Structural Analysis of Non-native Peptide-Based Catalysts Using 2D NMR-Guided MD Simulations

Proteins and enzymes generally achieve their functionsby creatingwell-defined 3D architectures that pre-organize reactive functionalities.Mimicking this approach to supramolecular pre-organization is leadingto the development of highly versatile artificial chemical environments,including new biomaterials, medicines, artificial enzymes, and enzyme-likecatalysts. The use of & beta;-turn and & alpha;-helical motifs is oneapproach that enables the precise placement of reactive functionalgroups to enable selective substrate activation and reactivity/selectivitythat approaches natural enzymes. Our recent work has demonstratedthat helical peptides can serve as scaffolds for pre-organizing tworeactive groups to achieve enzyme-like catalysis. In this study, weused CYANA and AmberTools to develop a computational approach fordetermining how the structure of our peptide catalysts can lead toenhancements in reactivity. These results support our hypothesis thatthe bifunctional nature of the peptide enables catalysis by pre-organizingthe two catalysts in reactive conformations that accelerate catalysisby proximity. We also present evidence that the low reactivity ofmonofunctional peptides can be attributed to interactions betweenthe peptide-bound catalyst and the helical backbone, which are notobserved in the bifunctional peptide.