Two-dimensional (2D) nanomaterials (nanosheets) have potential advantages for the construction of devices of technological importance, such as chemical sensors, diagnostics, selectively permeable membranes, and catalytic and electronic scaffolds. However, the limited methods to control growth and rationally modify the resultant structures of these materials represents a significant impediment to progress in this field. Peptides and proteins are attractive candidates for the construction of these types of 2D materials since the control of sequence potentially permits the control of structure and function across length scales. One complicating factor is that proteins commonly display complex folding pathways, which can often result in limited control over the structure of the final material. An approach is proposed in which structural information from the Protein Data Bank (PDB), a vast library of freely available high-resolution protein structures, will be employed as the starting point to create novel classes of protein-based 2D materials. Layered protein structures will be identified in the PDB, in which close contacts are observed within the layer and long contacts are observed between layers. Computational and rational design methods will be used to strengthen interaction within a layer and further weaken or abrogate interactions between layers. Using this approach, one need not explicitly design the structure from first principles, but can instead create nanosheets from proteins that have a demonstrated propensity to form 2D layers. Several classes of materials targets will be investigated that would be useful from the perspective of potential applications in devices, including selectively permeable membranes and polar 2D crystals. These initial studies will validate the computational design approach and provide generally applicable methods to access novel classes of structurally defined 2D materials. Students involved in this project will gain valuable experience in cross-cutting research that enables a vertical consolidation of skill sets, including computational design, synthesis, and advanced methods of high-resolution structural characterization, that will be implemented for the design and fabrication of functional 2D nanomaterials. In addition, material related to the proposed research will be presented as content to illustrate concepts and learning objectives in a newly developed introductory undergraduate lecture course and laboratory experience on macromolecular chemistry at Emory University.
A heuristic approach is proposed to the design of structurally ordered 2D peptide nanomaterials that leverages the natural diversity of crystal structures in the Protein Data Bank (PDB). The PDB represents a rich trove of structural information on biomolecules. Many structures comprise layers of biomolecules, i.e., arrangements in which contact areas are more extensive within at least one crystallographically defined plane than between planes. In principle, the lateral interfaces within appropriately chosen crystal structures can be computationally optimized to enhance the cohesive interactions between protomers, while axial interactions are attentuated through weakening or blocking of the lamination of layers. This investigation comprises a proof-of-principle directed toward the hypothesis that crystallographically characterized layered structures can be used as a starting point to engineer and structurally diversify crystalline 2D peptide and protein assemblies through computational optimization of protomer interfaces. The research plan of this proposal encompasses three specific aims in support of the preceding hypothesis. The first two aims focus on the validation of this computationally-driven approach with respect to the design of two specific classes of 2D peptide materials targets that represent potential substrates for high value-added applications, namely open framework (porous) lattices and polar 2D crystals. We anticipate that success in these two aims will experimentally validate the feasibility and scope of this approach with respect to materials design, while simultaneously providing access to novel 2D nanomaterials. In the third specific aim, structural data resulting from the materials generated in specific aims 1 and 2 will be employed as input for additional rounds of computational design in order to create multi-component 2D nanostructures in which the tectons are chemically distinguishable and independently addressable on the nanoscale. In each specific aim, computational methods will be employed initially to optimize the structurally critical interfaces between protomers. Candidate peptides will be synthesized and screened using higher throughput, low-resolution experimental methods. Suitable structures will be subjected to high-resolution structural analysis, primarily using cryo-EM 2D reconstruction with direct electron detection and, when applicable, single-crystal diffraction analysis.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
