Molecular modeling is increasingly being integrated into the drug discovery process. Although computational methods are already an essential part of the process today, these techniques have vast potential to evolve and refine drug design in the future. The integration of modeling is further catalyzed by the rapidly growing computational power available to both academia and pharmaceutical companies. These resources extend the reach of the computational methods to new time scales in physics-based simulations of biomolecular systems and increase the number of molecules that is possible to dock to a receptor by several orders of magnitude. However, there is also a need for further development of methods that utilize the increased computational power to increase the level of detail in modeling of molecular interactions. The work presented in this thesis has contributed to method development in two different areas and demonstrated how virtual screening can be applied to identify ligands of proteins. The first main project investigated modeling of ordered water molecules in protein binding sites to understand the role of water in molecular recognition and the impact of ligands on hydration networks. In a second project, an approach for discovery and optimization of fragment-sized ligands based on virtual screening was developed and used to identify inhibitors of a cancer drug target. Finally, molecular docking was applied to assess proposed substrates of cytochrome b₅₆₁, a recently crystallized membrane protein.

This thesis is divided into three parts; the first part describes a method for efficient screening of membrane proteins for crystallography. By utilising the properties of a folding reporter GFP it is possible to quickly and accurately screen the stability of a protein in a range of conditions without full purification. This allows rapid assessment of the suitability of a protein for crystallography and a parallel optimisation of purification conditions for subsequent large-scale protein production.

The second part describes the discovery of a membrane bound superoxide oxidase (SOO), a novel scavenger of membrane proximal superoxide. SOO is a kinetically perfect enzyme, reacting at rates close to the diffusion limit in a similar fashion to other superoxide scavengers, such as superoxide dismutase. We propose that SOO rescues electrons “lost” to superoxide and recycles them back into the respiratory chain, releasing oxygen. At the same time SOO contributes to the proton motive force by uptake of protons from the cytoplasmic side of the membrane.

The third part concerns the fatty acyl-CoA synthetase FadD13 from Mycobacterium tuberculosis (M. tuberculosis). It represents a critical node point in M. tuberculosis lipid metabolism and has been suggested to be a vital component of M. tuberculosis survival in host cell macrophages. FadD13 harbours a hydrophobic cavity that is unable to house the very-long-chain substrates the enzyme has preference for. We propose that FadD13 is a peripheral membrane protein, utilising the membrane to house the very-long-chain fatty acid substrates during the activation reaction.