Multiscale approaches environment

Besides the classical techniques for structural determination of proteins, namely X-ray diffraction or nuclear magnetic resonance, molecular modelling has become a complementary approach, providing refined structural details [4—7]. This view on the atomic scale paves the way to a comprehensive smdy of the correlations between protein structure and function, but a realistic description relies strongly on the performance of the theoretical tools. Nowadays, a full size protein is treated by force fields models [7-10], and smaller motifs, such as an active site of an enzyme, by multiscale approaches involving both quantum chemistry methods for local description, and molecular mechanics for its environment [11]. However, none of these methods are ab initio force fields require a parameterisation based on experimental data of model systems DPT quantum methods need to be assessed by comparison against high level ab initio calculations on small systems. 

In this review, we have shown how computational chemistry can be used to successfully predict the important effects the environment has on properties and processes of (supra)molecular systems. The overview of the theoretical methods and the computational tools available is necessarily not exhaustive. However, those selected exemplify the most reliable and accurate protocols available for a correct comparison with the experiments. All of them are based on a multiscale strategy, where the whole system is partitioned into distinct but interacting parts, described at different levels of accuracy. Here, in particular, we have mostly focused on those multiscale strategies which combine a quantum chemical description with classical models. These strategies have shown to be extremely effective both in terms of the ratio of computational cost to accuracy, and their extensibility to systems of increasing complexity. We believe that these hybrid QM/classical approaches will continue to play a dominant role, even if the incredibly fast developments in the QM methods on one side and in the computational tools on the other side are rapidly extending the dimension of the QM part of the systems towards a reahsm which has never been reached before. 

As another nonadiabatic QM/MM approach, Doltsinis et al. introduced a further layer in the MM part. This type of multiscale dynamics includes nonadiabatic QM parts, interacting MM part, and course-grained interaction with the environment. This approach intends to treat a drastic structure change in a macro scale originated from a microscopic phenomena associated with nonadiabaticity of electrons after shining a light [55]. 

Today, it is indispensable and conunon in modem chemistry to deal with molecules as the quantum systems that consist of a couple of classical mechanical (CM) nuclei and quantum mechanical (QM) electrons, for understanding chemical phenomena deeply. Such QM approaches can provide us the microscopic information such as the stmctural information (e.g. stable state (SS) and transition state (TS)) and chemical properties (e.g. electric or magnetic external fields and internal perturbations such as a nuclear or electron spin) of chemical reaction systems. However, from the point of view of computational efforts, it remains difficult to directly apply the QM approaches to large reaction systems such as the solution (or biological) ones that we are interested in. Thus, to treat these whole reaction systems in solution and biological environment, it is very useful in many cases to employ a multiscale model such as the quantum mechanical/molecular mechanical (QM/MM) methods, which are often combined with molecular dynamics (MD) or Monte Carlo (MC). 

Abstract Multiscale QM/MM approaches are nowadays a well-established computational tool to study properties and processes of supramolecular systems. In this chapter, an overview of the extension of these methods to photoinduced processes in biological systems will be presented and discussed. The attention will be focused on the strategies which can be used to properly describe the static and dynamic effects that the environment exerts on the electronic states involved in the processes. Specific problems related to the modeling of stationary properties and correlations, as well as reactive events will be analyzed and the computational tools developed so far within the QM/MM framework to solve them will be described. 

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