Computational methods relying on first principles are fundamental for dissecting
basic physicochemical properties of biological systems and unveiling mechanistic details
that are often silent to experiments. The tireless improvement of theoretical schemes for
molecular modelling and simulations, coupled to the increasing computational power of
novel architectures and integrated with available experimental inputs, allows today
exploring the functioning of biological systems with unprecedented accuracy. Indeed,
molecular simulations at both the quantum mechanics and molecular mechanics levels are
nowadays able to dissect with high confidence the structural and dynamical features of
large systems in native-like conditions, up to the point that their mode of action can be
modulated in a controlled fashion. These computational chemistry strategies are
particularly appealing when applied to pharmaceutically relevant targets. In this chapter, we
will present recent successes of computational investigations applied to a broad variety of
biochemical systems that are promising or validated targets for drug discovery. In
particular, we will show how molecular modelling at the quantum mechanics level is key
for revealing the mechanistic details of catalysis in bacterial and viral metallo-enzymes. We
will continue by discussing how accurate molecular mechanics-based free energy
calculations can provide a new quantitative description of the function of systems of
relevance for multidrug resistance in bacteria. In the final part of the chapter, we will show
examples where computational and medicinal chemistry is fully integrated with structural
and biochemical data to study function and inhibition of target enzymes implicated in
cancer and other inflammatory-related diseases. The final goal of these studies is to develop
new molecular entities potentially endowed with a desired pharmacological activity. This
chapter will therefore define the contribution of emerging approaches and recent advances
in the field of computational chemistry for translating the atomic-level understanding of
complex biological phenomena into useful information to progress in molecular medicine.
Keywords: Hybrid QM/MM, molecular dynamics, molecular modelling, multiscale
modelling, protein ligand interactions, structure-based drug design.
