This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.Biological macromolecules including proteins and RNA generally adopt unique, folded conformations that are responsible for their remarkable properties, including binding, catalysis, signal transduction, and cell penetration. Until recently, the process of folding was considered a mystery, but as the fields of protein folding, RNA structure and folding, and molecular organization have advanced it has become increasingly clear that it should be possible to design non-biological molecules that fold into unique structures. Recently, chemists have begun to design oligomers of non-standard amino acids with altered backbone structure, to explore the types of secondary structures they can form. However, there have been no general methods for sequence-specific design of their structures. Thus, the application of traditional computational protein design (CPD) techniques to non-alpha amino acid scaffolds, such as Beta amino acids, has been largely unexplored. Several labs have successfully designed alpha amino acid proteins using computational techniques, including new enzymes, signaling molecules, small molecule detectors, and drugs. However, the applications of the fundamental principles used to accomplish these successes have largely been confined to natural proteins. The ability to design foldamers of non-alpha scaffolds would enable the exploration of a myriad of new structural possibilities. Given the additional flexibility of foldamers, it might be possible to design novel folds using CPD, similar in concept to the work done by Kuhlman et al in 2003 . These novel designed folds could improve our ability to modulate biologic pathways in meaningful ways. Beta amino acids present an intriguing new design scaffold where these same design concepts and techniques can be applied to yield novel and medically relevant protein like compounds. This new scaffold allows for greater design diversity due to the extra backbone carbon atom in each residue between the alpha and carboxyl positions that can be used for R-group substitution. Moreover, the additional carbon also confers natural protease resistance. These properties contribute to the therapeutic importance of beta amino acids as future design scaffolds. Our lab has CPD techniques have been applied to a variety of beta amino acid scaffolds to yield stable oligomer designs. These scaffold designs were then further stabilized by in-silico mutagenesis. A simplistic energy equation has been used to-date to achieve these results, consisting of van der Waals and electrostatic interactions. In addition, the use of existing side-chain rotamer libraries have yielded reasonable biochemical and structural results. The further refinement and development of these parameters should increase our ability to replicate the successes of alpha amino acid based CPD. This preliminary beta amino acid CPD work is currently being vetted using traditional protein synthesis and characterization techniques. This approach can be generalized to other foldamer scaffolds as well. Delta and Gamma peptides for example provide additional degrees of backbone conformational freedom whereby novel structural elements could be constructed. In addition, traditional small-molecule scaffolds such as terphenyl could prove to be interesting starting points for this new CPD design approach. These scaffolds combined with traditional CPD concepts could enhance the diversity of future therapeutics. If the scientific communities understanding of structural biology is accurate, then applying existing modeling techniques to these new foldamers should yield interesting results. There should be some addition insights gained by performing these simulations as we test the limits and accuracy of know biophysical parameters.
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