Design of protein biomaterials through tailored shape and packing strategies of patchy particles
Abstract
The ability to control the assembly of materials is paramount to the design and production of smart materials with novel properties. Unfortunately, programmed assembly has proven difficult: nucleic acids can be programmed to assemble, but in general do not form structures extensive enough to be useful for many applications. Conversely, polymers that can form extensive structures, such as plastics, have interactions that are relatively non-directed and are not sufficiently information rich to program. We have therefore begun to explore whether proteins that can be produced in bulk can be generally programmed to self-assemble into higher order structures based on relatively non-directed electrostatic interactions, effectively encompassing the information rich nature of nucleic acids and the relatively non-directed and extensive assembly capabilities of plastics and other materials. Our initial efforts to program supercharged protein assembly have proven extremely successful, and under this grant we hope to both generalize these results to other proteins, and to show the utility of supercharged protein assembly for a variety of relevant applications, from printing structures to functionalizing assemblies with silicon and metals. Our aims are to (i) expand our knowledge of the hierarchical assembly process with fluorescent proteins as substrates, (ii) apply this knowledge to new protein scaffolds, and ultimately (iii) use the engineered protein assemblies in 3D and ink jet printing and for the construction of functional silicate and metallated biomaterials. The experimental work carried out by the Ellington lab (UT Austin) will be closely mirrored by molecular simulation studies carried out by the Glotzer group (U. Michigan), which will provide guidance on experimental design and result in a generalized strategy for adapting any protein to becoming a building block for charge-based assembly. A purely computational goal of this grant is to elucidate pathways to protein crystal formation. Building on the nucleation pathways previously studied, we will, in the time ahead, focus on crystal shape prediction from patchy shape models. The goal will be to predict the three-dimensional habit (such as needle-like, bipyramidal etc.) of the crystal using large-scale simulations of 10,000s of proteins simultaneously using our patchy shape model. Elucidating both protein crystallization pathways and crystal shape is of high relevance for drug discovery and manufacturing.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 02, 2019
- Source ID
- W911NF1810167
Entities
People
- Sharon Glotzer
Organizations
- Army Contracting Command
- United States Army
- University of Michigan