AromTool: predicting aromatic stacking energy using an atomic neural network model

文献情報

出版日 2021-06-29

DOI 10.1039/D1CP01954F

インパクトファクター 3.676

著者

Wengan He, Danhong Liang, Hongjuan Diao, Ruibo Wu

原文を見る

要旨

Aromatic stacking exists widely and plays important roles in protein–ligand interactions. Computational tools to automatically analyze the geometry and accurately calculate the energy of stacking interactions are desired for structure-based drug design. Herein, we employed a Behler–Parrinello neural network (BPNN) to build predictive models for aromatic stacking interactions and further integrated it into an open-source Python package named AromTool for benzene-containing aromatic stacking analysis. Based on extensive testing, AromTool presents desirable precision in comparison to DFT calculations and excellent efficiency for high-throughput aromatic stacking analysis of protein–ligand complexes.

掲載誌

Physical Chemistry Chemical Physics

CiteScore: 5.5

自己引用率: 10.3%

年間論文数: 3036

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.