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This paper deals with the development and first validation of a composite approach for the simulation of chiroptical spectra in solution aimed to strongly reduce the number of full QM computations without any significant accuracy loss. The approach starts from the quantum mechanical computation of reference spectra including vibrational averaging effects and taking average solvent effects into account by means of the polarizable continuum model. Next, the snapshots of classical molecular dynamics computations are clusterized and one reference configuration from each cluster is used to compute a reference spectrum. Local fluctuation effects within each cluster are then taken into account by means of the perturbed matrix model. The performance of the proposed approach is tested on the challenging case of the optical and chiroptical spectra of camphorquinone in methanol solution. Although further validations are surely needed, the results of this first study are quite promising also taking into account that agreement with experimental data is reached by just a couple of full quantum mechanical geometry optimizations and frequency computations.

The Perturbed Matrix Method (PMM) approach to be used in combination with Molecular Dynamics (MD) trajectories (MD-PMM) has been recoded from scratch, improved in several aspects, and implemented in the Gaussian suite of programs for allowing a user-friendly and yet flexible tool to estimate quantum chemistry observables in complex systems in condensed phases. Particular attention has been devoted to a description of rigid and flexible quantum centers together with powerful essential dynamics and clustering approaches. The default implementation is fully black-box and does not require any external action concerning both MD and PMM sections. At the same time, fine-tuning of different parameters and use of external data are allowed in all the steps of the procedure. Two specific systems (Tyrosine and Uridine) have been reinvestigated with the new version of the code in order to validate the implementation, check the performances, and illustrate some new features.