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<p>The complexity of protein-protein interactions enables proteins to self-assemble
into a rich array of structures, such as virus capsids, amyloid fibers, amorphous
aggregates, and protein crystals. While some of these assemblies form under biological
conditions, protein crystals, which are crucial for obtaining protein structures from
diffraction methods, do not typically form readily. Crystallizing proteins thus requires
significant trial and error, limiting the number of structures that can be obtained
and studied. Understanding how proteins interact with one another and with their environment
would allow us to elucidate the physicochemical processes that lead to crystal formation
and provide insight into other self-assembly phenomena. This thesis explores this
problem from a soft matter theory and simulation perspective. </p><p>We first attempt
to reconstruct the water structure inside a protein crystal using all-atom molecular
dynamics simulations with the dual goal of benchmarking empirical water models and
increasing the information extracted from X-ray diffraction data. We find that although
water models recapitulate the radial distribution of water around protein atoms, they
fall short of reproducing its orientational distribution. Nevertheless, high-intensity
peaks in water density are sufficiently well captured to detect the protonation states
of certain solvent-exposed residues.</p><p>We next study a human gamma D-crystallin
mutant, the crystals of which have inverted solubility. We parameterize a patchy particle
and show that the temperature-dependence of the patch that contains the solubility
inverting mutation reproduces the experimental phase diagram. We also consider the
hypothesis that the solubility is inverted because of increased surface hydrophobicity,
and show that even though this scenario is thermodynamically plausible, microscopic
evidence for it is lacking, partly because our understanding of water as a biomolecular
solvent is limited.</p><p>Finally, we develop computational methods to understand
the self-assembly of a two-dimensional protein crystal and show that specialized Monte
Carlo moves are necessary for proper sampling.</p>
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