Machine-learning-assisted molecular design of phenylnaphthylamine-type antioxidants.

In this study, a total of 302 molecular structures of phenylnaphthylamine antioxidants based on N-phenyl-1-naphthylamine and N-phenyl-2-naphthylamine skeletons with various substituents were modeled by exhaustive methods. Antioxidant parameters, including the hydrogen dissociation energy, solubility parameter, and binding energy, were calculated through molecular simulations. Then, a group decomposition scheme was determined to decompose 302 antioxidants. The antioxidant parameters and decomposition results constituted machine-learning data sets. Using an artificial neural network model, a correlation coefficient between the predicted and true values above 0.88 and an average relative error within 6% were achieved. Random forest models were used to analyze the factors affecting antioxidant activity from chemical and physical perspectives; the results showed that amino and alkyl groups were conducive to improving antioxidant performance. Moreover, substituent positions 1, 7, and 10 of N-phenyl-1-naphthylamine and 3, 7, and 10 of N-phenyl-2-naphthylamine were found to be the optimal positions for modifications to improve antioxidant activity. Two potentially efficient phenylnaphthylamine antioxidant structures were proposed and their antioxidant parameters were also calculated; the hydrogen dissociation energy and solubility parameter decreased by more than 9% and 7%, respectively, whereas the binding energy increased by more than 16% compared with the benchmark of N-phenyl-1-naphthylamine. These results indicate that molecular simulation and machine learning could provide alternative tools for the molecular design of new antioxidants.

Study on the Effect of Polymer Excipients on the Dispersibility, Interaction, Solubility, and Scavenging Reactive Oxygen Species of Myricetin Solid Dispersion: Experiment and Molecular Simulation.

Although the preparation of amorphous solid dispersions can improve the solubility of crystalline drugs, there is still a lack of guidance on the micromechanism in the screening and evaluation of polymer excipients. In this study, a particular method of experimental characterization combined with molecular simulation was attempted on solubilization of myricetin (MYR) by solid dispersion. According to the analysis of the dispersibility and hydrogen-bond interaction, the effectiveness of the solid dispersion and the predicted sequence of poly(vinyl pyrrolidone) (PVP) > hypromellose (HPMC) > poly(ethylene glycol) (PEG) as the polymer excipient were verified. Through the dissolution, cell viability, and reactive oxygen species (ROS)-level detection, the reliability of simulation and micromechanism analysis was further confirmed. This work not only provided the theoretical guidance and screening basis for the miscibility of solid dispersions from the microscopic level but also served as a reference for the modification of new drugs.