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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
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
Cited by
Sorted by citations
Items 101–122 of 122
Wang, Y., Maity, N. C., Zhao, L., Krämer, M., Hasegawa, J., Shichibu, Y., Konishi, K., Wang, X., Song, Z., Bando, M., et al. (2021) · Chemistry Letters · doi:10.1246/cl.210112 · Cited by 1
Copolymer Sequence Regulation Enabled by Reactivity Ratio Fingerprints via Machine Learning
Zhang, Z., Zhou, C., Chen, Y., Gu, Y. Q., & Chen, M. (2025) · Angewandte Chemie · doi:10.1002/ange.202513086 · Cited by 1
Characterization of Sequence Distributions in Random and Semi-Random Copolymers
Cole, M., Fitch, J., & Meyer, T. Y. (2026) · Macromolecules · doi:10.1021/acs.macromol.5c01799 · Cited by 1
Topological Doping of Charged Bottlebrush Polymers for Efficient Artificial Ion Channels
Lin, Y., Wu, B., Ji, C., & Lang, C. (2026) · Polymer science & technology. · doi:10.1021/polymscitech.6c00031 · Cited by 1
Multimerization interactions between protein-inspired single-chain random heteropolymers
Hilburg, S. L., Jin, T., Ganesh, P., & Alexander‐Katz, A. (2026) · PLoS ONE · doi:10.1371/journal.pone.0349103 · Cited by 1
Kim, M., Patil, S., Wiegart, L., Cheng, S., & Cai, L. (2026) · Science Advances · doi:10.1126/sciadv.aec4474 · Cited by 1
Polymeric protagonists for biological processes
Gudinas, A. P., & Mai, D. J. (2023) · Nature Chemistry · doi:10.1038/s41557-023-01219-9 · Cited by 1
Stoddart, A. (2020) · Nature Reviews Materials · doi:10.1038/s41578-020-0179-z
DNA nanopores as artificial membrane channels for origami-based bioelectronicsPreprint
Luo, L., Manda, S., Park, Y., Demir, B., Vicente, J., Anantram, M. P., Ören, E. E., Gopinath, A., & Rolandi, M. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.03.01.530356
Self-citationEnsembles of synthetic polymers mimic biological fluids
Perry, S. L. (2023) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2023.05.012
Longhini, A. P., Fattah, M. A., Sala‐Jarque, J., DuBose, A., Rivera, E. K., Sclafani, O., Zhou, J., Anatot, J. E., Thompson, M. P., Unger, M. T., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.02.636155 · Cited by 1
Self-citationBifunctional Polyester Synthase–Channel Driving Phosphorylated PHB–PHV Synthesis and Ion ConductancePreprint
Abd-El-Haleem, D. A. M. (2025) · Research Square · doi:10.21203/rs.3.rs-6506981/v1
Li, C., Wu, Y., Bao, S., Xu, Z., Yan, J., Li, H., Yu, X., Weng, Z., Xu, J., Wang, T., et al. (2025) · Angewandte Chemie · doi:10.1002/ange.202500986
Self-citationUchida, N., Ishizaka, R., Kawakita, A., Ueno, H., Noji, H., Kasai, R. S., Yokoyama, T., Kurihara, S., Noguchi, T., Watanabe, G., et al. (2025) · Journal of the American Chemical Society · doi:10.1021/jacs.5c13384
Selectively tunable coordination polymer engineered via ligand sequence
Zhang, Y., Zhang, X., Xiong, C., Qin, Y., Qin, Y., & Jia, Y. (2025) · Materials Today Chemistry · doi:10.1016/j.mtchem.2025.103158
Zheng, Z., Wei, X., Lin, Y., Tao, S., Li, H., Ji, Z., Wei, H., Jin, J., Zhao, F., Lang, C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26667211
Guo, Z., Sun, Y., Xue, T.-R., Jing, X., & Zhao, P. (2026) · Electrochimica Acta · doi:10.1016/j.electacta.2026.148824
Zhang, Y., Zhang, G., Chen, B., Wang, Y., Wei, J., Liu, Q., & Liu, X. (2026) · Green Energy & Environment · doi:10.1016/j.gee.2026.07.007
Li, C., Bao, S., Liu, W., Yue, Y., Xu, J., Yan, T., Xu, Z. M., Zhou, Y., Cao, Y., Wu, Y., et al. (2026) · Chemical Engineering Journal · doi:10.1016/j.cej.2026.179732
Self-citationHibi, Y. (2026) · Polymer Chemistry · doi:10.1039/d6py00532b
Molecular Origins of Catalysis in Random Heteropolymer Enzyme Mimics through All-Atom Simulations
Hilburg, S. L., Han, Z., Jin, T., Ganesh, P., Yu, H., Kang, P., Xu, T., & Alexander‐Katz, A. (2026) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.6c05638
Self-citation
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review