月別: 2023年12月

[Published online Journal of Computer Chemistry, Japan Vol.22, 18-20, by J-STAGE]
<Title:> Theoretical Analysis of the Aggregation-Inhibition Effect of Arginine on Polyglutamine Protein by the Generalized-Ensemble Method
<Author(s):> Shoichi TANIMOTO, Hisashi OKUMURA
<Corresponding author E-Mill:> sktanimoto(at)ims.ac.jp
<Abstract:> The aggregation of polyglutamine (polyQ) proteins, which have the abnormal expansion of glutamine repeats, is a critical pathological hallmark of polyQ diseases. Experimental studies have shown an amino acid arginine uniquely inhibits the polyQ-protein aggregation. We performed replica-permutation molecular dynamics simulations to clarify the inhibitory effects of arginine on the polyQ-protein aggregation. We found arginine makes more contact with the polyQ protein than lysine, and this tendency of arginine likely inhibits the polyQ-protein aggregation.
<Keywords:> Molecular dynamics simulation, Generalized-ensemble algorithm, Polyglutamine, Protein-aggregation inhibition, Amyloid
<URL:> https://www.jstage.jst.go.jp/article/jccj/22/2/22_2023-0020/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.22, 21-23, by J-STAGE]
<Title:> 化学系特許中の表及びテキストからの材料知識データ抽出
<Author(s):> 我妻　正太郎, 竹内　理
<Corresponding author E-Mill:> shotaro.agatsuma.hd(at)hitachi.com
<Abstract:> Material Informatics (MI) needs large amount of data about materials. However, the cost of data extraction is very high. Therefore, chemical researchers are interested in technology to automatically extract the data from published documents such as patents. Previous technologies can extract the data from text in patents, but not tables. Therefore, we develop the data for MI extraction method from texts and tables in patents. In our evaluation, our method can reduce the time of data extraction by one-half. In the results, it can be expected that the new method can sufficiently reduce the cost of data extraction.
<Keywords:> Materials informatics, Machine learning, Natural Language Processing, Data Extraction
<URL:> https://www.jstage.jst.go.jp/article/jccj/22/2/22_2023-0023/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.22, 12-14, by J-STAGE]
<Title:> 量子化学計算と各種スペクトル情報を用いた化合物の自動同定手法の開発
<Author(s):> 熊谷　拓海, 中嶋　裕也, 清野　淳司
<Corresponding author E-Mill:> j-seino(at)aoni.waseda.jp
<Abstract:> Recent practical application of automated experiments using robotics, high-throughput experiments, and artificial intelligence technology has been progressing rapidly. In automated experiments, molecular identification is an important process for obtaining structural information on synthesized compounds and understanding their reactivity and chemical properties. In this study, we developed a system for automated molecular identification. The system uses spectral information and quantum chemical calculations, which provide no fluctuating data and have a potential to explore a wide range of chemical space. Numerical validation results suggested that the system is capable of efficient and accurate automated molecular identification in organic compounds with low molecular weight.
<Keywords:> Molecular identification; Quantum chemical calculation; Spectral data; Molecular generator; Organic compound
<URL:> https://www.jstage.jst.go.jp/article/jccj/22/2/22_2023-0029/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.22, 15-17, by J-STAGE]
<Title:> タンパク質に関する FMO-DPD シミュレーション用パラメータ算定と試行
<Author(s):> 太刀野　雄介, 土居　英男, 奥脇　弘次, 平野　秀典, 望月　祐志
<Corresponding author E-Mill:> fullmoon(at)rikkyo.ac.jp
<Abstract:> We have been promoting a project to evaluate the set of effective interaction parameters used in dissipative particle dynamics (DPD) simulations for all amino acid residues covering various proteins, based on fragment molecular orbital (FMO) calculations. This simulation protocol has been termed FMO-DPD. Here we report a test application to the folding problem of Chignolin and Superchignolin with hairpin structures, where 7 amino acid residues were considered.
<Keywords:> Fragment Molecular Orbital, FMO, Dissipative Particle Dynamics, DPD, Protein Folding, Chignolin
<URL:> https://www.jstage.jst.go.jp/article/jccj/22/2/22_2023-0019/_article/-char/ja/