graining and machine learning ideas which are not system specific and under heterogenous conditions are nowadays necessary to bridge the gap between molecular motion and mesoscopic processes. This topic focuses on the recent development of multiscale simulation for biomolecules and potential biotechnological applications.
In this Research Topic we are looking for original research, reviews, mini reviews and perspective articles on themes including but not limited to:
• Novel methods for building, sampling and analyzing large biomolecular assemblies and large conformational change in biomolecules
• Development of multiscale approaches from quantum to continuum scales
• Mechanical and energetic characterization of large biomolecular complexes
• Design of machine learning protocols for acceleration of molecular dynamics simulation
• Enhanced sampling techniques of rare events in biosystems
Coarse-grained (CG) simulations reduce the complexity of the system and allow for longer time and large length scales comparable to experiments, not possible by atomistic models. In this regard, several CG force fields such as MARTINI, UNRES, SIRAH, etc. introduce effective interactions based on thermodynamics principles and the choice of the most relevant degrees-of-freedom. Several of these approaches when combined with structure-based models capture large-scale conformational changed of biomolecules, e.g., Go-MARTINI, supporting single-molecule force spectroscopy and expanding applications in mechanobiology. In addition, bottom-up approaches between different methods from quantum to mesoscopic approaches going through CG methods in a multiscale fashion has been employed to capture relevant features in each scale and build strategies for bridging the gap between them. This Research Topic aims to bring together theoretical and computational experts in quantum chemistry, molecular dynamics and continuum modelling, as well as interdisciplinary research aided by experimental data (i.e., SMFS, SAXS, NMR, etc.) and machine learning protocols.
Molecular simulation revolutionized our world by controlling the design of materials with outstanding properties for energy and data storage, drug discovery, etc. Describing the structure-function relationship in biomolecules (e.g., protein, polysaccharides, etc.) under a computational microscope had direct impact on applied research. Atomistic description of large-scale biomolecular conformational transitions still faces challenges as underlying time and length scales are beyond traditional scales in all-atom molecular dynamics (MD). Development of novel methodologies aided by coarse graining and machine learning ideas which are not system specific and under heterogenous conditions are nowadays necessary to bridge the gap between molecular motion and mesoscopic processes. This topic focuses on the recent development of multiscale simulation for biomolecules and potential biotechnological applications.
In this Research Topic we are looking for original research, reviews, mini reviews and perspective articles on themes including but not limited to:
• Novel methods for building, sampling and analyzing large biomolecular assemblies and large conformational change in biomolecules
• Development of multiscale approaches from quantum to continuum scales
• Mechanical and energetic characterization of large biomolecular complexes
• Design of machine learning protocols for acceleration of molecular dynamics simulation
• Enhanced sampling techniques of rare events in biosystems
