Impact of conformation and intramolecular interactions on vibrational circular dichroism spectra identified with machine learning.

ABSTRACT: Vibrational Circular Dichroism (VCD) spectra often differ strongly from one conformer to another, even within the same absolute configuration of a molecule. Simulated molecular VCD spectra typically require expensive quantum chemical calculations for all conformers to generate a Boltzmann averaged total spectrum. This paper reports whether machine learning (ML) can partly replace these quantum chemical calculations by capturing the intricate connection between a conformer geometry and its VCD spectrum. Three hypotheses concerning the added value of ML are tested. First, it is shown that for a single stereoisomer, ML can predict the VCD spectrum of a conformer from solely the conformer geometry. Second, it is found that the ML approach results in important time savings. Third, the ML model

SUBMITTER: Vermeyen T 

PROVIDER: S-EPMC10338531 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature