LETTER pubs.acs.org/JPCL Virtual Screening for Dipeptide Aggregation: Toward Predictive Tools for Peptide Self-Assembly

Self-assembling peptide materials are currently widely studiedfor potential applications in biomedicine and nanotechnology.1 They can form various nanostructures from 1D fibers2 and tubes35 to sheets6 and 3D networks with tunable supramole-cular functionalities such as electronic conductivity7 and bioactivity.8 These features, combined with their benign toxicology and ease of preparation, position peptide-based nanostructures at the forefront of next-generation, soft nanomaterials design. The high degree of flexibility in the types of nanostructures that can be produced is due to the vast chemical space that is available when considering the 20 gene-encoded amino acids and various functional groups that can be combined to create self-assembling peptide based units. As such, a method to rapidly screen these various combinations in the computer before investing time and resources in the laboratory is highly beneficial to the future development of novel materials