Understanding the Structure and Formation of Protein Crystals Using Computer Simulation and Theory

Charbonneau, Patrick

Altan, Irem

2020-02-10T17:28:06Z

2020-07-10T08:17:10Z

2019

Chemistry

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.

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.

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.

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.

https://hdl.handle.net/10161/20129

Computational chemistry

Biophysics

Statistical physics

biomolecular solvation

coarse-grained models

protein crystallization

Self-assembly

Understanding the Structure and Formation of Protein Crystals Using Computer Simulation and Theory

Dissertation

4.931506849315069