Multiscale simulations for understanding the evolution and mechanism of hierarchical peptide self-assembly
文献信息
Qianli Zou
Hierarchical self-assembly, abundant in biological systems, has been explored as an effective bottom-up method to fabricate highly ordered functional superstructures from elemental building units. Biomolecules, especially short peptides consisting of several amino acids, are a type of elegant building blocks due to their advantages of structural, mechanical, and functional diversity as well as high biocompatibility and biodegradability. The hierarchical self-assembly of peptides is a spontaneous process spanning multiple time and length scales under certain thermodynamics and kinetics conditions. Therefore, understanding the mechanisms of dynamic processes is crucial to directing the construction of complicated biomimetic systems with multiple functionalities. Multiscale molecular simulations that combine and systematically link several hierarchies can provide insights into the evolution and dynamics of hierarchical self-assembly from the molecular level to the mesoscale. Herein, we provided an overview of the simulation hierarchies in the general field of peptide self-assembly modeling. In particular, we highlighted multiscale simulations for unraveling the mechanisms underlying the dynamic self-assembly process with an emphasis on weak intermolecular interactions in the process stages and the energies of different molecular alignments as well as the role of thermodynamic and kinetic factors at the microscopic level.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.










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