The worldwide acknowledged success of multiscale methods [1-7], accompanied by the continuously evolving high performance computing (HPC) architectures [8,9], has boosted the demand for dedicated training courses. A strong point supporting the above statement is the fact that these approaches have become appealing both in academy and industry. Recent extensions, going beyond the original purpose that motivated hybrid quantum mechanics / molecular mechanics (QM/MM) approaches is the rising of the use of QM/MM in combination with quantum treatment of the nuclei (path integral MD, PIMD), construction of still non-existing data bases (DBs) for machine learning (ML) approaches and search algorithms to reduce the phase space of the QM/MM simulations [10-13]. Some of these issues have already been pioneered by us in the last edition of this School, but explicit requests from the participants evidenced the need for a deepening of some of these hot topics.
    The inclusion of different levels of accuracy in QM/MM algorithms to account for realistically large systems remains a delicate point requiring a specific and detailed presentation to young students and researchers approaching this field and for which regular university courses are still insufficient or non-existing, thus calling for continuous formation and updating oriented to students facing for the first time this field or in search for a specifically oriented course. On a technical standpoint, advances in methods and their implementation in algorithms suited to continuously evolving HPC architectures toward peta- and exascale-level represent simultaneously an unprecedented powerful tool and a continuous challenge [14,15]. Worldwide HPC facilities, such as in the PRACE initiative and its succeedor EuroHPC, have played a prominent role also in social and human activities, for example during the recent pandemic CoViD'19 crisis or global environmental problems [16], underscoring the impact of this type of computational approaches in the general context of human activities.
    The importance of QM/MM approaches, with particular emphasis in chemistry and biochemistry, was acknowledged in 2013 with the Nobel Prize in Chemistry awarded jointly to M. Karplus, M. Levitt and A. Warshel. From a historical standpoint, the first attempt to join quantum and classical molecular mechanics marked in 1976 [17] the official birth of the QM/MM approach. This seminal work paved the route to the QM/MM that we know nowadays and it has motivated new challenges (now almost paradigms) for exploiting modern HPC platforms, leading to a breakthrough in the simulations of realistic bio-systems [18-20].
    Another important milestone has been the coupling of QM/MM dynamical simulations to free energy sampling methods for the exploration of reaction mechanisms [21,22]. This has boosted the activities in the field of computational biochemistry [23-26], making de facto experiments in silico (term coined in 1989 by the Mexican mathematician Pedro Miramontes) the natural counterpart of the traditional in vivo and in vitro ones.
    The wide variety of QM/MM approaches coded in different computer codes, nowadays available on demand and/or freely downloadable from open repositories, make their choice in their approach and implementation, and often using them poses a major challenge not easy to sort out, especially for newcomers. Hence, guidance from experienced practitioners and developers is of paramount importance to next-generation researchers who are going to continue and take over the work of present generation researchers. A major risk of the availability of this type of codes open-source and/or freely downloadable is the blind use of these tools as “black boxes”, often appearing in a transparent way also in published work or in presentations at international conferences, a fact that also the proposers of this School have witnessed.
    The scope of our School, which follows previous editions held since 2011 until 2022 with a two- to three-year periodicity, is to offer a general and up-to-date insight into well assessed and forefront QM/MM approaches. Since its original edition, we have taken particular care to keep this CECAM School dynamical and timely evolving, including new developments and arising challenges that this specific field experienced over the years. Being both developers and experienced practitioners, we intend to provide, accounting for the feedback of former participants, an updated overview of methods, algorithms, and forefront challenges on biomolecular systems. According to our former experience, the lectures, exercises and the constant interaction with the participants allows us to provide them a precise know-how on how to set up a QM/MM simulation starting from pristine crystallographic data and going across all the required steps to complete the system, including the addition of missing hydrogen atoms and solvent molecules. The lectures in the previous editions have always been animated by questions and specific requests from the participants, accompanied with additional lectures and files provided by us via the CECAM web server.

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