  Molecular biology and biochemistry interpret microscopic processes in the
living world in terms of molecular structures and their interactions, which are
quantum mechanical by their very nature. Whereas the theoretical foundations of
these interactions are very well established, the computational solution of the
relevant quantum mechanical equations is very hard. However, much of molecular
function in biology can be understood in terms of classical mechanics, where
the interactions of electrons and nuclei have been mapped onto effective
classical surrogate potentials that model the interaction of atoms or even
larger entities. The simple mathematical structure of these potentials offers
huge computational advantages; however, this comes at the cost that all quantum
correlations and the rigorous many-particle nature of the interactions are
omitted. In this work, we discuss how quantum computation may advance the
practical usefulness of the quantum foundations of molecular biology by
offering computational advantages for simulations of biomolecules. We not only
discuss typical quantum mechanical problems of the electronic structure of
biomolecules in this context, but also consider the dominating classical
problems (such as protein folding and drug design) as well as data-driven
approaches of bioinformatics and the degree to which they might become amenable
to quantum simulation and quantum computation.
