(773i) Aggregation and Self-Assembly of Biomimetic Polymers at Interfaces | AIChE

(773i) Aggregation and Self-Assembly of Biomimetic Polymers at Interfaces

Authors 

Prakash, A. - Presenter, University of Washington
Pfaendtner, J., University of Washington
Mundy, C. J., Pacific Northwest National Laboratory
Peptoids, or N-glycine substitutes, have been replacing conventional peptides for use as scaffolds, anti-fouling coatings, and functionalized membranes. Their ease of synthesis, thermal, and enzymatic stability and large combinatorial library of sequences make them attractive replacements for peptides1. In this talk, we will highlight the driving forces of aggregation and self-assembly of peptoids using molecular dynamics simulations and metadynamics2–6enhanced sampling.

We discuss how peptoids differ from peptides with simulations of model systems (sarcosine and alanine), using a forcefield that is re-parameterized for peptoids7. We examine the origins of peptoid hydrophilicity, and the differences between the conformational space explored by peptoids and peptides. Considering these results, we try to understand how peptoids form nanostructures on surfaces. For a comprehensive examination of the assembly process, it is essential to understand both solution behavior (to understand nanostructure seed formation), and interfacial behavior (to understand complex formation for nanostructures). Thus, we investigate how peptoids form clusters in solution and the effect of ions on these clusters. We find that pi-stacking and backbone flexibility allow peptoids to retain elongated conformations. Further, we discuss how peptoids may exhibit crystal facet selectivity (for gold) and how their assembly may be templated by the surface structure (for mica). These simulations highlight molecular-level origins of assembly of peptoids in different environments, which are poorly understood, using a multi-scale modeling approach.

Reference:

(1) Zuckermann, R. N. Biopolymers 2011, 96(5), 545–555.

(2) Pfaendtner, J.; Bonomi, M. J. Chem. Theory Comput. 2015, 11(11), 5062–5067.

(3) Barducci, A.; Bussi, G.; Parrinello, M. Phys. Rev. Lett. 2008, 100(2), 20603.

(4) Valsson, O.; Tiwary, P.; Parrinello, M. Annu. Rev. Phys. Chem. 2016, 67(1), 159–184.

(5) Raiteri, P.; Laio, A.; Gervasio, F. L.; Micheletti, C.; Parrinello, M. J. Phys. Chem. B 2006, 110(8), 3533–3539.

(6) Tiwary, P.; Parrinello, M. J. Phys. Chem. B 2015, 119(3), 736–742.

(7) Mirijanian, D. T.; Mannige, R. V.; Zuckermann, R. N.; Whitelam, S. J. Comput. Chem. 2014, 35 (5), 360–370.

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