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Cited by 18Lipid Membrane Structure and BehaviorRNA Interference and Gene DeliveryAntimicrobial Peptides and Activities

The DOI matches its Crossref record; 93 of the 93 references it cites were found in a registry or an index.

Computational Insights into Membrane Disruption by Cell-Penetrating Peptides

Open access
Catalina-Hernandez, Eric, Aguilella-Arzo, Marcel, Peralvarez-Marin, Alex, Lopez-Martin, Mario·2025·Journal of Chemical Information and Modeling
DOI 10.1021/acs.jcim.4c01940PMC PMC11815844

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Abstract

Cell-penetrating peptides (CPPs) can translocate into cells without inducing cytotoxicity. The internalization process implies several steps at different time scales ranging from microseconds to minutes. We combine adaptive Steered Molecular Dynamics (aSMD) with conventional Molecular Dynamics (cMD) to observe nonequilibrium and equilibrium states to study the early mechanisms of peptide-bilayer interaction leading to CPPs internalization. We define three membrane compositions representing bilayer sections, neutral lipids (i.e., upper leaflet), neutral lipids with cholesterol (i.e., hydrophobic core), and neutral/negatively charged lipids with cholesterol (i.e., lower leaflet) to study the energy barriers and disruption mechanisms of Arg9, MAP, and TP2, representing cationic, amphiphilic, and hydrophobic CPPs, respectively. Cholesterol and negatively charged lipids increase the energetic barriers for the peptide-bilayer crossing. TP2 interacts with the bilayer by hydrophobic insertion, while Arg9 disrupts the bilayer by forming transient or stable pores. MAP has shown both behaviors. Collectively, these findings underscore the significance of innovative computational approaches in studying membrane-disruptive peptides and, more specifically, in harnessing their potential for cell penetration.

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Crossref · 10.1021/acs.jcim.4c01940

Cites

93 of 93 references verified0 citation errors · 0 not checkable

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Figures

Figure 1 Potential of mean force (PMF) calculation in (A) forward and backward aSMD simulations and (B) different pulling speed simulations. (A) PMF has been calculated forward (normal, blue) and backward (return, orange) to calibrate the system and test that the bilayers’ energy barriers were comparable. The effect of normal and return aSMD has been computed for the three membrane compositions. (B) To test the best pulling velocity, aSMD has been simulated at two different speeds: 10 Å/ns (orange) and 1 Å/ns (blue). The effect of pulling speed has been done in DPPC membrane.
Figure 1 Potential of mean force (PMF) calculation in (A) forward and backward aSMD simulations and (B) different pulling speed simulations. (A) PMF has been calculated forward (normal, blue) and backward (return, orange) to calibrate the system and test that the bilayers’ energy barriers were comparable. The effect of normal and return aSMD has been computed for the three membrane compositions. (B) To test the best pulling velocity, aSMD has been simulated at two different speeds: 10 Å/ns (orange) and 1 Å/ns (blue). The effect of pulling speed has been done in DPPC membrane.CC BY · PubMed Central
Figure 2 Initial and final snapshots of the aSMD process. Starting (A) and final (B) snapshots of the aSMD for the three CPPs and the three membrane compositions. See Video S1 for further details.
Figure 2 Initial and final snapshots of the aSMD process. Starting (A) and final (B) snapshots of the aSMD for the three CPPs and the three membrane compositions. See Video S1 for further details.CC BY · PubMed Central
Figure 3 PMF barrier of peptides with respect to the membrane composition. The values indicated correspond to the last value (highest energy) of the PMF analysis. PMF profiles of the three membrane compositions are shown. PMF profiles of all replicas are shown with a transparency of 10%.
Figure 3 PMF barrier of peptides with respect to the membrane composition. The values indicated correspond to the last value (highest energy) of the PMF analysis. PMF profiles of the three membrane compositions are shown. PMF profiles of all replicas are shown with a transparency of 10%.CC BY · PubMed Central
Figure 4 Illustrative representation of the peptide location in the 3 membrane compositions after the 100 ns of conventional MD (relaxation). Peptides are colored as Arg9 in dark green, MAP in rose, TP2 in gold. The polar heads of phospholipids in both the upper and lower bilayers are illustrated in darker and lighter shades of gray, respectively, while the lipid tails are portrayed in transparent white. Peptide colors are maintained in the following figures. Waters are omitted for clarity. See Video S1 for further details.
Figure 4 Illustrative representation of the peptide location in the 3 membrane compositions after the 100 ns of conventional MD (relaxation). Peptides are colored as Arg9 in dark green, MAP in rose, TP2 in gold. The polar heads of phospholipids in both the upper and lower bilayers are illustrated in darker and lighter shades of gray, respectively, while the lipid tails are portrayed in transparent white. Peptide colors are maintained in the following figures. Waters are omitted for clarity. See Video S1 for further details.CC BY · PubMed Central
Figure 5 Residue occupancy by the polar head of the phospholipids in the upper and lower leaflets. Polar heads corresponding to PC (phosphatidylcholine) occupancy is shown for DPPC, DPPC:DOPC:CHOL, and DPPC:DOPC:DPPS:DOPSCHOL membranes. For the third membrane, PS (phosphatidylserine) occupancy is also shown. The occupancy analysis refers to the first replica.
Figure 5 Residue occupancy by the polar head of the phospholipids in the upper and lower leaflets. Polar heads corresponding to PC (phosphatidylcholine) occupancy is shown for DPPC, DPPC:DOPC:CHOL, and DPPC:DOPC:DPPS:DOPSCHOL membranes. For the third membrane, PS (phosphatidylserine) occupancy is also shown. The occupancy analysis refers to the first replica.CC BY · PubMed Central

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Cites

Research works printed but not linked: 3

  1. 10.1016/S0165-6147(00)01447-4 · DOI · Paper page
  2. 10.1038/s41592-022-01488-1 · DOI · Paper page
  3. Case, D. A.; Belfon, K.; Ben-Shalom, I. Y.; Brozell, S. R.; Cerutti, D. S.; T. E. Cheatham, I. I. I.; Cruzeiro, V. W. D.; Darden, T. A.; Duke, R. E.; Giambasu, G.; Gilson, M. K.; Gohlke, H.; Goetz, A. W.; Harris, R.; Izadi, S.; Izmailov, S. A.; Kasavajhala, K.; Kovalenko, A.; Krasny, R.; Kurtzman, T.; Lee, T. S.; LeGrand, S.; Li, P.; Lin, C.; Liu, J.; Luchko, T.; Luo, R.; Man, V.; Merz, K. M.; Miao, Y.; Mikhailovskii, O.; Monard, G.; Nguyen, H.; Onufriev, A.; Pan, F.; Pantano, S.; Qi, R.; Roe, D. R.; Roitberg, A.; Sagui, C.; Schott-Verdugo, S.; Shen, J.; Simmerling, C. L.; Skrynnikov, N. R.; Smith, J.; Swails, J.; Walker, R. C.; Wang, J.; Wilson, L.; Wolf, R. M.; Wu, X.; Xiong, Y.; Xue, Y.; York, D. M.; Kollman, P. A. AMBER. 2020; Vol. 2020.

Metadata

Authors
Catalina-Hernandez, E., Aguilella-Arzo, M., Peralvarez-Marin, A., & Lopez-Martin, M.
Affiliations
  • Unit of Biophysics, Department of Biochemistry and Molecular Biology, Facultat de Medicina, Av. Can Domènech s/n, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Catalonia, Spain
  • Laboratory of Molecular Biophysics, Department of Physics
ORCID
Venue
Journal of Chemical Information and Modeling
Publisher
American Chemical Society (ACS)
Published
2025-01-17
Volume
65
Issue
3
Pages
1549-1559
ISSN
  • 1549-9596 (ISSN-L)
  • 1549-960X
DOI
10.1021/acs.jcim.4c01940
PMC
PMC11815844
OpenAlex
W4406508939
Cited by
18
References
93
Citations by year
2026: 11 · 2025: 7
FWCI
5.41
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Chemical Information and Modeling (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Dipòsit Digital de Documents de la UAB (Universitat Autònoma de Barcelona) (submittedVersion, cc-by)
Funders
  • Ministerio de Ciencia, Innovaci?n y Universidades (MGSD2021-10)
  • Universitat Jaume I (UJI-B2022-42)
  • Agencia Nacional de Promoci?n Cient?fica y Tecnol?gica (PID2020-120222GB-I00, PID2022-142795NB-I00)
  • Universitat Aut?noma de Barcelona (B21P0033)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Lipid Membrane Structure and Behavior
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Interference and Gene Delivery
  • Life Sciences › Immunology and Microbiology › Microbiology › Antimicrobial Peptides and Activities
Keywords
cell-penetrating peptides, membrane damage, peptide internalization, cholesterol, negatively charged lipids, energy barrier, pore formation, hydrophobic insertion, maps, TP2, cationic peptides, peptide amphiphiles, hydrophobic peptides
MeSH terms
Cell Membrane, Cholesterol, Lipid Bilayers, Thermodynamics, Molecular Dynamics Simulation, Cell-Penetrating Peptides, Hydrophobic and Hydrophilic Interactions

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