My Ph.D work is focused on investigating the dynamics for the hydrophobic aggregation of the Aggregation Induced Emission (AIE) molecules and their interactions with proteins. To model the dynamics of aggregation, we have developed a new algorithm: Automatic state Partitioning for Multi-body systems (APM), for constructing Markov State Models (MSM) from a large number of Molecular Dynamics (MD) simulations to dissect the details of aggregation processes. The APM algorithm effectively models the impact of inter-molecular interactions on conformational dynamics, and the drastic differences in the timescales for dynamics of individual molecules before and after aggregation. This is achieved by directly incorporating kinetics into geometric clustering when identifying the metastable...[ Read more ]

My Ph.D work is focused on investigating the dynamics for the hydrophobic aggregation of the Aggregation Induced Emission (AIE) molecules and their interactions with proteins. To model the dynamics of aggregation, we have developed a new algorithm: Automatic state Partitioning for Multi-body systems (APM), for constructing Markov State Models (MSM) from a large number of Molecular Dynamics (MD) simulations to dissect the details of aggregation processes. The APM algorithm effectively models the impact of inter-molecular interactions on conformational dynamics, and the drastic differences in the timescales for dynamics of individual molecules before and after aggregation. This is achieved by directly incorporating kinetics into geometric clustering when identifying the metastable conformation states. We show that APM greatly enhances the computational efficiency as well as the accuracy for the MSM construction of multi-body systems. Another difficulty associated with the study of aggregation processes is the existence of numerous parallel pathways with comparable probabilities. To address this issue, we have developed a novel path lumping algorithm that is able to compare the similarities of different pathways (according to the pair-wise inter-crossing flux) and further lump them into metastable path channels. Using the APM and path lumping algorithm, we have successfully identified two families of pathways that dominate the dynamics of the hydrophobic collapse of a pair of AIE molecules (9D9F). Further analysis of representative pathways from these families indicates that water molecules mainly serve as the lubricant to facilitate the hydrophobic collapse. In addition, we have modeled the binding of AIE molecules to protein insulin to explain their retardation effect in the insulin fibrillation. Finally, we have modeled the fiber structure assembled by another type of AIE molecules that can strongly emit circularly polarized luminescence.