Efficient Exploration of Phenol Derivatives Using QUBO Solvers with Group Contribution-Based Approaches

Molecule screening from a vast number of possible compounds is a challenging task. The emergence of quadratic unconstrained binary optimization (QUBO) solvers provides alternatives to address this issue. We propose a process for screening molecules by integrating QUBO solvers and density functional theory (DFT) calculations. As a proof-of-concept work, we map the problem of screening phenolic inhibitors onto the QUBO model. We approximate the bond dissociation energy (BDE) of the -OH bond, an indicator of good polymeric inhibitors, into the QUBO model by modifying the group contribution method (GCM) with the aid of DFT calculations. We demonstrate a strong correlation between this QUBO model and the data from DFT, with the correlation coefficient and Spearman's coefficient of 0.82 and 0.86, respectively, when tested on the 85 given molecules. This mapping allows us to identify the candidates through the QUBO solver, whose BDEs are validated through DFT calculations, as well. Our work provides a promising direction for incorporating the GCM into QUBO solvers to tackle the molecule screening problems.