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Molecular modeling studies of peptoid polymers

  • Received: 05 June 2017 Accepted: 25 July 2017 Published: 12 September 2017
  • 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.

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

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  • 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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