The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Single-chain heteropolymers transport protons selectively and rapidly
Open accessAbstract
Precise protein sequencing and folding are believed to generate the structure and chemical diversity of natural channels 1,2, both of which are essential to synthetically achieve proton transport performance comparable to that seen in natural systems. Geometrically defined channels have been fabricated using peptides, DNAs, carbon nanotubes, sequence-defined polymers and organic frameworks 3-13. However, none of these channels rivals the performance observed in their natural counterparts. Here we show that without forming an atomically structured channel, four-monomer-based random heteropolymers (RHPs)14 can mimic membrane proteins and exhibit selective proton transport across lipid bilayers at a rate similar to those of natural proton channels. Statistical control over the monomer distribution in an RHP leads to segmental heterogeneity in hydrophobicity, which facilitates the insertion of single RHPs into the lipid bilayers. It also results in bilayer-spanning segments containing polar monomers that promote the formation of hydrogen-bonded chains 15,16 for proton transport. Our study demonstrates the importance of the adaptability that is enabled by statistical similarity among RHP chains and of the modularity provided by the chemical diversity of monomers, to achieve uniform behaviour in heterogeneous systems. Our results also validate statistical randomness as an unexplored approach to realize protein-like behaviour at the single-polymer-chain level in a predictable manner.
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“Therefore, we aimed to statistically replicate the sequence features of functional classes through ideal random copolymerization of the six functional monomers, which has minimal composition drift during polymerization and enables statistically controlled sequences19,27–29.”
From Data-driven de novo design of super-adhesive hydrogels (2025) · cites this paper as [29]
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Cites
VMD: visual molecular dynamics
Humphrey, W., Dalke, A., & Schulten, K. (1996) · Journal of Molecular Graphics · doi:10.1016/0263-7855(96)00018-5 · Cited by 66,952
Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
Particle mesh Ewald: An N⋅log(N) method for Ewald sums in large systems
Darden, T., York, D., & Pedersen, L. (1993) · The Journal of Chemical Physics · doi:10.1063/1.464397 · Cited by 29,638
A simple method for displaying the hydropathic character of a protein
Kyte, J., & Doolittle, R. F. (1982) · Journal of Molecular Biology · doi:10.1016/0022-2836(82)90515-0 · Cited by 22,927
A tutorial on hidden Markov models and selected applications in speech recognition
Rabiner, L. R. (1989) · Proceedings of the IEEE · doi:10.1109/5.18626 · Cited by 22,743
A smooth particle mesh Ewald method
Essmann, U., Perera, L., Berkowitz, M., Darden, T., Lee, H.-C., & Pedersen, L. (1995) · The Journal of Chemical Physics · doi:10.1063/1.470117 · Cited by 21,378
Polymorphic transitions in single crystals: A new molecular dynamics method
Parrinello, M., & Rahman, A. (1981) · Journal of Applied Physics · doi:10.1063/1.328693 · Cited by 20,009
GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation
Hess, B., Kutzner, C., van der Spoel, D., & Lindahl, E. R. (2008) · Journal of Chemical Theory and Computation · doi:10.1021/ct700301q · Cited by 15,830
All-Atom Empirical Potential for Molecular Modeling and Dynamics Studies of Proteins
MacKerell, A. D., Bashford, D., Bellott, M., Dunbrack, R. L., Evanseck, J. D., Field, M. J., Fischer, S., Gao, J., Guo, H., Ha, S., et al. (1998) · The Journal of Physical Chemistry B · doi:10.1021/jp973084f · Cited by 14,429
P ACKMOL : A package for building initial configurations for molecular dynamics simulations
Martı́nez, L., Andrade, R., Birgin, E. G., & Martínez, J. M. (2009) · Journal of Computational Chemistry · doi:10.1002/jcc.21224 · Cited by 10,013
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Self-citationData-driven de novo design of super-adhesive hydrogels
Liao, H., Hu, S., Yang, H., Wang, L., Tanaka, S., Takigawa, I., Li, W., Fan, H., & Gong, J. P. (2025) · Nature · doi:10.1038/s41586-025-09269-4 · Cited by 169
“Therefore, we aimed to statistically replicate the sequence features of functional classes through ideal random copolymerization of the six functional monomers, which has minimal composition drift during polymerization and enables statistically controlled sequences 19,27–29 .”
A Light‐Operated Molecular Cable Car for Gated Ion Transport
Wang, C., Wang, S., Yang, H., Xiang, Y., Wang, X., Bao, C., Zhu, L., Tian, H., & Qu, D. (2021) · Angewandte Chemie International Edition · doi:10.1002/anie.202102838 · Cited by 122
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Self-citationShi, B., Pang, X., Lyu, B., Wu, H., Shen, J., Guan, J., Wang, X., Fan, C., Cao, L., Zhu, T., et al. (2023) · Advanced Materials · doi:10.1002/adma.202211004 · Cited by 104
Metadata
- Authors
- Jiang, T., Hall, A., Eres, M., Hemmatian, Z., Qiao, B., Zhou, Y., Ruan, Z., Couse, A. D., Heller, W. T., Huang, H., de la Cruz, M. O., Rolandi, M., & Xu, T.
- Affiliations
- Xiamen University (CN)
- University of California, Berkeley (US)
- University of California, Santa Cruz (US)
- Northwestern University (US)
- Indiana University Bloomington (US)
- Oak Ridge National Laboratory (US)
- Lawrence Berkeley National Laboratory (US)
- Corresponding author
- Xu, Ting
- ORCID
- Venue
- Nature
- Published
- 2020-01-08
- Volume
- 577
- Issue
- 7789
- Pages
- 216-220
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2999129979
- Cited by
- 122
- References
- 48
- Citations by year
- 2026: 13 · 2025: 26 · 2024: 24 · 2023: 23 · 2022: 18 · 2021: 8 · 2020: 10
- FWCI
- 4.63
- Type
- journal article
- Language
- en
- Open access
- green
- www.osti.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DRYAD (public-domain)
- Funders
- National Science Foundation (DEAC02-05CH11231, W911NF-13)
- U.S. Department of Defense (DE-AC02-05CH11231)
- U.S. Department of Energy (-AC02-05CH11231, DE‐FG02‐, DEFG0208ER46539, 05CH11231, DE AC02 05CH11231, FG02-08ER46539, DE-AC02-)
- U.S. Department of Commerce
- Sherman Fairchild Foundation
- National Institutes of Health (1s10od024998-01, DE-AC02–05CH11231)
- National Institute of Standards and Technology (DE-AC02-05CH11231)
- Office of Science (DEAC02–05CH11231, AC02-05CH11231, DE-AC02)
- Division of Materials Research
- Basic Energy Sciences (DE-AC02, DE-FG02-08ER46539, DE-AC02-05CH11231., DE-FG02, AC02–05CH11231)
- Army Research Office (DE-AC02-05CH11231, W911NF- 13-1-0232, W911NF-13-1-, W911NF-13, W911NF)
- Oak Ridge National Laboratory (DE-AC0205CH11231)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Nanopore and Nanochannel Transport Studies
- Physical Sciences › Chemistry › Organic Chemistry › Advanced Polymer Synthesis and Characterization
- Physical Sciences › Chemistry › Organic Chemistry › Supramolecular Chemistry and Complexes
- Keywords
- random heteropolymers, proton transport, lipid bilayers, ion selectivity, artificial ion channels, membrane mimetics, hydrogen-bonded chains, statistical randomness
- MeSH terms
- Lipid Bilayers, Lipids, Models, Molecular, Molecular Conformation, Polymers, Protons
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