COVID-19の経口治療薬開発に向けたハイブリッド型in Silico創薬 [Published online J. Comput. Chem. Jpn., 21, 48-51, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 48-51, by J-STAGE]
<Title:> COVID-19の経口治療薬開発に向けたハイブリッド型in Silico創薬
<Author(s):> 小清水 初花, 小野 純一, 福西 快文, 中井 浩巳
<Corresponding author E-Mill:> nakai(at)waseda.jp
<Abstract:> Hybrid in silico drug discovery was performed by combining large-scale quantum molecular dynamics (QMD) simulations with the conventional in silico drug discovery, focusing on developing covalent inhibitors against the main protease (Mpro) of SARS-CoV-2, the virus responsible for ongoing COVID-19 pandemic. The crystal structures and instantaneous structures obtained from the large-scale QMD simulations for Mpro were used as receptors in ensemble docking to estimate the binding affinities of the four ligands: the natural substrate recognized by Mpro, that recognized by the other enzyme of SARS-CoV-2, approved covalent inhibitor (PF-07321332), and the new candidate compound X determined from virtual screening. The present result shows that the binding affinity of X was comparable to that of PF-07321332, demonstrating the potency of our drug discovery.
<Keywords:> COVID-19, In silico drug discovery, Quantum molecular dynamics, Main protease, Covalent drug
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/2/21_2022-0029/_article/-char/ja/

量子コンピュータを利用したタンパク質の畳み込みモデル [Published online J. Comput. Chem. Jpn., 21, 39-42, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 39-42, by J-STAGE]
<Title:> 量子コンピュータを利用したタンパク質の畳み込みモデル
<Author(s):> 齊藤 瑠偉, 奥脇 弘次, 望月 祐志, 永井 隆太郎, 加藤 拓己, 杉﨑 研司, 湊 雄一郎
<Corresponding author E-Mill:> fullmoon(at)rikkyo.ac.jp
<Abstract:> We have performed a series of quantum computations for folding of the PSVKMA peptide by using the blueqat AutoQML simulator by which a given problem can be converted from QUBO (quadratic unconstrained binary optimization) of quantum annealing to QAOA (quantum approximate optimization algorithm) of VQE (variational quantum eigensolver). The IonQ quantum system of ion-trap type was utilized as well. A three qubit problem was successful by both. However, the situation became difficult for a five qubit case, especially for the IonQ having vulnerability to noises.
<Keywords:> Quantum computation, Protein folding, Lattice model, QUBO, QAOA
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/2/21_2022-0022/_article/-char/ja/

β-LiAlSiO4結晶の分子動力学法に用いる原子間相互作用の改良 [Published online J. Comput. Chem. Jpn., 21, 33-35, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 33-35, by J-STAGE]
<Title:> β-LiAlSiO4結晶の分子動力学法に用いる原子間相互作用の改良
<Author(s):> 大垣 毅弥, 澤口 直哉
<Corresponding author E-Mill:> nasawa(at)mmm.muroran-it.ac.jp
<Abstract:> Thermal change of lattice parameters of β-LiAlSiO4 crystal simulated by molecular dynamics simulation was improved by revision of the interatomic potential. The discontinuity of thermal change of c-axis lattice parameter observed in the previous work between 800 K and 900 K was dissolved, but the simulated linear thermal expansion of c-axis was smaller than the reference data. The visualized shift of relative coordinates of each atom with the temperature increase from 300 K to 1200 K showed the different variation between the two types of double helix structures that exist in the unit cell.
<Keywords:> Molecular dynamics, ??i??β??/i??-eucryptite, ??i??β??/i??-LiAlSiO4, Thermal expansion, Structure analysis
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/2/21_2022-0023/_article/-char/ja/

少数データを効率的に利用したデータ駆動型反応機構探索 [Published online J. Comput. Chem. Jpn., 21, 36-38, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 36-38, by J-STAGE]
<Title:> 少数データを効率的に利用したデータ駆動型反応機構探索
<Author(s):> 塩谷 友希, 嶋田 五百里
<Corresponding author E-Mill:> iori(at)shinshu-u.ac.jp
<Abstract:> Chemical reaction neural network (CRNN) is a machine learning model that enables a data-driven search of chemical reaction mechanisms by incorporating reaction kinetics theory into the neural network architecture. Conventionally, 103 order data were required for searching a simple reaction system, but the reduction in the number of data required for CRNN is expected to enable its application to various experimental systems. In this study, we investigated the number of data required for prediction in the CRNN. The result showed that prediction of the reaction is possible with as few as 180 data by avoiding falling into local optimal solutions. We also confirmed that incorporating the concept of material balance into loss function has effect of reducing the computational complexity.
<Keywords:> Reaction mechanism, Kinetics, Chemical reaction neural network, Physics-informed machine learning, Data-driven
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/2/21_2022-0024/_article/-char/ja/

VR-MD: スマホ VR で実施する分子動力学計算とその教育への適用 [Published online J. Comput. Chem. Jpn., 21, 43-44, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 43-44, by J-STAGE]
<Title:> VR-MD: スマホ VR で実施する分子動力学計算とその教育への適用
<Author(s):> 吉川 信明, 松田 健郎, 梶田 晴司, 佐藤 宗太, 谷川 智洋
<Corresponding author E-Mill:> kikkawa(at)mosk.tytlabs.co.jp
<Abstract:> An application for molecular dynamics (MD) simulations was implemented on a smartphone for utilizing virtual reality (VR) in chemistry education. This application consists only of a smartphone, a simple VR lens, and an on-board camera. The screen displays molecular motions equivalent to MD calculations in actual research. The molecules move synchronously with the six-dimensional movements of the user’s head. The on-board camera also recognizes hand coordinates, allowing the user to “touch” and “grab” the molecules through the hand model displayed in the VR space. This application enables users to intuitively understand molecular motion. A special lecture was held at high schools using this application, and survey results shows that students’ understanding of molecules improved.
<Keywords:> Chemical education, Virtual reality, Smartphone application, Molecular dynamics
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/2/21_2022-0028/_article/-char/ja/

Theoretical Study on the Reaction Mechanism of the Water-Splitting Process on Cobalt Oxide Catalysts [Published online J. Comput. Chem. Jpn., 21, 45-47, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 45-47, by J-STAGE]
<Title:> Theoretical Study on the Reaction Mechanism of the Water-Splitting Process on Cobalt Oxide Catalysts
<Author(s):> Narumi FUJIWARA, Koichi YAMASHITA, Azusa MURAOKA
<Corresponding author E-Mill:> muraokaa(at)fc.jwu.ac.jp
<Abstract:> In recent years, artificial photosynthesis has attracted attention as a mechanism for generating fuel by sunlight irradiation of a photocatalyst to split water into O and H. Elucidation of the four-electron oxidation reaction mechanism of this split is essential for the development of highly active photocatalysts. A reaction mechanism has been proposed for Co3O4 catalysts using time-resolved Fourier transform infrared spectroscopy to identify the intermediates in the oxidation of water under reaction. In this study, density functional theory was used to examine the mechanism of the four-electron reaction of the Co3O4 photocatalysts.
<Keywords:> cobalt oxide, Photocatalyst, Four-electron oxidation reaction, DFT
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/2/21_2022-0030/_article/-char/ja/