An Artificial Intelligence Approach for Tackling Conformational Energy Uncertainties in Chiroptical Spectroscopies

This project aims to develop a novel approach for determining the absolute configuration of chiral molecules, crucial for various chirality-related fields. Leveraging the interaction with polarised light, the method combines a genetic algorithm to identify relevant conformers while considering uncertainties in DFT relative energies, and a hierarchical clustering algorithm to analyze spectra trends and identify when predictions are unreliable. The effectiveness of this approach is demonstrated through challenging cases involving papuamine and haliclonadiamine, two bis-indane natural products with significant conformational heterogeneity.

Authors: Gabriel Marton, Mark A. J. Koenis, Hong-Bing Liu, Carole A. Bewley, Wybren Jan Buma, Dr. Valentin Paul Nicu

Paper: https://onlinelibrary.wiley.com/doi/10.1002/anie.202307053