Combined substituent number utilized machine learning for the development of antimicrobial agent.

The utilization of machine learning has a potential to improve the environment of the development of antimicrobial agents. For practical use of machine learning, it is important that the conversion of molecules information to an appropriate descriptor because too informative descriptor requires enormous computation time and experiments for gathering data, whereas a less informative descriptor has problems in validity. In this study, we utilized a descriptor only focused on substituent. The type and the position of substituents on the molecules that have a 4-quinolone structure (11,879 compounds) were converted to the combined substituent number (CSN). While the CSN does not include information on the detailed structure, physical properties, and quantum chemistry of molecules, the prediction model constructed by machine learning of CSN indicated a sufficient coefficient of determination (0.719 for the training dataset and 0.519 for the validation dataset). In addition, this CSN can easily construct the unknown molecules library which has a relatively consistent structure by recombination of substituents (32,079,318 compounds) and screening of them. The validity of the prediction model was also confirmed by growth inhibition experiments for E. coli using the model-suggested molecules and commercially available antimicrobial agents.

Total Synthesis of Azulene Derivative, a Blue Pigment Isolated from Lactarius indigo, and Colorant Application of Its Aqueous Dispersion.

Safety concerns in the food industry have increased the demand for natural food colorants. However, the application ranges of natural blue colorants are insufficient because they are scarce in nature, and the currently available natural blue dyes are limited to water-soluble products. In this study, we investigated a fat-soluble azulene derivative isolated from the mushroom Lactarius indigo as a potential candidate for a natural blue colorant. We developed its first total synthesis, where the azulene skeleton was constructed from a pyridine derivative and an ethynyl group was converted into an isopropenyl group using zirconium complexes. Moreover, nanoparticles of the azulene derivative were prepared via reprecipitation method, and their colorant ability was investigated in aqueous solutions. The new candidate food colorant exhibited a deep-blue color in an organic solvent and aqueous dispersion.

Total synthesis and antimicrobial evaluation of (+)-hygrophorone B12 and its analogues.

This paper describes the synthesis and evaluation of lead compounds with a new chemical skeleton that is not found in conventional antimicrobial agents. The biologically attractive cyclopentenoid (+)-hygrophorone B12, isolated from the fruiting bodies of Hygrophorus abieticola, and its analogues were synthesized in a longer linear sequence of twelve steps, starting from a cyclopentenone derivative. This synthesis involved the following crucial steps: (i) oximation of a ketone to stabilize the requisite aldehyde to install a side chain and (ii) coupling of an aldehyde with a side chain to assemble the desired hygrophorone. Then, the antimicrobial activity of these hygrophorones towards clinically relevant bacterial pathogens was evaluated. The results showed that hygrophorone B12 and its analogues are especially effective in preventing the proliferation of gram-positive bacteria. In addition, it was found that some structural features such as the presence of the enone moiety as well as the carbon-carbon triple bond on the hydrocarbon chain were pivotal to increase the antimicrobial activity of hygrophorone B. This study is expected to support the development of novel antimicrobial agents by flexibly synthesizing hygrophorone B analogues with a carbon five-membered ring skeleton from the common intermediate.