Biomolecular phase separation plays an important role in the formation and regulation of various biomolecular condensates in cells. Recently, the stickers-and-spacers framework, which is based on associative polymer theory, has been developed to explain the phase behaviors of biomolecules, and the f...
Biomolecular phase separation plays an important role in the formation and regulation of various biomolecular condensates in cells. Recently, the stickers-and-spacers framework, which is based on associative polymer theory, has been developed to explain the phase behaviors of biomolecules, and the framework was successfully implemented in a graph-based simulation module. The module uses the concept of percolation, which allows us to describe condensation in the language of graph theory, where percolation is depicted by the emergence of a giant component. In this thesis, we propose a 4-stage relaxation process towards reaching percolation. At each stage, we analyze the system's energy, percolation extent, and bonding information. Additionally, we introduce a new approach that starts from a metastable state to reduce computational costs, obtaining a relaxation curve. Furthermore, we present two hypotheses regarding the impact of adjusting entropy loss during the formation of inter-chain bonding on percolation propensity. According to our results, reducing the entropy penalty when bonding occurs within a cluster enhances the propensity for phase separation. In the second part of the paper, we apply the previously discussed graph-theoretic simulation to the fluorescent protein EYFP trimer, introducing a novel system. Initially, we investigate the percolation threshold by obtaining a phase diagram through graph-based simulation. Subsequently, we analyze fluorescent images of EYFP3 WT and A206K experimentally, exploring how the difference in binding affinity influences percolation. Our research correlates computational and experimental findings, confirming that increasing binding affinity enhances percolation propensity.
Biomolecular phase separation plays an important role in the formation and regulation of various biomolecular condensates in cells. Recently, the stickers-and-spacers framework, which is based on associative polymer theory, has been developed to explain the phase behaviors of biomolecules, and the framework was successfully implemented in a graph-based simulation module. The module uses the concept of percolation, which allows us to describe condensation in the language of graph theory, where percolation is depicted by the emergence of a giant component. In this thesis, we propose a 4-stage relaxation process towards reaching percolation. At each stage, we analyze the system's energy, percolation extent, and bonding information. Additionally, we introduce a new approach that starts from a metastable state to reduce computational costs, obtaining a relaxation curve. Furthermore, we present two hypotheses regarding the impact of adjusting entropy loss during the formation of inter-chain bonding on percolation propensity. According to our results, reducing the entropy penalty when bonding occurs within a cluster enhances the propensity for phase separation. In the second part of the paper, we apply the previously discussed graph-theoretic simulation to the fluorescent protein EYFP trimer, introducing a novel system. Initially, we investigate the percolation threshold by obtaining a phase diagram through graph-based simulation. Subsequently, we analyze fluorescent images of EYFP3 WT and A206K experimentally, exploring how the difference in binding affinity influences percolation. Our research correlates computational and experimental findings, confirming that increasing binding affinity enhances percolation propensity.
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