Programmable Self-Assembled Nanostructures
Researchers demonstrate a strategy for tailoring dendritic polymers
Biological nanostructures that grow and change shape may have an important role to play in drug-delivery systems, sensors, and other future applications. But designing nanostructures for specific settings will require control over the self-assembly process.
A research team including PNNL postdoctoral scientist Peiyuan Gao, a computational mathematician, has developed a highly tunable version of self-assembled structures by adjusting external stimuli to manipulate the shape and size of a polymer cluster called a micelle, a structure formed in nature. They describe the work in their paper "Dynamic and programmable morphology and size evolution via a living hierarchical self-assembly strategy," which was published in Nature Communications in July 2018. Gao is a co-author with four researchers from the Chinese Academy of Sciences.
Why it matters: Relying on biologically spontaneous self-assembly processes can be an efficient strategy for creating a myriad of well-organized nanostructures that are engineered from the bottom up. But designing nanostructures tailored to deliver specific drugs, for example, requires an ability to control their shape, structure, and size as they grow in order to maximize their functionality. This study provides new insights that could aid the fabrication of these intelligent drug carriers.
Summary: Previous studies have explored self-assembly of soft surfactant molecules into nanostructures. In this first-of-its-kind study, the researchers worked with a hard-soft copolymer: POSS-(SS-PEG)8, a star-shaped molecule containing a disulfide-linked core/shell structure with one polyhedral oligomeric silsesquioxane (POSS) core and eight polyethylene glycol (PEG) chains that can be disconnected from the core. The hard POSS-embedded backbone lends this amphiphilic hybrid dendrimer a different mechanism of assembly. The nanostructure's evolution can then be manipulated in situ by tuning pH stimuli to activate and/or terminate the thiol-disulfide exchange reaction. The self-assemby process can be interrupted at any time by neutralization or restarted by rebasification.
The researchers used a combination of computational studies and experimental methods to demonstrate this mechanism. Gao carried out the computational work at PNNL, using the multiscale simulation software LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator). The team started by building atomic models of the POSS dendrimers. To investigate the packing style, they computed the size of the dendrimer molecules in the assembly process with an atomic model. Then the atomic POSS dendrimer models were mapped to the coarse-grained level. A dissipative particle dynamics (DPD) simulation technique was used to study the assembly mechanism and final assembled structure.
What's next? The researchers want to investigate the effect of topology on assembly with various POSS dendrimer molecules.
Acknowledgments: This work is part of the Collaboratory on Mathematics for Mesoscopic Modelling of Materials (CM4), which focuses on the development of new numerical simulation methods and new applications for computer-aided materials design. In this study, the assembly mechanism was demonstrated and validated by numerical simulation (atomic molecular dynamics and dissipative particle dynamics simulation). The simulation results are also helpful in designing new types of surfactant molecules.
Sponsor: This work was supported by was supported by NSFC (Nos. 21504096, 21725403, 21674120, and 21474115), the Ministry of Science and Technology of China (No. 2014CB932200), and the "Young Thousand Talents Program." Peiyuan Gao was supported by the U.S. Department of Energy (DOE), Office of Science, and Office of Advanced Scientific Computing Research, as part of the Collaboratory on Mathematics for Mesoscopic Modelling of Materials (CM4).
Reference: Wang X, Gao P, Yang Y, Guo H, Wu D. "Dynamic and programmable morphology and size evolution via a living hierarchical self-assembly strategy." Nature Communications (2018). DOI: 10.1038/s41467-018-05142-3