A Multiscale Model for the Self-Assembly of Coat Proteins in Bacteriophage MS2

Dissecting the general mechanisms of protein cage self-assembly by coarse-grained simulations

The development of artificial protein cages has recently gained massive attention due to their promising application prospect as novel delivery vehicles for therapeutics. These nanoparticles are formed through a process called self-assembly, in which individual subunits spontaneously arrange into highly ordered patterns via non-covalent but specific interactions. Therefore, the first step toward the design of novel engineered protein cages is to understand the general mechanisms of their self-assembling dynamics. Here we have developed a new computational method to tackle this problem. Our method is based on a coarse-grained model and a diffusion-reaction simulation algorithm. Using a tetrahedral cage as test model, we showed that self-assembly of protein cage requires of a seeding process in which specific configurations of kinetic intermediate states are identified. We further found that there is a critical concentration to trigger self-assembly of protein cages. This critical concentration allows that cages can only be successfully assembled under a persistently high concentration. Additionally, phase diagram of self-assembly has been constructed by systematically testing the model across a wide range of binding parameters. Finally, our simulations demonstrated the importance of protein's structural flexibility in regulating the dynamics of cage assembly. In summary, this study throws lights on the general principles underlying self-assembly of large cage-like protein complexes and thus provides insights to design new nanomaterials.

Stability and conformational memory of electrosprayed and rehydrated bacteriophage MS2 virus coat proteins

Proteins are innately dynamic, which is important for their functions, but which also poses significant challenges when studying their structures. Gas-phase techniques can utilise separation and a range of sample manipulations to transcend some of the limitations of conventional techniques for structural biology in crystalline or solution phase, and isolate different states for separate interrogation. However, the transfer from solution to the gas phase risks affecting the structures, and it is unclear to what extent different conformations remain distinct in the gas phase, and if resolution in silico can recover the native conformations and their differences. Here, we use extensive molecular dynamics simulations to study the two distinct conformations of dimeric capsid protein of the MS2 bacteriophage. The protein undergoes notable restructuring of its peripheral parts in the gas phase, but subsequent simulation in solvent largely recovers the native structure. Our results suggest that despite some structural loss due to the experimental conditions, gas-phase structural biology techniques provide meaningful data that inform not only about the structures but also conformational dynamics of proteins.

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Presented extensive molecular dynamics (MD) simulation data investigating protein vacuum exposure and rehydration dynamics.

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Demonstrated that the majority of the protein structure recovers their initial solution conformation after vacuum exposure.

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Explored the potential gain for structural biology of using MD simulation to refine gas-phase determined protein structures.

Understanding the impacts of cellular environments on ligand binding of membrane receptors by computational simulations

Binding of cell surface receptors with their extracellular ligands initiates various intracellular signaling pathways. However, our understanding of the cellular functions of these receptors is very limited due to the fact that in vivo binding between ligands and receptors has only been successfully measured in a very small number of cases. In living cells, receptors are anchored on surfaces of the plasma membrane, which undergoes thermal undulations. Moreover, it has been observed in various systems that receptors can be organized into oligomers prior to ligand binding. It is not well understood how these cellular factors play roles in regulating the dynamics of ligand-receptor interactions. Here, we tackled these problems by using a coarse-grained kinetic Monte Carlo simulation method. Using this method, we demonstrated that the membrane undulations cause a negative effect on ligand-receptor interactions. We further found that the preassembly of membrane receptors on the cell surface can not only accelerate the kinetics of ligand binding but also reduce the noises during the process. In general, our study highlights the importance of membrane environments in regulating the function of membrane receptors in cells. The simulation method can be potentially applied to specific receptor systems involved in cell signaling.

Multiscale modelling and simulation of viruses

In recent years, advances in structural biology, integrative modelling, and simulation approaches have allowed us to gain unprecedented insights into viral structure and dynamics. In this article we survey recent studies utilizing this wealth of structural information to build computational models of partial or complete viruses and to elucidate mechanisms of viral function. Additionally, the close interplay of viral pathogens with host factors - such as cellular and intracellular membranes, receptors, antibodies, and other host proteins - makes accurate models of viral interactions and dynamics essential. As viruses continue to pose severe challenges in prevention and treatment, enhancing our mechanistic understanding of viral infection is vital to enable the development of novel therapeutic strategies.