Cytosolic expression, solution structures, and molecular dynamics simulation of genetically encodable disulfide-rich de novo designed peptides.Buchko, G.W., Pulavarti, S.V.S.R.K., Ovchinnikov, V., Shaw, E.A., Rettie, S.A., Myler, P.J., Karplus, M., Szyperski, T., Baker, D., Bahl, C.D.
(2018) Protein Sci 27: 1611-1623
- PubMed: 30152054
- DOI: 10.1002/pro.3453
- Primary Citation of Related Structures:
- PubMed Abstract:
Disulfide-rich peptides represent an important protein family with broad pharmacological potential. Recent advances in computational methods have made it possible to design new peptides which adopt a stable conformation de novo. Here, we describe a s ...
Disulfide-rich peptides represent an important protein family with broad pharmacological potential. Recent advances in computational methods have made it possible to design new peptides which adopt a stable conformation de novo. Here, we describe a system to produce disulfide-rich de novo peptides using Escherichia coli as the expression host. The advantage of this system is that it enables production of uniformly 13 C- and 15 N-labeled peptides for solution nuclear magnetic resonance (NMR) studies. This expression system was used to isotopically label two previously reported de novo designed peptides, and to determine their solution structures using NMR. The ensemble of NMR structures calculated for both peptides agreed well with the design models, further confirming the accuracy of the design protocol. Collection of NMR data on the peptides under reducing conditions revealed a dependency on disulfide bonds to maintain stability. Furthermore, we performed long-time molecular dynamics (MD) simulations with tempering to assess the stability of two families of de novo designed peptides. Initial designs which exhibited a stable structure during simulations were more likely to adopt a stable structure in vitro, but attempts to utilize this method to redesign unstable peptides to fold into a stable state were unsuccessful. Further work is therefore needed to assess the utility of MD simulation techniques for de novo protein design.
Institute for Protein Innovation, Boston, Massachusetts, 02115.