Enumerative Discovery of Noncanonical Polypeptide Secondary Structures

Area of Science:

• Polymer Chemistry
• Biomolecular Engineering
• Computational Chemistry

Background:

• Flexible polymers can adopt ordered conformations due to favorable local interactions, like the alpha helix in proteins stabilized by hydrogen bonds.
• The growing diversity of unnatural amino acids and backbones presents opportunities for novel polymer structures beyond natural proteins.
• A systematic approach is needed to identify polymers with unique low-energy repeating structures for molecular engineering.

Purpose of the Study:

• To develop and apply a systematic computational approach for identifying novel, low-energy repeating structures in polymers.
• To explore dipeptide combinations of diverse amino acids for predictable conformational preferences.
• To provide new building blocks for advanced molecular engineering.

Main Methods:

• Systematic computational screening of dipeptide combinations from 130 chemically diverse amino acids.
• Prediction of unique low-energy conformational states for polymer sequences.
• Experimental characterization of identified structures using circular dichroism spectroscopy.
• Validation of computational models with NMR and X-ray crystallography for selected polymers.

Main Results:

• Identified ten new dipeptide repeating structures with unique low-energy states.
• Experimental data (CD spectra) correlated well with computational predictions.
• Structural analysis (NMR, X-ray crystallography) confirmed the accuracy of computational models for two polymers.
• Demonstrated the generalizability of the approach for diverse polymer systems.

Conclusions:

• A systematic computational strategy effectively identifies novel, ordered polymer structures.
• The discovered dipeptide repeat polymers represent valuable new building blocks for molecular engineering.
• This methodology can be extended to discover low-energy repeating structures across a broad range of polymers.