The Computational Prediction of Raman and ROA Spectra of Charged Histidine Tautomers in Aqueous Solution

Histidine is a key component of a number of enzymatic mechanisms, and undertakes a myriad of functionalities in biochemical systems. Its computational modelling can be problematic, as its capacity to take on a number of distinct formal charge states, and tautomers thereof, is difficult to capture by conventional techniques. We demonstrate a means for recovering the experimental Raman optical activity (ROA) spectra of histidine to a high degree of accuracy. The resultant concordance between experiment and theory is of particular importance in characterising physically insightful quantities, such as band assignments. We introduce a novel conformer selection scheme that unambiguously parses snapshots from a molecular dynamics trajectory into a smaller conformational ensemble, suitable for reproducing experimental spectra. We show that the “dissimilarity” of the conformers within the resultant ensemble is maximised and representative of the physically relevant regions of molecular conformational space. In addition, we present a conformer optimisation strategy that significantly reduces the computational costs associated with alternative optimisation strategies. This conformer optimisation strategy yields spectra of equivalent quality to those of the aforementioned alternative optimisation strategies. Finally, we demonstrate that microsolvated models of small molecules yield spectra that are comparable in quality to those obtained from ab initio calculations involving a large number of solvent molecules.