月別: 2024年7月

[Published online Journal of Computer Chemistry, Japan -International Edition Vol.10, -, by J-STAGE]
<Title:> Reconstruction of Four-Body Statistical Pseudopotential for Protein-Peptide Docking
<Author(s):> Tae YAMAMOTO, Yasuhiro IKABATA, Hitoshi GOTO
<Corresponding author E-Mill:> gotoh(at)tut.jp
<Abstract:> We constructed the four-body statistical pseudopotential proposed by Krishnamoorthy and Tropsha, which is a type of coarse-grained potential previously used for protein-peptide docking, using different data sets. The first data set is composed of crystal structures of proteins that satisfy the conditions specified using PISCES, a protein sequence culling server. The second data set consists of crystal structures of protein-protein complexes obtained from the PDBbind-CN database. The four-body potential has 44275 patterns of scores, depending on the type of amino acid in the quadruplet of residues and the continuity of amino acid in the sequence of protein or peptide. While the PISCES-based data set covers almost all patterns, docking simulations revealed that both potentials provided comparable accuracy in reproducing experimentally determined peptide binding poses.
<Keywords:> Docking simulation, Protein-peptide complex, Four-body statistical pseudopotential, Coarse-grained potential, Peptide binding pose
<URL:> https://www.jstage.jst.go.jp/article/jccjie/10/0/10_2023-0039/_html

[Advanced Published online Journal of Computer Chemistry, Japan, by J-STAGE]
<Title:> FMODBからのデータ取得用Pythonスクリプトの開発
<Author(s):> 松岡　壮太, 柿沼　紗也果, 奥脇　弘次, 土居　英男, 望月　祐志
<Corresponding author E-Mill:> fullmoon(at)rikkyo.ac.jp
<Abstract:> フラグメント分子軌道(FMO)計算による相互作用解析は，特に理論創薬の分野でよく使われており，計算結果をデータベース化したFMODBも整備・公開されている．本論文では，FMODBにアクセスしてデータを取得するPythonツールを開発した．取得データをscikit-learnなど機械学習のツールで処理することも可能である．
<Keywords:> Fragment molecular orbital, FMO, FMODB, Python, Machine learning
<URL:> https://www.jstage.jst.go.jp/article/jccj/advpub/0/advpub_2023-0040/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.23, 40-43, by J-STAGE]
<Title:> The Analysis of Defect Structure of Sn-based Perovskite Solar Cell Materials Using First-principles Calculations
<Author(s):> Mai OTAKE, Suzune OMORI, Sana KOGURE, Masanori KANEKO, Koichi YAMASHITA, Azusa MURAOKA
<Corresponding author E-Mill:> muraokaa(at)fc.jwu.ac.jp
<Abstract:> While Sn-based perovskite solar cells have photoelectronic properties comparable to those of lead halide perovskites, their low photoelectric conversion efficiency is a problem. The main cause of this problem is the defect level caused by the presence of defects in the crystal. In this study, we analyzed the defect structures in FASnI₃ and MASnI₃ perovskites using first-principles calculations and focused on the correlation between the photoelectric conversion efficiency and defect levels.In both structures, the defect formation energy of V_Sn was low and tin tended to be easily removed. In FASnI₃, by changing the chemical potential to the Sn-rich, I-poor condition, the defect levels that were easy to form in the Sn-poor, I-rich condition became defect levels that were hard to form. It was also found that MASnI₃ has a wide range of thermodynamically stable regions with no defect levels that are prone to form under any chemical potential condition. Therefore, from the viewpoint of structural stability and structural defects, MA is preferable to FA as the A-site cation of Sn-based perovskite.
<Keywords:> Sn-based perovskite, Lead-free perovskite, Defect, Deep levels, Defect formation energy
<URL:> https://www.jstage.jst.go.jp/article/jccj/23/1/23_2024-0010/_article/-char/ja/