Molecular Driving Forces of Peptide-Based Biomaterials
Abstract
Bottom-up biomimetic materials design is a promising strategy for enhancing the attainable properties of synthetic materials. Naturally occurring protein-based materials outperform current synthetic materials in properties such as strength-to-weight ratio and combined hardness and flexibility Self-assembly of short amino acid sequences, or peptides, is an appealing approach to synthesize materials that exhibit the naturally occurring properties of the protein-based systems. A fundamental understanding of the molecular driving forces that dictate self-assembly and the other macroscopic properties of interest is necessary to choose the appropriate peptide sequence. The multiscale nature of peptide self-assembly, however, make it a challenge to investigate the driving forces of this process using standard experimental and computational techniques. We propose an ambitious multiscale study of dipeptide self-assembly in which we develop and employ a novel multiscale computational framework and utilize cutting-edge two-dimensional infrared spectroscopy to verify these models. The proposed multiscale modeling framework is build on a bottom-up coarse-graining formalism but adapted to peptide self-assembly by employing physically motivated interactions that will allow for informed molecular engineering of new materials. This is achieved by systematically coarse-graining degrees of freedom of the system motivated, in part, by the time- and length-scales of different components of the self-assembly mechanism. The degrees of freedom of the bulk solvent, for example, become less important as the peptides aggregate and order suggesting that these degrees of freedom can be integrated out. The insight and accuracy of the multiscale computational framework will be tested using 2D IR spectroscopy for the same set of dipeptides. In particular, the shift in the Amide-I and Amide-II peaks and the inhomogeneous broadening of the Amide-I peak will be monitored to elucidate the structure and solvent mediated interactions of the aggregation and ordering processes. Qualitative agreement between experiment and simulation will be sought between the estimated timescale and mechanism of assembly; while quantitative agreement will be measured b) directly computing the 2D IR spectra from the simulation. The outcomes of this work will be: 1) a fundamental understanding of peptide self-assembly from the nano to the mesoscale, 2) a proof of concept regarding transferable coarse-grained potentials. and 3) a set of experimentally and computationally verified rules governing the assembly of peptide-based biomaterials.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 07, 2018
- Source ID
- W911NF1710383
Entities
People
- Martin McCullagh
Organizations
- Army Contracting Command
- Colorado State University
- United States Army