The ferulic acid is known to have strong antioxidant properties. In the present study, we have investigate the electronic structures of the ferulic acid and its radical extracting the hydrogen atom from its phenolic hydroxyl group. We have discussed the relation of the results with the radical scavenging activity with the DPPH reagent measured by Sakamoto et al. by machine learning.

View full abstract

Mixed raw materials are often used when thermosetting resins are synthesized. In such case, it is difficult to predict physical properties of resins by machine learning, owing to the deficits of dataset and/or to misclassification of raw materials. In order to solve this problems, we propose a method to calculate the feature of thermosetting resin based on raw material classification, and to predict physical properties of thermosetting resin by machine learning. First, the classificationｓ of raw materials were predicted by random forest using Extended Circular Fingerprint (ECFP) as an explanatory variable, representing the structural formula of raw materials. As a result, we could predict the classifications of raw materials, with high accuracy (F value = 0.96). Second, the resin physical properties were predicted by using ECFP. For the explanatory variables, we employed the features of the reaction intermediate, the curing condition of the resin, and the integration of ECFPs for each classification of raw materials. As a result, the elastic modulus could be predicted with the accuracy of R2 = 0.8. From these results, it was confirmed that the proposed method can predict the physical properties of the thermosetting resin synthesized by mixed raw materials.

View full abstract

Ni is mainly used in the methane steam reforming processes because of its high reactivity and low cost. The C-H cleavage of methane on Ni(111) surface was investigated by Blaylock et al. with DFT calculation. The strong C-H bond of methane is cleaved on the Ni surface, and further cleavage of C-H bonds leads to energetically stable CH* with low barriers. The CH* is converted into CO using H2O in the conventional process. If CH3* and CH2* lie in energy below CH* on an alloy surface, the direct conversion of methane into methanol, ethylene, etc. can be achieved because of the extended lifetime of the CH3* and CH2* intermediates. Based on this idea, we screened various binary alloys with DFT computations. We have found 6 kinds of binary alloys on which CH3* and CH2* are stable more than CH* so far.

View full abstract

The development of novel analytical methods based on bioinformatics and computational modelling is expected to offer innovative approaches in human medical science. Recently, we have performed computational analyses using some transcriptome and metabolome datasets for one of the human esophagus cancer cell line, TE-4, resulting in the generation of a model to explain the change of flow of biological reaction pathways. We extended this method in the current study to examine for differences in the behaviour between Cancer Stem Cells (CSCs) and non-CSCs. Our new approach revealed a previously uncharacterized role for the ornithine metabolic pathway in conferring chemo-resistance in CSC. In our analysis, we showed that CSCs reduce polyamine levels to resist chemotherapy. In contrast, polyamines in non-CSCs are maintained at a high level. The high polyamine level may act to inhibit lysine-specific demethylase 1A (LSD1) activity and induce epigenetic changes that increase cell survival, as suggested in previous reports.

View full abstract

[in Japanese]

View full abstract

Zeolite is aluminosilicate with a unique pore structure. Adsorbent properties and solid acidity are developed due to the unique pore structure, and it is used for adsorbent and hydrocarbon decomposition catalyst. In this study, the correlation between Si/All ratio of zeolite framework and pKa was investigated. In order to conduct this study, multiple models with different Si/Al ratios were created. H₃O⁺ was placed in the pores of these models, and the reactivity of acid sites was investigated by performing structural optimization calculations. As a result, proton desorption from the zeolite did not occur in the optimized structure of this model, and H₃O⁺ adsorption structure to zeolite was obtained. Therefore, it is a model which is not suitable for the evaluation of pKa, and it was found that other ingenuity is necessary.

View full abstract

The electronic similarity was calculated using electronic-structure calculations on beta-lactam antibacterial agent as descriptor. The ranking and the classification of antimicrobial agent were investigated. The correlation between electronic descriptors and minimum inhibitory concentration (MIC) of the antibacterial agent was also investigated. There was a correlation between the two categories of molecules, but clear correlations were not found for the molecules of the other categories. A regression model describing MIC for Escherichia coli showed that the correlation was found between the predicted value and the experimental value, indicating that the electronic descriptors are useful as explanatory variables to describe MIC.

View full abstract

FAS inhibitors inhibit the action of fatty acid synthase (FAS), which is abundantly present in cancer cells, and are therefore expected as one of new cancer treatment methods. In this study, electronic structure calculations were performed on 45 molecules which were supposed to have FAS inhibitory potency, and 17 kinds of electronic similarities were calculated using these numerical results. A multiple regression analysis was performed on the electronic descriptor and an equation for calculating a predicted value of the half inhibitory concentration was calculated from the numerical value of the electronic descriptor. The coefficient of determination R2 was 0.81, and a high correlation was found. Therefore, the obtained regression equation can reasonably reproduce the physical properties of the compounds, and is considered to be useful in the search for alternative compounds.

View full abstract

Fragment Molecular Orbital (FMO) method, developed by Kitaura et. al., is an approach to perform ab-initio quantum chemistry calculation for large molecule such as protein or nucleic acid by splitting covalent bonds. In addition, a more detailed analysis can be performed by Pair Interaction Energy Decomposition Analysis (PIEDA) that divides the interaction energy between fragments into its components. FMO method is implemented by GAMESS, ABINIT-MP, and PAICS. ABINIT-MP can perform fragmentation protein and nucleic acid automatically. However, manual fragmentation should be performed when calculating the system contains a large legend or performing detailed PIEDA (e.g. Analyzing interaction energy components of functional groups). The current fragmentation interface of ABINIT-MP requires selecting all atoms in fragments and it is more complicated than necessary. Thus, we developed the library for Molecular Operating Environment (MOE) to perform fragmentation the system and analyzing the FMO calculation result. It makes the entire of FMO workflow conclude in MOE.

View full abstract

Quantitatively grasping state change such as element distribution change due to manufacturing process is important in developing high performance devices. Electron energy loss spectroscopy (EELS) is known as a method for analyzing the state of a measurement sample. Multivariate Curve Resolution Alternative Least Squares (MCRALS) has been proposed as a method to obtain element concentration distribution from information measured by EELS. However, in MCRALS, when there is similarity between spectra of pure components contained in the sample, the estimation result becomes unstable. In this study, attention was paid to the fact that the concentration distribution must be smooth, and attempts were made to solve the instability by introducing a smoothing process on the concentration distribution in the process of calculating the concentration distribution of elements using MCRALS. Effectiveness was confirmed by applying the proposed method to the EELS data before and after annealing of the Ti / Ti - O sample layered on the Si substrate and estimating the state of oxygen diffusion.

View full abstract