Abstract
An effective yet reliable computational workflow is proposed, which permits the computation of accurate geometrical structures for large flexible molecules at an affordable cost thanks to the integration of machine learning tools and DFT models together with reduced scaling computations of vibrational averaging effects. After validation of the different components of the overall strategy, a panel of molecules of biological interest have been analyzed. The results confirm that very accurate geometrical parameters can be obtained at reasonable cost for molecules including up to about 50 atoms, which are the largest ones for which comparison with high-resolution rotational spectra is possible. Since the whole computational workflow can be followed employing standard electronic structure codes, accurate results for large-sized molecules can be obtained at DFT cost also by nonspecialists.
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