Abstract

In this work, I aimed to accurately simulate the Raman optical activity (ROA) signatures of flexible solute molecules in their environment. Indeed, these systems are quite challenging due to the potentially huge number of conformers—that is, local minima on the potential energy surface (PES). Furthermore, the environment can drastically alter the PES, as evidenced by experimental ROA spectra that vary significantly depending on the molecule’s conformation and its surroundings. To address this issue, we have developed a hierarchy of methodologies designated M1, M2, and M3. In M1 and M2, the so-called static approach is used: one or more conformers are identified, their geometries are reoptimized at the Density Functional Theory (DFT) level, and their vibrational signatures are simulated, typically using the harmonic approximation. The initial list of conformers was obtained using the CREST algorithm. In M1, the solvent is treated implicitly, whereas in M2, explicit solvent molecules are added around the solute molecule. In M3, we perform ab initio molecular dynamics simulations of the solute molecule surrounded by explicit solvent molecules. The spectrum is obtained by evaluating time-correlation functions along the trajectory. Our first systems of interest were cryptophane derivatives. These are flexible cage-like systems consisting of two hemispheres connected by three -O-(CH₂)n-O- (denoted Cr–nnn) linkers that exhibit chiroptical properties. For Cr–111, the smallest possible cryptophane, the M1 methodology showed good agreement with experimental data, especially in the fingerprint region. However, we demonstrated that the relative ratio between the different conformers was strongly influenced by the choice of the exchange-correlation (XC) functional in our DFT calculations, highlighting the sensitivity of the potential energy surface (PES) description. Cr–222 molecules have been shown to be more flexible, as evidenced by a greater number of significant conformers. The overall agreement with experimental data was also satisfactory. Finally, to test our different approaches (M1–M3), I performed new ROA measurements of amino acids in water at the University of Bordeaux in Dr. Daugey’s laboratory. When compared to our simulations, we clearly observed an improvement in the ROA signatures when explicit water molecules were added to our simulations (M2 vs. M1). Unfortunately, the M3 method did not perform as expected, and further investigation is needed. Overall, I have shown that the PES, as described by our various methodologies, is highly sensitive to various simulation parameters—such as the XC functional, the number and position of explicit solvent molecules, and so on—and that all of these factors strongly influence the simulated ROA signatures.

Jury

  • Prof. Francesca CECCHET (UNamur), Chair
  • Prof. Vincent LIÉGEOIS (UNamur), Secretary
  • Prof. Benoît CHAMPAGNE (UNamur)
  • Prof. Carine CLAVAGUÉRA (University of Paris-Saclay)
  • Dr. Nicolas DAUGEY (University of Bordeaux)