Physics of Self-assembly in Complex Matter



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This dissertation is based on my graduate research studying complex matter in multiple areas of biological physics. While the complex matter systems in each area differ vastly in scale and function, I use similar computational approaches on each to answer scientific queries about their structure and dynamics. In the first and second sections, I present how graph theory helps interpret actomyosin networks, which are complex biological active matter composed of filament, linker, and motor proteins. The results show how the network’s dynamics and structure are reshaped by motor and multivalent actin-binding proteins (“multilinkers”).

The third section presents my collaborative work with James Liman and Carlos Bueno on the effect of the actin-related protein (Arp2/3) complex on actomyosin dynamics. Generally, Arp2/3 forms a brancher between a mother and a daughter filament at an angle of 70^∘. I show that in percolating networks of actin monomers, Arp2/3 promotes avalanches (abrupt release of accumulated mechanical tension) in actomyosin.

In the fourth section, I use deep learning to identify substructures in the global three-dimensional (3D) folded structure of genomes inside the cell nucleus. Those 3D substructures were originally detected by the Aiden lab’s Hi-C technology in 2014 when they reported the existence of approximately 10,000 long-range interactions in the human genome called loops. My deep learning model detected the most noticeable loops and alluded to the existence of many more loop-like interactions, which are not easily visible to the naked eye.

In the fifth and final section of this dissertation, I present a collaborative work led by Dr. Fabio Zegarra on the effect of hydrodynamic interactions on the folding of proteins in water. Here, I describe how our computational model of hydrodynamic interactions between proteins and live intracellular media resolved an open question in the literature about whether (a) the effect of hydrodynamics interactions is negligible; (b) hydrodynamics interactions accelerate the folding process; or (c) hydrodynamic interactions decelerate the folding process. I show how all three conclusions are correct under certain circumstances, with an intimate dependence on the system’s temperature regime.



Networks, Biophysics, Complexity, Complex Matter


Portions of this document appear in: Eliaz, Yossi, Francois Nedelec, Greg Morrison, Herbert Levine, and Margaret S. Cheung. "Insights from graph theory on the morphologies of actomyosin networks with multilinkers." Physical Review E 102, no. 6 (2020): 062420. And in: Eliaz, Yossi, Mark Danovich, and Gregory P. Gasic. "Poolkeh Finds the Optimal Pooling Strategy for a Population-wide COVID-19 Testing (Israel, UK, and US as Test Cases)." MedRxiv (2020). And in: Liman, James, Carlos Bueno, Yossi Eliaz, Nicholas P. Schafer, M. Neal Waxham, Peter G. Wolynes, Herbert Levine, and Margaret S. Cheung. "The role of the Arp2/3 complex in shaping the dynamics and structures of branched actomyosin networks." Proceedings of the National Academy of Sciences 117, no. 20 (2020): 10825-10831. And in: Zegarra, Fabio C., Dirar Homouz, Yossi Eliaz, Andrei G. Gasic, and Margaret S. Cheung. "Impact of hydrodynamic interactions on protein folding rates depends on temperature." Physical Review E 97, no. 3 (2018): 032402.