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

Proteins and enzymes generally achieve their functions by creating well-defined 3D architectures that pre-organize reactive functionalities. Mimicking this approach to supramolecular pre-organization is leading to the development of highly versatile artificial chemical environments, including new biomaterials, medicines, artificial enzymes, and enzyme-like catalysts. The use of ß-turn and α-helical motifs is one approach that enables the precise placement of reactive functional groups to enable selective substrate activation and reactivity/selectivity that approaches natural enzymes. Our recent work has demonstrated that helical peptides can serve as scaffolds for pre-organizing two reactive groups to achieve enzyme-like catalysis. In this study, we used CYANA and AmberTools to develop a computational approach for determining how the structure of our peptide catalysts can lead to enhancements in reactivity. These results support our hypothesis that the bifunctional nature of the peptide enables catalysis by pre-organizing the two catalysts in reactive conformations that accelerate catalysis by proximity. We also present evidence that the low reactivity of monofunctional peptides can be attributed to interactions between the peptide-bound catalyst and the helical backbone, which are not observed in the bifunctional peptide.

Optimizing the Local Chemical Environment on a Bifunctional Helical Peptide Scaffold Enables Enhanced Enantioselectivity and Cooperative Catalysis.

We describe a proof-of-concept study in which peptide-bound enamine and thiourea catalysts are used to facilitate the conjugate addition of cyclohexanone to nitroolefins. Our bifunctional peptide scaffold is modified to optimize the local environment around both catalysts to enhance both reactivity and enantioselectivity, affording selectivities of ≤95% ee. Circular dichroism, nuclear magnetic resonance nuclear Overhauser effect studies, and molecular dynamics simulations verify the helical structure of our catalyst in solution and the importance of the secondary structure in catalysis.

CAN: A new program to streamline preparation of molecular coordinate files for molecular dynamics simulations.

Preparing molecular coordinate files for molecular dynamics (MD) simulations can be a very time-consuming process. Herein we present the development of a user-friendly program that drastically reduces the time required to prepare these molecular coordinate files for MD software packages such as AmberTools. Our program, known as charge atomtype naming (CAN), creates and uses a library of structures such as amino acid monomers to update the charge, atom type, and name of atoms in any molecular structure (mol2) file. We demonstrate the utility of this new program by rapidly preparing structural files for MD simulations for polypeptides ranging from small molecules to large protein structures. Both native and non-native amino acid residues are easily handled by this new program.