グラフニューラルネットワークによる有機遷移金属反応の学習 [Published online J. Comput. Chem. Jpn., 21, 126-128, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 126-128, by J-STAGE]
<Title:> グラフニューラルネットワークによる有機遷移金属反応の学習
<Author(s):> 酒井 基至, 金重 光典, 安田 耕二
<Corresponding author E-Mill:> yasudak(at)imass.nagoya-u.ac.jp
<Abstract:> 深層学習による反応予測は,人が識別パターンを設計する必要がないため最近注目されている.しかし有機遷移金属反応は一見複雑で,深層学習の適応例は殆どなかった.我々は,論文や特許などから集めた数万件の実験反応を,素反応に分解したデータベースを構築し,グラフニューラルネットワークを用いて学習させた.最高で97.1%の精度で反応が予測できた.
<Keywords:> Graph neural network, Forward synthesis prediction, Organo transition metal reactions
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/4/21_2023-0012/_article/-char/ja/

中分子の膜透過性に対する計算手法の検討 [Published online J. Comput. Chem. Jpn., 21, 118-122, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 118-122, by J-STAGE]
<Title:> 中分子の膜透過性に対する計算手法の検討
<Author(s):> 高橋 輝行, Hengphasatporn Kowit, 原田 隆平, 重田 育照
<Abstract:> We used computational methods to predict the cell membrane permeability of a medium molecular drug, Bottromycin A2. We compared the three calculation methods, electronic structure calculation, molecular dynamics (MD) simulation, and empirical method, and examined which method was the best. As a result, we found that the first one is the best method among three methods treated, and that a prediction with high accuracy can be expected by increasing the number of experimental data.
<Keywords:> Membrane permeability, Medium Molecular Drug, Bottromycin A2, Cyclic Peptide, LogP
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/4/21_2023-0007/_article/-char/ja/

抗体軽鎖四量体の立体構造の理論解析 [Published online J. Comput. Chem. Jpn., 21, 123-125, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 123-125, by J-STAGE]
<Title:> 抗体軽鎖四量体の立体構造の理論解析
<Author(s):> Lian Duan, Hengphasatporn Kowit, 重田 育照
<Abstract:> In this study, the trajectories of the four protomers corresponding to the light chain tetramers of human antibodies were obtained from MD simulations. The four protomers, which should be symmetrically constructed, were not completely symmetrical in the simulations. The DSSP analysis and 2D-RMSD analysis of the four protomers showed that although the secondary structure of the four protomers is approximately the same, the deconvolution of part of the α helix leads to the asymmetry of the overall structure in the simulation. Although the number of interactions within the protomers decreases, that between the protomers increases, making the overall energy more stable. We hypothesize that the deconvolution is caused by the formation of the α helix fragment in the tetramer, and the hydrogen bonding and van der Waals forces between the protomers lead to the breakage of the hydrogen bond within the protomers, further leading to the disappearance of the α helix.
<Keywords:>
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/4/21_2023-0005/_article/-char/ja/

On the Thermodynamic Stability of Alloys: Combination of Neural Network Potential and Wang-Landau Sampling [Published online J. Comput. Chem. Jpn., 21, 111-117, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 111-117, by J-STAGE]
<Title:> On the Thermodynamic Stability of Alloys: Combination of Neural Network Potential and Wang-Landau Sampling
<Author(s):> Tien Quang NGUYEN, Yusuke NANBA, Michihisa KOYAMA
<Corresponding author E-Mill:> quang(at)shinshu-u.ac.jp
<Abstract:> Thermodynamic properties and atomic configuration of PdRu alloy were investigated using Wang-Landau Monte Carlo method in combination with a newly-developed universal neural network potential. By using this new potential, excess energy of PdRu alloy was calculated. It is found that PdRu alloy in FCC lattice is unstable in the full range of alloy composition. This agrees with previous study based on density functional theory. The combined method was able to determine the configurational density of states, from which thermodynamic properties of the alloy were derived. It is found that when temperature increases, the excess free energy of the alloy is reduced, increasing the possibility of alloy mixing. Depending on the composition, transition peaks appear at finite temperatures where there are changes of preferable atomic arrangement due to the effect of temperature via the configurational entropy. In addition, the analyses on short-range order parameter and bond fraction show that PdRu alloy prefers to be in segregated form, where Pd and Ru are immiscible at low temperature, consistent with the experimental observations. The random mixing of Pd and Ru atoms in the form of solid-solution can occur at high temperature.
<Keywords:> Alloy stability, Wang-Landau sampling, Neural network potential, Short-range order parameter, Bond fraction
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/4/21_2023-0015/_article/-char/ja/

FMOプログラムABINIT-MPの整備状況2022 [Published online J. Comput. Chem. Jpn., 21, 106-110, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 106-110, by J-STAGE]
<Title:> FMOプログラムABINIT-MPの整備状況2022
<Author(s):> 望月 祐志, 中野 達也, 坂倉 耕太, 渡邊 啓正, 佐藤 伸哉, 奥脇 弘次, 秋澤 和輝, 土居 英男, 大島 聡史, 片桐 孝洋
<Corresponding author E-Mill:> fullmoon(at)rikkyo.ac.jp
<Abstract:> We have been developing the ABINIT-MP program for fragment molecular orbital (FMO) calculations over 20 years. Several improvements for accelerated processing were made after the release of Open Version 2 Revision 4 at September 2021. Functionalities were enhanced as well. In this short report, we summarize such developments toward the next release of Revision 8.
<Keywords:> Fragment molecular orbital, FMO, ABINIT-MP, Supercomputer, A64FX, SX-Aurora TSUBASA
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/4/21_2022-0037/_article/-char/ja/

分子軌道エネルギーを説明変数とした機械学習 [Published online J. Comput. Chem. Jpn., 21, 103-105, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 103-105, by J-STAGE]
<Title:> 分子軌道エネルギーを説明変数とした機械学習
<Author(s):> 寺前 裕之, 玄 美燕, 高山 淳, 岡﨑 真理, 坂本 武史
<Corresponding author E-Mill:> teramae(at)gmail.com
<Abstract:> The values of the DPPH free radical scavenging ability values (IC50) of ferulic acid and its derivatives have been estimated by machine learning with only molecular orbital (MO) energies as the explanatory variables. We use four machine learning regression methods, Partial Least Square (pls), Random Forest (rf), Multi-Layer Perceptron Neural Network with Optional Monotonicity Constraints (monmlp) and eXtreme Gradient Boosting with Linear model (xgbLinear), using R-package caret. We use 22 molecules for the training set and 6 molecules for the test set. The root mean square (RMS) errors of predicted values for the test set are used for estimating the precision of the training. The best result is obtained by xgbLinear just using two MO energies (HOMO and LUMO). It has been proved that the IC50 values can be predicted by the molecular orbital energies only.
<Keywords:> Antioxidant effect, Radical scavenging ability, Equilibrium geometries, Eigenvalues of molecular orbital, Machine learning
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/4/21_2023-0001/_article/-char/ja/

分子集合体の弾性体モデルにもとづく粗視化剛性行列の力学的解釈 [Published online J. Comput. Chem. Jpn., 21, 99-102, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 99-102, by J-STAGE]
<Title:> 分子集合体の弾性体モデルにもとづく粗視化剛性行列の力学的解釈
<Author(s):> 北條 博彦, 中嶋 紘大, 岡村 彰太, 菊岡 龍太郎
<Corresponding author E-Mill:> houjou(at)iis.u-tokyo.ac.jp
<Abstract:> We have been developing a method for coarse-graining the low-frequency vibration modes of molecular assemblies, which affords a numerical representation of the down-sized stiffness matrix. In this study, we present an analytical representation of the stiffness matrix based on the elastic-body modeling of molecular assemblies. Comparison between the numerical and analytical data allows the 13 parameters regarding the dimension and mechanical properties of the putative elastic body. The results for 57 molecular dimers with various hydrogen-bond multiplicity demonstrate that the obtained parameters were physically reasonable and well-reproduced the wavenumbers of normal-mode vibrations.
<Keywords:> Intermolecular stiffness, Normal-mode analysis, Elastic-body mechanics, Finite element method, Trans-scale simulation
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/4/21_2023-0006/_article/-char/ja/

積層芳香族性を有するπスタック単分子接合の伝導特性に関する理論的研究 [Published online J. Comput. Chem. Jpn., 21, 87-89, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 87-89, by J-STAGE]
<Title:> 積層芳香族性を有するπスタック単分子接合の伝導特性に関する理論的研究
<Author(s):> 岡澤 一樹, 辻 雄太, 吉澤 一成
<Corresponding author E-Mill:> kazunari(at)ms.ifoc.kyushu-u.ac.jp
<Abstract:> π-stacked single-molecule junctions stacked with π-conjugated molecules have the potential to be used as building blocks for single-molecule scale three-dimensional integrated circuits. In this study, we investigate the relationship between π-stacking distance and conductance in face-to-face π-stacked single-molecule junctions with benzene as the monomer unit using the non-equilibrium Green’s function (NEGF), which combines the H ckel molecular orbital (HMO) and density functional theory (DFT) methods. As the π-stack distance between two benzene molecules decreases, the pseudo-para junction, which is insulating, turns conductive. Furthermore, it was found that the cause of this change can be explained by orbital interactions.
<Keywords:> Single-molecule junction, π-conjugated system, Stacked aromaticity, Frontier orbital, H ckel method
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/4/21_2023-0002/_article/-char/ja/

Lattice Folding Simulation of Peptide by Quantum Computation [Published online J. Comput. Chem. Jpn. Int. Ed., 9, -, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan -International Edition Vol.9, -, by J-STAGE]
<Title:> Lattice Folding Simulation of Peptide by Quantum Computation
<Author(s):> Rui SAITO, Koji OKUWAKI, Yuji MOCHIZUKI, Ryutaro NAGAI, Takumi KATO, Kenji SUGISAKI, Yuichiro MINATO
<Corresponding author E-Mill:> fullmoon(at)rikkyo.ac.jp
<Abstract:> Computational protein folding has attracted considerable interest over the years, including molecular simulations and artificial intelligence assisted methods. On the other hand, research and development of quantum computer hardware and software have been thriving recently. In this paper, we report a case study of peptide (PSVKMA) folding based on a two-dimensional lattice model, by using both the blueqat quantum simulator (called AutoQML) and the IonQ quantum device. As a result, it was found that the actual device was still susceptible to noises.
<Keywords:>
<URL:> https://www.jstage.jst.go.jp/article/jccjie/9/0/9_2022-0036/_html

有機分子触媒を用いたアミノ酸ラセミ化反応の理論的研究 [Published online J. Comput. Chem. Jpn., 21, 80-81, by J-STAGE]

[Published online Journal of Computer Chemistry, Japan Vol.21, 80-81, by J-STAGE]
<Title:> 有機分子触媒を用いたアミノ酸ラセミ化反応の理論的研究
<Author(s):> 渡辺 七都稀, 庄司 光男, 堀 優太, 重田 育照
<Corresponding author E-Mill:> watanabe.natsuki.sm(at)alumni.tsukuba.ac.jp
<Abstract:> Racemization of amino acid catalyzed by aldehyde and carboxylic acid has been proposed and widely used. Herein, we investigated the detailed racemization mechanism of alanine catalyzed by salicylaldehyde and acetic acid. Quantum chemistry calculations based on the density functional theory demonstrated that the dehydration reaction is the rate-determining step, and this dehydration step is enhanced by surrounding water molecules. We also discussed the dependence of the reaction rates on the type of amino acid.
<Keywords:> Racemization reaction, Organocatalytic reaction, Amino acid, Alanine, Density functional theory
<URL:> https://www.jstage.jst.go.jp/article/jccj/21/4/21_2023-0004/_article/-char/ja/