Abstract
Simulations in biological environments such as proteins, DNA or lipids entail model systems that include a large number of atoms. Moreover, dynamic simulations, in which thermal effects are considered, sometimes require hundreds of thousands of calculations in order to reproduce a physicochemical process in a biological environment. Therefore, classical simulations based on widely parametrized force fields are employed instead of more accurate quantum methods, whose high computational requirements preclude their application. Disappointingly, although classical simulations could provide a proper sampling of the nuclear configurational space along a given process, they do not yield reliable microscopic information on the weight of different non-covalent interactions; namely, electrostatic, Pauli repulsion, induction (and charge transfer) and dispersion, in the total energy. This is mainly due to compensation of errors between different terms of the force field associated with the parametrization process, focused on getting good macroscopic properties instead of an accurate description of the interatomic interactions. As an alternative to classical and quantum methods, hybrid quantum mechanics/molecular mechanics schemes (QM/MM), where the target region is treated with a quantum method and the rest is represented by a classical force field, can be applied for large biological systems. These schemes combine the accuracy of quantum approaches and the small computational requirements of classical ones. In addition, a thorough analysis of intermolecular interactions can be carried out by means of an energy decomposition analysis (EDA), whose implementation within the framework of QM/MM schemes is known as QM/MM-EDA. In this paper, a methodology developed in our group to investigate intermolecular interactions, combining CMD simulations and a QM/MM energy decomposition analysis (QM/MM-EDA), and its implementation are presented. Finally, some applications to the study of ion solvation and membrane permeation processes are discussed.
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Mandado, M., Ramos-Berdullas, N. (2024). EDA-NCI: A Scientific Software to Investigate Non-covalent Interactions Combining Classical Dynamic Simulations and QM/MM Calculations. In: Gervasi, O., Murgante, B., Garau, C., Taniar, D., C. Rocha, A.M.A., Faginas Lago, M.N. (eds) Computational Science and Its Applications – ICCSA 2024 Workshops. ICCSA 2024. Lecture Notes in Computer Science, vol 14823. Springer, Cham. https://doi.org/10.1007/978-3-031-65329-2_25
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