Thermodynamic Driving Forces for the Self-Assembly of Diblock Polypeptoids
Source abstract
Abstract
High Resolution Image Download MS PowerPoint Slide Peptoid polymers with sequence-defined side chains are observed to self-assemble into a variety of structures spanning nanometer and micron scales. We explored a diblock copolypeptoid, poly( N -decylglycine) 10 - block -poly( N -2-(2-(2-methoxyethoxy)ethoxy)-ethylglycine) 10 (abbreviated as Ndc 10 -Nte 10 ), which forms crystalline nanofibers and nanosheets as evidenced by recent cryo-transmission electron microscopy, atomic force microscopy, X-ray diffraction, and calorimetry. Using all-atom molecular dynamics simulations, we examined the thermodynamic forces driving such self-assembly and how nanoscale morphology is tailored through modification of the N-terminus or via the addition of small molecules (urea). We have found that the hydrophobic Ndc domain alignment is key to the formation of molecular stacks whose growth is limited by electrostatic repulsion between protonated N-termini. These stacks are the building blocks that assemble via cooperative van der Waals attraction between the tips of extended decyl side chains to form nanofibers or nanosheets with a well-converged intermolecular interaction energy. Assemblies are significantly more stable in urea solution due to its strong attraction to the peptoid–solvent interface. Isolated peptoids exhibit curved all- cis backbones, which straighten within molecular stacks to maximize contact and registry between neighboring molecules. We hypothesize that competition between this attractive interaction and a strain cost for straightening the backbone is what leads to finite stack widths that define crystalline nanofibers of protonated Ndc 10 -Nte 10 . Growth is proposed to proceed through backbone unfurling via trans defects, which is more prevalent in aqueous solution than in THF, indicating a possible pathway to self-assembly under experimentally defined synthesis conditions (viz., THF evaporation).
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Research context
OpenAlex topics: Bacteriophages and microbial interactions · Biochemical and Structural Characterization · Protein Structure and Dynamics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
The Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
Funding
Basic Energy Sciences
References (48)
Show source-provided references
1. 10.1002/bip.2157310.1002/bip.21573 ↗
2. 10.1039/D0TB00477D10.1039/D0TB00477D ↗
3. 10.1007/s00289-016-1902-110.1007/s00289-016-1902-1 ↗
4. 10.1002/bip.2307010.1002/bip.23070 ↗
5. 10.1021/acs.biomac.5b0156110.1021/acs.biomac.5b01561 ↗
6. 10.1021/acsinfecdis.1c0053610.1021/acsinfecdis.1c00536 ↗
7. 10.1021/acs.biomac.9b0071310.1021/acs.biomac.9b00713 ↗
8. 10.1002/smll.20180354410.1002/smll.201803544 ↗
9. 10.1002/smll.20190248510.1002/smll.201902485 ↗
10. 10.1021/acs.accounts.5b0043910.1021/acs.accounts.5b00439 ↗
11. 10.1021/nn401571410.1021/nn4015714 ↗
12. 10.1021/ja00052a07610.1021/ja00052a076 ↗
13. 10.1021/acs.macromol.8b0150810.1021/acs.macromol.8b01508 ↗
14. 10.1073/pnas.151716911310.1073/pnas.1517169113 ↗
15. 10.1073/pnas.201181611710.1073/pnas.2011816117 ↗
16. 10.1038/s41467-017-02059-110.1038/s41467-017-02059-1 ↗
17. Jiang X. · 2023
18. 10.1002/bip.2326510.1002/bip.23265 ↗
19. Cheng Y. · 2015 · 450
20. 10.1038/nmeth.416910.1038/nmeth.4169 ↗
21. 10.1039/C9SM00633H10.1039/C9SM00633H ↗
22. 10.1073/pnas.190999211610.1073/pnas.1909992116 ↗
23. 10.1021/acs.jpcb.2c0184310.1021/acs.jpcb.2c01843 ↗
24. 10.1021/acsnano.2c1250310.1021/acsnano.2c12503 ↗
25. 10.1021/acs.jpcb.0c0456710.1021/acs.jpcb.0c04567 ↗
26. 10.48550/arXiv.1903.0197510.48550/arXiv.1903.01975 ↗
27. 10.1002/jcc.2347810.1002/jcc.23478 ↗
28. 10.1002/jcc.2585010.1002/jcc.25850 ↗
29. 10.1371/journal.pone.016002310.1371/journal.pone.0160023 ↗
30. Weiser, L. J. Developing Simulation Models of Peptoid Polymers. Doctoral, North Carolina State University, 2017.
31. 10.3934/matersci.2017.5.102910.3934/matersci.2017.5.1029 ↗
32. 10.1038/nature1536310.1038/nature15363 ↗
33. 10.1073/pnas.180039711510.1073/pnas.1800397115 ↗
34. 10.1021/acs.biomac.1c0138510.1021/acs.biomac.1c01385 ↗
35. 10.1021/jp204407d10.1021/jp204407d ↗
36. Yu, T.; Luo, X.; Prendergast, D.; Balsara, N.; Zuckermann, R.; Jiang, X. Self-Assembled Polypeptoid Nanostructures Revealed by 3-D Cryogenic Electron Microscopy. APS March Meeting Abstracts, 2022; Vol. 2022, p M19–004.
37. 10.1002/jcc.2136710.1002/jcc.21367 ↗
38. 10.1021/ci300363c10.1021/ci300363c ↗
39. 10.1021/ci300364910.1021/ci3003649 ↗
40. 10.1021/j100142a00410.1021/j100142a004 ↗
41. 10.1002/jcc.116610.1002/jcc.1166 ↗
42. 10.1063/1.275469010.1063/1.2754690 ↗
43. 10.1016/j.softx.2015.06.00110.1016/j.softx.2015.06.001 ↗
44. 10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H ↗
45. 10.1063/1.240842010.1063/1.2408420 ↗
46. 10.1063/1.32869310.1063/1.328693 ↗
47. 10.1063/1.44811810.1063/1.448118 ↗
48. 10.1016/j.cpc.2013.09.01810.1016/j.cpc.2013.09.018 ↗