Cytosolic expression, solution structures, and molecular dynamics simulation of genetically encodable disulfide‐rich de novo designed peptides

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 13C‐ and 15N‐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.

[1]  D. Baker,et al.  Global analysis of protein folding using massively parallel design, synthesis, and testing , 2017, Science.

[2]  P E Wright,et al.  Defining solution conformations of small linear peptides. , 1991, Annual review of biophysics and biophysical chemistry.

[3]  H. Kolmar Natural and engineered cystine knot miniproteins for diagnostic and therapeutic applications. , 2011, Current pharmaceutical design.

[4]  D. G. Gibson,et al.  Enzymatic assembly of DNA molecules up to several hundred kilobases , 2009, Nature Methods.

[5]  D. Craik,et al.  Structure and folding of disulfide‐rich miniproteins: Insights from molecular dynamics simulations and MM‐PBSA free energy calculations , 2008, Proteins.

[6]  N. C. Price,et al.  How to study proteins by circular dichroism. , 2005, Biochimica et biophysica acta.

[7]  G. Parisi,et al.  Simulated tempering: a new Monte Carlo scheme , 1992, hep-lat/9205018.

[8]  Gaetano T Montelione,et al.  Evaluating protein structures determined by structural genomics consortia , 2006, Proteins.

[9]  G. Ciccotti,et al.  Numerical Integration of the Cartesian Equations of Motion of a System with Constraints: Molecular Dynamics of n-Alkanes , 1977 .

[10]  R. Vincentelli,et al.  High throughput screening identifies disulfide isomerase DsbC as a very efficient partner for recombinant expression of small disulfide-rich proteins in E. coli , 2013, Microbial Cell Factories.

[11]  Fred Heffron,et al.  A multi-pronged search for a common structural motif in the secretion signal of Salmonella enterica serovar Typhimurium type III effector proteins. , 2010, Molecular bioSystems.

[12]  David E. Golan,et al.  Protein therapeutics: a summary and pharmacological classification , 2008, Nature Reviews Drug Discovery.

[13]  László Szilágyi,et al.  Chemical shifts in proteins come of age , 1995 .

[14]  C. Zhang,et al.  Enhanced sampling and applications in protein folding in explicit solvent. , 2010, The Journal of chemical physics.

[15]  David A. Snyder,et al.  Identification of Zinc-ligated Cysteine Residues Based on 13Cα and 13Cβ Chemical Shift Data , 2006 .

[16]  Damon H. May,et al.  Screening, large-scale production, and structure-based classification for cystine-dense peptides , 2018, Nature Structural & Molecular Biology.

[17]  M J Harvey,et al.  ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale. , 2009, Journal of chemical theory and computation.

[18]  Xiao-Xia Xia,et al.  Proteome‐based identification of fusion partner for high‐level extracellular production of recombinant proteins in Escherichia coli , 2008, Biotechnology and bioengineering.

[19]  F. Studier,et al.  Protein production by auto-induction in high density shaking cultures. , 2005, Protein expression and purification.

[20]  R. Woody,et al.  Circular dichroism. , 1995, Methods in enzymology.

[21]  K Wüthrich,et al.  The program XEASY for computer-supported NMR spectral analysis of biological macromolecules , 1995, Journal of biomolecular NMR.

[22]  P. Myler,et al.  Backbone and side chain 1H, 13C, and 15N NMR assignments for the organic hydroperoxide resistance protein (Ohr) from Burkholderia pseudomallei , 2009, Biomolecular NMR assignments.

[23]  Torsten Herrmann,et al.  Protein NMR structure determination with automated NOE assignment using the new software CANDID and the torsion angle dynamics algorithm DYANA. , 2002, Journal of molecular biology.

[24]  R J Read,et al.  Crystallography & NMR system: A new software suite for macromolecular structure determination. , 1998, Acta crystallographica. Section D, Biological crystallography.

[25]  Stefano Piana,et al.  Demonstrating an Order-of-Magnitude Sampling Enhancement in Molecular Dynamics Simulations of Complex Protein Systems. , 2016, Journal of chemical theory and computation.

[26]  K. Rajarathnam,et al.  13C NMR chemical shifts can predict disulfide bond formation , 2000, Journal of biomolecular NMR.

[27]  Robert Powers,et al.  Protein NMR recall, precision, and F-measure scores (RPF scores): structure quality assessment measures based on information retrieval statistics. , 2005, Journal of the American Chemical Society.

[28]  Lu Zhang,et al.  Massively parallel de novo protein design for targeted therapeutics , 2017, Nature.

[29]  Jianpeng Ma,et al.  CHARMM: The biomolecular simulation program , 2009, J. Comput. Chem..

[30]  A. Bax,et al.  Protein backbone angle restraints from searching a database for chemical shift and sequence homology , 1999, Journal of biomolecular NMR.

[31]  David Baker,et al.  Accurate de novo design of hyperstable constrained peptides , 2016, Nature.

[32]  Jens Meiler,et al.  ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules. , 2011, Methods in enzymology.

[33]  D. Waugh An overview of enzymatic reagents for the removal of affinity tags , 2011, Protein Expression and Purification.

[34]  Kurt Wüthrich,et al.  Processing of multi-dimensional NMR data with the new software PROSA , 1992 .

[35]  M. Nilges,et al.  Refinement of protein structures in explicit solvent , 2003, Proteins.

[36]  K. Wüthrich NMR of proteins and nucleic acids , 1988 .

[37]  R. Woody,et al.  [4] Circular dichroism , 1995 .

[38]  D. Wishart,et al.  An NMR approach to structural proteomics , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[39]  K. Wüthrich,et al.  Torsion angle dynamics for NMR structure calculation with the new program DYANA. , 1997, Journal of molecular biology.

[40]  A. Lyubartsev,et al.  New approach to Monte Carlo calculation of the free energy: Method of expanded ensembles , 1992 .