The underlying electronic structure of atoms and molecules shapes and defines the fundamental physical, chemical, and biological processes occurring in Nature. Computational methods can help to understand such processes if approximations reach an acceptable compromise between computational efficiency and accuracy. A full quantum-mechanical (QM) treatment of large biomolecular systems, such as chromophores embedded in proteins or lipid bilayers, becomes unmanageable due to the steep scaling with respect to system size. In addition, these systems undergo dynamic processes of crucial importance where the inclusion of temperature is paramount. The use of hybrid quantum mechanics/molecular mechanics (QM/MM) is often an excellent cost-effective alternative to full-QM approaches. These models assume that a small central part of the system can be treated quantum mechanically while its environment, the remainder, is treated classically using molecular mechanics (MM) force fields.