Predictive computational modeling of biological processes is one of the most signifi-
cant and important present day challenges faced by the computational chemistry and
biology community. The complexity of these problems demands the use of methods
that are able to accurately model intra and intermolecular forces, adequately sample
relevant configurational space, and establish realistic solvated environments. At one
end of the spectrum, catalytic processes may require a high-level quantum chemical
description, whereas at the other end of the spectrum large-scale conformational rear￾rangements or molecular recognition events may require very long simulation times
or specialized methods for configurational sampling. These computational modeling
challenges are amplified when such processes are coupled. In order to address these
problems, so-called “multiscale” simulation models are required. Here, “multi-scale”
implies the integration of a hierarchy of methods that span a broad range of spatial
and temporal domains and work in concert to provide insight into complex problems.
This book aims to provide a collection of state-of- the-art multiscale quantum simu￾lation techniques recently developed and applied to tackle fundamental biocatalysis
problems.