Charge-patching method for the calculation of electronic structure of polypeptides
文献信息
Fu Ding, Lin-Wang Wang
Theoretical study of the electronic structures of protein is a fundamental challenge in computational biochemistry due to the large size of the systems. The electronic structure of a protein is important for some of the important protein functionalities, such as photosynthesis. In this study, we explored the charge-patching method to calculate the electronic structure of polypeptides. This method generates the charge densities of the systems by patching the charge motifs calculated from small prototype systems. The method was tested on a range of polypeptides, including the glycine polypeptide in 27-ribbon, α-helix, 310-helix, and β-strand structures. After the charge density profiles of these systems were obtained, the electronic structures of these glycine polypeptides were further calculated based on density functional theory (DFT) using a folded-spectrum method. The highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) were analyzed and compared with conventional direct DFT calculations. The charge-patching method results were found to be in good agreement with the directed DFT results.
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来源期刊
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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