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Cited by 293

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Understanding nature's design for a nanosyringe

Open access
Lopez, Carlos F., Nielsen, Steve O., Moore, Preston B., Klein, Michael L.·2004·Proceedings of the National Academy of Sciences

Abstract

Synthetic and natural peptide assemblies can possess transport or conductance activity across biomembranes through the formation of nanopores. The fundamental mechanisms of membrane insertion necessary for antimicrobial or synthetic pore formation are poorly understood. We observe a lipid-assisted mechanism for passive insertion into a model membrane from molecular dynamics simulations. The assembly used in the study, a generic nanotube functionalized with hydrophilic termini, is assisted in crossing the membrane core by transleaflet lipid flips. Lipid tails occlude a purely hydrophobic nanotube. The observed insertion mechanism requirements for hydrophobic-hydrophilic matching have implications for the design of synthetic channels and antibiotics.

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Crossref · 10.1073/pnas.0400352101

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Metadata

Authors
Lopez, C. F., Nielsen, S. O., Moore, P. B., & Klein, M. L.
Venue
Proceedings of the National Academy of Sciences
Published
2004-03-12
Volume
101
Issue
13
Pages
4431-4434
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2148138913
Cited by
293
References
1
FWCI
5.47
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Understanding nature's design for a nanosyringe. https://app.cochat.ai/papers/10.1073/pnas.0400352101
The paper
Lopez, C. F., Nielsen, S. O., Moore, P. B., & Klein, M. L. (2004). Understanding nature's design for a nanosyringe. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0400352101

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.