Background: Innovations in computer hardware and software capabilities have paved the way for advances in molecular modelling techniques and methods, leading to an unprecedented expansion of their potential applications. In contrast to the docking technique, which usually identifies the most stable selector-selectand (SO-SA) complex for each enantiomer, the molecular dynamics (MD) technique enables the consideration of a distribution of the SO-SA complexes based on their energy profile. This approach provides a more truthful representation of the processes occurring within the column. However, benchmark procedures and focused guidelines for computational treatment of enantioselectivity at the molecular level are still missing.
Results: Twenty-eight molecular dynamics simulations were performed to study the enantiorecognition mechanisms of seven N-3,5-dinitrobenzoylated α- and β-amino acids (DNB-AAs), occurring with the two quinine- and quinidine-based (QN-AX and QD-AX) chiral stationary phases (CSPs), under polar-ionic conditions. The MD protocol was optimized in terms of box size, simulation run time, and frame recording frequency. Subsequently, all the trajectories were analyzed by calculating both the type and amount of the interactions engaged by the selectands (SAs) with the two chiral selectors (SOs), as well as the conformational and interaction energy profiles of the formed SA-SO associates. All the MDs were in strict agreement with the experimental enantiomeric elution order and allowed to establish (i) that salt-bridge and H-bond interactions play a pivotal role in the enantiorecognition mechanisms, and (ii) that the π-cation and π-π interactions are the discriminant chemical features between the two SOs in ruling the chiral recognition mechanism.
Significance: The results of this work clearly demonstrate the high contribution given by MD simulations in the comprehension of the enantiorecognition mechanism with Cinchona alkaloid-based CSPs. However, from this research endeavor it clearly emerged that the MD protocol optimization is crucial for the quality of the produced results.
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http://dx.doi.org/10.1016/j.aca.2024.342791 | DOI Listing |
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