Molecular investigation of polypyrrole and surface recognition by affinity peptides
Successful tissue engineering strategies in the nervous system must be carefully crafted to interact favorably with the complex biochemical signals of the native environment. To date, all chronic implants incorporating electrical conductivity degrade in performance over time as the foreign body reaction and subsequent fibrous encapsulation isolate them from the host tissue. Our goal is to develop a peptide-based interfacial biomaterial that will non-covalently coat the surface of the conducting polymer polypyrrole, allowing the implant to interact with the nervous system through both electrical and chemical cues. Starting with a candidate peptide sequence discovered through phage display, we used computational simulations of the peptide on polypyrrole to describe the bound peptide structure, explore the mechanism of binding, and suggest new, better binding peptide sequences. After experimentally characterizing the polymer, we created a molecular mechanics model of polypyrrole using quantum mechanics calculations and compared its in silico properties to experimental observables such as density and chain packing. Using replica exchange molecular dynamics, we then modeled the behavior of affinity binding peptides on the surface of polypyrrole in explicit water and saline environments. Relative measurements of the contributions of each amino acid were made using distance measurements and computational alanine scanning.