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Molecular modeling studies of peptoid polymers

Department of Chemical and Biomolecular Engineering, NC State University, Campus Box 7905, Raleigh, NC 27695-7905, United States

Topical Section: Theory, simulations and modeling of materials

Peptoids, or poly-N-substituted glycines, are synthetic polymers composed of a protein backbone with side chains attached to the nitrogen atoms rather than the α-carbons. Peptoids are biomimetic and protease resistant and have been explored for a variety of applications including pharmaceuticals and coatings. They are also foldamer-type materials that can adopt diverse structures based on the sequences of their side chains. Design of new peptoid sequences may lead to the creation of many interesting materials. Given the large number of possible peptoid side chains, computer models predicting peptoid structure-side chain relationships are desirable. In this paper, we provide a survey of computational efforts to understand and predict peptoid structures. We describe simulations at several levels of theory, along with their assumptions and results. We also discuss some challenges for future peptoid computational research.
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Keywords peptoids; foldamer; molecular simulation; biomimetic

Citation: Laura J. Weiser, Erik E. Santiso. Molecular modeling studies of peptoid polymers. AIMS Materials Science, 2017, 4(5): 1029-1051. doi: 10.3934/matersci.2017.5.1029


  • 1. Sun J, Zuckermann RN (2013) Peptoid Polymers: A Highly Designable Bioinspired Material. ACS Nano 7: 4715–4732.    
  • 2. Seo J, Lee BC, Zuckermann RN (2011) Peptoids: Synthesis, Characterization, and Nanostructures. Compr Biomater 2: 53–76.
  • 3. Chongsiriwatana NP, Patch JA, Czyzewski AM, et al. (2008) Peptoids that mimic the structure, function, and mechanism of helical antimicrobial peptides. Proc Natl Acad Sci USA 105: 2794–2799.    
  • 4. Vollrath SBL, Fürniss D, Schepers U, et al. (2013) Amphiphilic peptoid transporters-synthesis and evaluation. Org Biomol Chem 11: 8197–8201.    
  • 5. Li N, Zhu F, Gao F, et al. (2010) Blockade of CD28 by a synthetical peptoid inhibits T-cell proliferation and attenuates graft-versus-host disease. Cell Mol Immunol 7: 133–142.    
  • 6. Dohm MT, Kapoor R, Barron AE (2011) Peptoids: Bio-Inspired Polymers as Potential Pharmaceuticals. Curr Pharm Design 17: 2732–2747.    
  • 7. Statz AR, Park JP, Chongsiriwatana NP, et al. (2008) Surface-immobilised antimicrobial peptoids. Biofouling 24: 439–448.    
  • 8. Seurynck SL, Patch JA, Barron AE (2005) Simple, helical peptoid analogs of lung surfactant protein B. Chem Biol 12: 77–88.    
  • 9. Maayan G, Ward MD, Kirshenbaum K (2009) Folded biomimetic oligomers for enantioselective catalysis. Proc Natl Acad Sci USA 106: 13679–13684.    
  • 10. Gellman SH (1998) Foldamers:  A Manifesto. Accounts Chem Res 31: 173–180.
  • 11. Armand P, Kirshenbaum K, Falicov A, et al. (1997) Chiral N-substituted glycines can form stable helical conformations. Fold Design 2: 369–375.    
  • 12. Shah NH, Butterfoss GL, Nguyen K (2008) Oligo(N-aryl glycines): A New Twist on Structured Peptoids. J Am Chem Soc 130: 16622–16632.    
  • 13. Huang K, Wu CW, Sanborn TJ, et al. (2006) A threaded loop conformation adopted by a family of peptoid nonamers. J Am Chem Soc 128: 1733–1738.    
  • 14. Crapster JA, Guzei IA, Blackwell HE (2013) A Peptoid Ribbon Secondary Structure. Angew Chem Int Ed 52: 5079–5084.    
  • 15. Mannige RV, Haxton TK, Proulx C, et al. (2015) Peptoid nanosheets exhibit a new secondary-structure motif. Nature 526: 415–420.    
  • 16. Hebert ML, Shah DS, Blake P, et al. (2013) Tunable peptoid microspheres: effects of side chain chemistry and sequence. Org Biomol Chem 11: 4459–4464.    
  • 17. Murnen HK, Rosales AM, Jaworski JN, et al. (2010) Hierarchical Self-Assembly of a Biomimetic Diblock Copolypeptoid into Homochiral Superhelices. J Am Chem Soc 132: 16112–16119.    
  • 18. Sanii B, Kudirka R, Cho A, et al. (2011) Shaken, Not Stirred: Collapsing a Peptoid Monolayer To Produce Free-Floating, Stable Nanosheets. J Am Chem Soc 133: 20808–20815.    
  • 19. Dill KA, MacCallum JL (2012) The Protein-Folding Problem, 50 Years On. Science 338: 1042–1046.    
  • 20. Gorske BC, Blackwell HE (2006) Tuning peptoid secondary structure with pentafluoroaromatic functionality: A new design paradigm for the construction of discretely folded peptoid structures. J Am Chem Soc 128: 14378–14387.    
  • 21. Stringer JR, Crapster JA, Guzei IA, et al. (2010) Construction of Peptoids with All Trans-Amide Backbones and Peptoid Reverse Turns via the Tactical Incorporation of N-Aryl Side Chains Capable of Hydrogen Bonding. J Org Chem 75: 6068–6078.    
  • 22. Gorske BC, Nelson RC, Bowden ZS, et al. (2013) "Bridged" n→π* Interactions Can Stabilize Peptoid Helices. J Org Chem 78: 11172–11183.    
  • 23. Wu CW, Kirshenbaum K, Sanborn TJ, et al. (2003) Structural and spectroscopic studies of peptoid oligomers with alpha-chiral aliphatic side chains. J Am Chem Soc 125: 13525–13530.    
  • 24. Kirshenbaum K, Barron AE, Goldsmith RA, et al. (1998) Sequence-specific polypeptoids: A diverse family of heteropolymers with stable secondary structure. Proc Natl Acad Sci USA 95: 4303–4308.    
  • 25. Armand P, Kirshenbaum K, Goldsmith RA, et al. (1998) NMR determination of the major solution conformation of a peptoid pentamer with chiral side chains. Proc Natl Acad Sci USA 95: 4309–4314.    
  • 26. Dill KA (1990) Dominant forces in protein folding. Biochemistry 29: 31.
  • 27. Dill KA, Ozkan SB, Shell MS, et al. (2008) The protein folding problem. Annu Rev Biophys 37: 289–316.    
  • 28. Sali A, Blundell TL (1993) Comparative protein modeling by satisfaction of spatial restraints. J Mol Biol 234: 779–815.    
  • 29. Shen MY, Sali A (2006) Statistical potential for assessment and prediction of protein structures. Protein Sci 15: 2507–2524.    
  • 30. Rohl CA, Strauss CEM, Misura KMS, et al. (2004) Protein structure prediction using Rosetta. Method Enzymol 383: 66–93.    
  • 31. Leach AR (2001) Molecular modelling : principles and applications, England: Pearson/Prentice Hall.
  • 32. Shell MS (2016) Coarse-Graining with the Relative Entropy, In: Rice SA, Dinner AR, Advances in Chemical Physics, Malden: Wiley-Blackwell, 395–441.
  • 33. Mackerell AD, Feig M, Brooks CL (2004) Extending the treatment of backbone energetics in protein force fields: Limitations of gas-phase quantum mechanics in reproducing protein conformational distributions in molecular dynamics simulations. J Comput Chem 25: 1400–1415.    
  • 34. Feigel M (1983) Rotation barriers of amides in the gas phase. J Phys Chem 87: 3054–3058.    
  • 35. Sui Q, Borchardt D, Rabenstein DL (2007) Kinetics and equilibria of cis/trans isomerization of backbone amide bonds in peptoids. J Am Chem Soc 129: 12042–12048.    
  • 36. Duffy EM, Severance DL, Jorgensen WL (1992) Solvent effects on the barrier to isomerization for a tertiary amide from ab initio and Monte Carlo calculations. J Am Chem Soc 114: 7535–7542.    
  • 37. Torrie GM, Valleau JP (1977) Nonphysical sampling distributions in Monte Carlo free-energy estimation: Umbrella sampling. J Comput Phys 23: 187–199.    
  • 38. Sugita Y, Okamoto Y (1999) Replica-exchange molecular dynamics method for protein folding. Chem Phys Lett 314: 141–151.    
  • 39. Stringer JR, Crapster JA, Guzei IA, et al. (2011) Extraordinarily Robust Polyproline Type I Peptoid Helices Generated via the Incorporation of alpha-Chiral Aromatic N-1-Naphthylethyl Side Chains. J Am Chem Soc 133: 15559–15567.    
  • 40. Ramachandran GN, Ramakrishnan C, Sasisekharan V (1963) Stereochemistry of polypeptide chain configurations. J Mol Biol 7: 95–99.    
  • 41. Butterfoss GL, Renfrew PD, Kuhlman B, et al. (2009) A Preliminary Survey of the Peptoid Folding Landscape. J Am Chem Soc 131: 16798–16807.    
  • 42. Mohle K, Hofmann HJ (1996) Peptides and peptoids—A systematic structure comparison. J Mol Model 2: 307–311.    
  • 43. Miertuš S, Scrocco E, Tomasi J (1981) Electrostatic interaction of a solute with a continuum. A direct utilizaion of AB initio molecular potentials for the prevision of solvent effects. Chem Phys 55: 117–129.
  • 44. Pascual-Ahuir JL, Silla E, Tomasi J, et al. (1987) Electrostatic interaction of a solute with a continuum. Improved description of the cavity and of the surface cavity bound charge distribution. J Comput Chem 8: 778–787.
  • 45. Parker BF, Knight AS, Vukovic S, et al. (2016) A Peptoid-Based Combinatorial and Computational Approach to Developing Ligands for Uranyl Sequestration from Seawater. Ind Eng Chem Res 55: 4187–4194.    
  • 46. Cancès E, Mennucci B, Tomasi J (1997) A new integral equation formalism for the polarizable continuum model: Theoretical background and applications to isotropic and anisotropic dielectrics. J Chem Phys 107: 3032–3041.    
  • 47. Cornell W, Cieplek P, Bayly CI, et al. (1995) A Second Generation Force-Field for the Simulation of Proteins, Nucleic-Acids, and Organic-Molecules. J Am Chem Soc 117: 5179–5197.    
  • 48. Hawkins GD, Cramer CJ, Truhlar DG (1998) Universal Quantum Mechanical Model for Solvation Free Energies Based on Gas-Phase Geometries. J Phys Chem B 102: 3257–3271.    
  • 49. Bradley EK, Kerr JM, Richter LS, et al. (1997) NMR Structural Characterization of Oligo-N-Substituted Glycine Lead Compounds from a Combinatorial Library. Mol Divers 3: 1–15.    
  • 50. Mann G, Yun RH, Nyland L, et al. (2002) The Sigma MD Program and a Generic Interface Applicable to Multi-Functional Programs with Complex, Hierarchical Command Structure, In: Schlick T, Gan HH, Computational Methods for Macromolecules: Challenges and Applications, Springer, Berlin, Heidelberg, 129–145.
  • 51. Hermans J, Berendsen HJC, Van Gunsteren WF, et al. (1984) A consistent empirical potential for water–protein interactions. Biopolymers 23: 1513–1518.    
  • 52. Butterfoss GL, Yoo B, Jaworski JN (2012) De novo structure prediction and experimental characterization of folded peptoid oligomers. Proc Natl Acad Sci USA 109: 14320–14325.    
  • 53. Wang JM, Wolf RM, Caldwell JW, et al. (2004) Development and testing of a general amber force field. J Comput Chem 25: 1157–1174.    
  • 54. Onufriev A, Bashford D, Case DA (2004) Exploring protein native states and large-scale conformational changes with a modified generalized born model. Proteins 55: 383–394.    
  • 55. MacKerell AD, Bashford D, Bellott M, et al. (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins. J Phys Chem B 102: 3586–3616.    
  • 56. Case DA, Cheatham TE, Darden T, et al. (2005) The Amber biomolecular simulation programs. J Comput Chem 26: 1668–1688.    
  • 57. Jorgensen WL, Maxwell DS, TiradoRives J (1996) Development and testing of the OPLS all-atom force field on conformational energetics and properties of organic liquids. J Am Chem Soc 118: 11225–11236.    
  • 58. Moehle K, Hofmann HJ (1996) Peptides and peptoids—A quantum chemical structure comparison. Biopolymers 38: 781–790.    
  • 59. Jorgensen W, Chandrasekhar J, Madura J, et al. (1983) Comparison of Simple Potential Functions for Simulating Liquid Water. J Chem Phys 79: 926–935.    
  • 60. Tobias DJ, Brooks CL (1988) Molecular dynamics with internal coordinate constraints. J Chem Phys 89: 5115–5127.    
  • 61. Wang J, Wang W, Kollman PA, et al. (2006) Automatic atom type and bond type perception in molecular mechanical calculations. J Mol Graph Model 25: 247–260.    
  • 62. Jakalian A, Jack DB, Bayly CI (2002) Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation. J Comput Chem 23: 1623–1641.
  • 63. Mukherjee S, Zhou G, Michel C, et al. (2015) Insights into Peptoid Helix Folding Cooperativity from an Improved Backbone Potential. J Phys Chem B 119: 15407–15417.    
  • 64. Lifson S, Roig A (1961) On the Theory of Helix-Coil Transition in Polypeptides. J Chem Phys 34: 1963–1974.    
  • 65. Mirijanian DT, Mannige RV, Zuckermann RN, et al. (2014) Development and use of an atomistic CHARMM-based forcefield for peptoid simulation. J Comput Chem 35: 360–370.    
  • 66. Jordan PA, Bishwajit P, Butterfoss GL, et al. (2011) Oligo(N-alkoxy glycines): trans substantiating peptoid conformations. J Pept Sci 96: 617–626.    
  • 67. Nam KT, Shelby SA, Cho PH, et al. (2010) Free-floating ultrathin two-dimensional crystals from sequence-specific peptoid polymers. Nat Mater 9: 454–460.    
  • 68. Mannige RV, Kundu J, Whitelam S (2016) The Ramachandran Number: An Order Parameter for Protein Geometry. PLoS One 11: e0160023.    
  • 69. Reith D, Putz M, Muller-Plathe F (2003) Deriving effective mesoscale potentials from atomistic simulations. J Comput Chem 24: 1624–1636.    
  • 70. Izvekov S, Voth GA (2005) Multiscale coarse graining of liquid-state systems. J Chem Phys 123: 134105.    
  • 71. Shell MS (2008) The relative entropy is fundamental to multiscale and inverse thermodynamic problems. J Chem Phys 129: 144108.    
  • 72. Haxton TK, Mannige RV, Zuckermann RN, et al. (2015) Modeling Sequence-Specific Polymers Using Anisotropic Coarse-Grained Sites Allows Quantitative Comparison with Experiment. J Chem Theory Comput 11: 303–315.    
  • 73. Sanii B, Haxton TK, Olivier GK, et al. (2014) Structure-Determining Step in the Hierarchical Assembly of Peptoid Nanosheets. ACS Nano 8: 11674–11684.    
  • 74. Haxton TK, Zuckermann RN, Whitelam S (2016) Implicit-Solvent Coarse-Grained Simulation with a Fluctuating Interface Reveals a Molecular Mechanism for Peptoid Monolayer Buckling. J Chem Theory Comput 12: 345–352.    
  • 75. Drew K, Renfrew PD, Butterfoss GL (2013) Adding Diverse Noncanonical Backbones to Rosetta: Enabling Peptidomimetic Design. PLoS One 8: e67051.
  • 76. Kaufmann KW, Lemmon GH, DeLuca SL, et al. (2010) Practically Useful: What the Rosetta Protein Modeling Suite Can Do for You. Biochemistry 49: 2987–2998.    
  • 77. Renfrew PD, Craven TW, Butterfoss GL, et al. (2013) A Rotamer Library to Enable Modeling and Design of Peptoid Foldamers. J Am Chem Soc 136: 8772–8782.
  • 78. Laio A, Gervasio FL (2008) Metadynamics: a method to simulate rare events and reconstruct the free energy in biophysics, chemistry and material science. Rep Prog Phys 71: 126601.    


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Copyright Info: 2017, Erik E. Santiso, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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