Prediction of absorption wavelength using ensemble learning

Abstract

Fluorescent substances have been increasingly important for a wide range of applications, e.g., animal experiment in drug discovery, liquid crystal displays, and lighting devices. The compounds with the BODIPY structure, which is composed of dipyrromethene complexed with a disubstituted boron atom, are known to exhibit fluorescence and some practical properties, e.g., a sharp fluorescence peak, small influence of wavelength change dependent on solvent and high quantum yield. Here we propose an ensemble learning-based model that quickly and accurately predicts new BODIPY candidates with desirable physical properties. Compared with the quantum computation model (MAE = 24.71, R² = 0.84), the proposed model showed highly accurate performance (MAE = 17.34, R² = 0.90). Our model presented some descriptors that are important for the prediction of absorption wavelengths, which is consistent with known chemistry knowledge and shows the reliability of the model. Our model still does not properly utilize solvent information, indicating the possibility of further improvement in the foreseeable future.