Free Energy of Membrane Pore Formation and Stability from Molecular Dynamics Simulations

. 2025 Jan 27 ; 65 (2) : 908-920. [epub] 20250110

Jazyk angličtina Země Spojené státy americké Médium print-electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid39792085

Understanding the molecular mechanisms of pore formation is crucial for elucidating fundamental biological processes and developing therapeutic strategies, such as the design of drug delivery systems and antimicrobial agents. Although experimental methods can provide valuable information, they often lack the temporal and spatial resolution necessary to fully capture the dynamic stages of pore formation. In this study, we present two novel collective variables (CVs) designed to characterize membrane pore behavior, particularly its energetics, through molecular dynamics (MD) simulations. The first CV─termed Full-Path─effectively tracks both the nucleation and expansion phases of pore formation. The second CV─called Rapid─is tailored to accurately assess pore expansion in the limit of large pores, providing quick and reliable method for evaluating membrane line tension under various conditions. Our results clearly demonstrate that the line tension predictions from both our CVs are in excellent agreement. Moreover, these predictions align qualitatively with available experimental data. Specifically, they reflect higher line tension of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) membranes containing 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-l-serine (POPS) lipids compared to pure POPC, the decrease in line tension of POPC vesicles as the 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol (POPG) content increases, and higher line tension when ionic concentration is increased. Notably, these experimental trends are accurately captured only by the all-atom CHARMM36 and prosECCo75 force fields. In contrast, the all-atom Slipids force field, along with the coarse-grained Martini 2.2, Martini 2.2 polarizable, and Martini 3 models, show varying degrees of agreement with experiments. Our developed CVs can be adapted to various MD simulation engines for studying pore formation, with potential implications in membrane biophysics. They are also applicable to simulations involving external agents, offering an efficient alternative to existing methodologies.

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Kabelka I.; Vácha R. Advances in Molecular Understanding of α-Helical Membrane-Active Peptides. Acc. Chem. Res. 2021, 54, 2196–2204. 10.1021/acs.accounts.1c00047. PubMed DOI

Brogden K. A. Antimicrobial peptides: Pore formers or metabolic inhibitors in bacteria?. Nat. Rev. Microbiol. 2005, 3, 238–250. 10.1038/nrmicro1098. PubMed DOI

Boukany P. E.; et al. Nanochannel electroporation delivers precise amounts of biomolecules into living cells. Nat. Nanotechnol. 2011, 6, 747–754. 10.1038/nnano.2011.164. PubMed DOI

Lee M. T.; Chen F. Y.; Huang H. W. Energetics of Pore Formation Induced by Membrane Active Peptides. Biochemistry 2004, 43, 3590–3599. 10.1021/bi036153r. PubMed DOI

Qian S.; Wang C.; Yang L.; Huang H. W. Structure of transmembrane pore induced by Bax-derived peptide: Evidence for lipidic pores. Proc. Natl. Acad. Sci. U. S. A. 2008, 105, 17379–17383. 10.1073/pnas.0807764105. PubMed DOI PMC

Qian S.; Wang C.; Yang L.; Huang H. W. Structure of the alamethicin pore reconstructed by x-ray diffraction analysis. Biophys. J. 2008, 94, 3512–3522. 10.1529/biophysj.107.126474. PubMed DOI PMC

Afonin S.; Dürr U. H.; Wadhwani P.; Salgado J.; Ulrich A. S. Solid state NMR structure analysis of the antimicrobial peptide gramicidin s in lipid membranes: Concentration-dependent re-alignment and self-assembly as a β-barrel. Top. Curr. Chem. 2008, 273, 139–154. 10.1007/128_2007_20. PubMed DOI

Esteban-Martín S.; Strandberg E.; Salgado J.; Ulrich A. S. Solid state NMR analysis of peptides in membranes: Influence of dynamics and labeling scheme. Biochim. Biophys. Acta - Biomembr. 2010, 1798, 252–257. 10.1016/j.bbamem.2009.08.010. PubMed DOI

Aisenbrey C.; Marquette A.; Bechinger B. Adv. Exp. Med. Biol. 2019, 1117, 33–64. 10.1007/978-981-13-3588-4_4. PubMed DOI

García-Sáez A. J.; Chiantia S.; Salgado J.; Schwille P. Pore formation by a bax-derived peptide: Effect on the line tension of the membrane probed by AFM. Biophys. J. 2007, 93, 103–112. 10.1529/biophysj.106.100370. PubMed DOI PMC

Henderson J. M.; Waring A. J.; Separovic F.; Lee K. Y. C. Antimicrobial Peptides Share a Common Interaction Driven by Membrane Line Tension Reduction. Biophys. J. 2016, 111, 2176–2189. 10.1016/j.bpj.2016.10.003. PubMed DOI PMC

Kakorin S.; Neumann E. Ionic conductivity of electroporated lipid bilayer membranes. Bioelectrochemistry 2002, 56, 163–166. 10.1016/s1567-5394(02)00040-3. PubMed DOI

Song C.; Weichbrodt C.; Salnikov E. S.; Dynowski M.; Forsberg B. O.; Bechinger B.; Steinem C.; De Groot B. L.; Zachariae U.; Zeth K. Crystal structure and functional mechanism of a human antimicrobial membrane channel. Proc. Natl. Acad. Sci. U. S. A. 2013, 110, 4586–4591. 10.1073/pnas.1214739110. PubMed DOI PMC

Kirsch S. A.; Böckmann R. A. Membrane pore formation in atomistic and coarse-grained simulations. Biochim. Biophys. Acta - Biomembr. 2016, 1858, 2266–2277. 10.1016/j.bbamem.2015.12.031. PubMed DOI

Dixit M.; Lazaridis T. Free energy of hydrophilic and hydrophobic pores in lipid bilayers by free energy perturbation of a restraint. J. Chem. Phys. 2020, 153, 05410110.1063/5.0016682. PubMed DOI PMC

Bubnis G.; Grubmüller H. Sequential Water and Headgroup Merger: Membrane Poration Paths and Energetics from MD Simulations. Biophys. J. 2020, 119, 2418–2430. 10.1016/j.bpj.2020.10.037. PubMed DOI PMC

Awasthi N.; Hub J. S. Simulations of pore formation in lipid membranes: Reaction coordinates, convergence, hysteresis, and finite-size effects. J. Chem. Theory Comput. 2016, 12, 3261–3269. 10.1021/acs.jctc.6b00369. PubMed DOI

Hub J. S.; Awasthi N. Probing a Continuous Polar Defect: A Reaction Coordinate for Pore Formation in Lipid Membranes. J. Chem. Theory Comput. 2017, 13, 2352–2366. 10.1021/acs.jctc.7b00106. PubMed DOI

Hub J. S. Joint Reaction Coordinate for Computing the Free-Energy Landscape of Pore Nucleation and Pore Expansion in Lipid Membranes. J. Chem. Theory Comput. 2021, 17, 1229–1239. 10.1021/acs.jctc.0c01134. PubMed DOI

Tribello G. A.; Bonomi M.; Branduardi D.; Camilloni C.; Bussi G. PLUMED 2: New feathers for an old bird. Comput. Phys. Commun. 2014, 185, 604–613. 10.1016/j.cpc.2013.09.018. DOI

Abraham M. J.; Murtola T.; Schulz R.; Páll S.; Smith J. C.; Hess B.; Lindah E. Gromacs: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 2015, 1–2, 19–25. 10.1016/j.softx.2015.06.001. DOI

Jo S.; Lim J. B.; Klauda J. B.; Im W. CHARMM-GUI membrane builder for mixed bilayers and its application to yeast membranes. Biophys. J. 2009, 97, 50–58. 10.1016/j.bpj.2009.04.013. PubMed DOI PMC

Wu E. L.; Cheng X.; Jo S.; Rui H.; Song K. C.; Dávila-Contreras E. M.; Qi Y.; Lee J.; Monje-Galvan V.; Venable R. M.; Klauda J. B.; Im W. CHARMM-GUI membrane builder toward realistic biological membrane simulations. J. Comput. Chem. 2014, 35, 1997–2004. 10.1002/jcc.23702. PubMed DOI PMC

Lee J.; et al. CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field. J. Chem. Theory Comput. 2016, 12, 405–413. 10.1021/acs.jctc.5b00935. PubMed DOI PMC

Klauda J. B.; Venable R. M.; Freites J. A.; O’Connor J. W.; Tobias D. J.; Mondragon-Ramirez C.; Vorobyov I.; MacKerell A. D.; Pastor R. W. Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types. J. Phys. Chem. B 2010, 114, 7830–7843. 10.1021/jp101759q. PubMed DOI PMC

Venable R. M.; Luo Y.; Gawrisch K.; Roux B.; Pastor R. W. Simulations of anionic lipid membranes: Development of interaction-specific ion parameters and validation using NMR data. J. Phys. Chem. B 2013, 117, 10183–10192. 10.1021/jp401512z. PubMed DOI PMC

Marrink S. J.; Risselada H. J.; Yefimov S.; Tieleman D. P.; De Vries A. H. The MARTINI force field: Coarse grained model for biomolecular simulations. J. Phys. Chem. B 2007, 111, 7812–7824. 10.1021/jp071097f. PubMed DOI

Souza P. C.; et al. Martini 3: a general purpose force field for coarse-grained molecular dynamics. Nat. Methods 2021, 18, 382–388. 10.1038/s41592-021-01098-3. PubMed DOI

Yesylevskyy S. O.; Schäfer L. V.; Sengupta D.; Marrink S. J. Polarizable water model for the coarse-grained MARTINI force field. PLoS Comput. Biol. 2010, 6, e100081010.1371/journal.pcbi.1000810. PubMed DOI PMC

Jorgensen W. L.; Chandrasekhar J.; Madura J. D.; Impey R. W.; Klein M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 1983, 79, 926–935. 10.1063/1.445869. DOI

Durell S. R.; Brooks B. R.; Ben-Naim A. Solvent-induced forces between two hydrophilic groups. J. Phys. Chem. 1994, 98, 2198–2202. 10.1021/j100059a038. DOI

Páll S.; Hess B. A flexible algorithm for calculating pair interactions on SIMD architectures. Comput. Phys. Commun. 2013, 184, 2641–2650. 10.1016/j.cpc.2013.06.003. DOI

Darden T.; York D.; Pedersen L. Particle mesh Ewald: An N·log(N) method for Ewald sums in large systems. J. Chem. Phys. 1993, 98, 10089–10092. 10.1063/1.464397. DOI

Essmann U.; Perera L.; Berkowitz M. L.; Darden T.; Lee H.; Pedersen L. G. A smooth particle mesh Ewald method. J. Chem. Phys. 1995, 103, 8577–8593. 10.1063/1.470117. DOI

Shirts M. R.; Mobley D. L.; Chodera J. D.; Pande V. S. Accurate and efficient corrections for missing dispersion interactions in molecular simulations. J. Phys. Chem. B 2007, 111, 13052–13063. 10.1021/jp0735987. PubMed DOI

Nosé S. A molecular dynamics method for simulations in the canonical ensemble. Mol. Phys. 1984, 52, 255–268. 10.1080/00268978400101201. DOI

Hoover W. G. Canonical dynamics: Equilibrium phase-space distributions. Phys. Rev. A 1985, 31, 1695–1697. 10.1103/PhysRevA.31.1695. PubMed DOI

Bussi G.; Donadio D.; Parrinello M. Canonical sampling through velocity rescaling. J. Chem. Phys. 2007, 126, 01410110.1063/1.2408420. PubMed DOI

Berendsen H. J.; Postma J. P.; Van Gunsteren W. F.; Dinola A.; Haak J. R. Molecular dynamics with coupling to an external bath. J. Chem. Phys. 1984, 81, 3684–3690. 10.1063/1.448118. DOI

Parrinello M.; Rahman A. Polymorphic transitions in single crystals: A new molecular dynamics method. J. Appl. Phys. 1981, 52, 7182–7190. 10.1063/1.328693. DOI

Bauer D. danijoo/WHAM: Bugfixes, 2021. https://zenodo.org/record/1488597.

Grossfield A. WHAM: the weighted histogram method. http://membrane.urmc.rochester.edu/wordpress/?page_id=126.

Berger O.; Edholm O.; Jähnig F. Molecular dynamics simulations of a fluid bilayer of dipalmitoylphosphatidylcholine at full hydration, constant pressure, and constant temperature. Biophys. J. 1997, 72, 2002–2013. 10.1016/S0006-3495(97)78845-3. PubMed DOI PMC

Dickson C. J.; Madej B. D.; Skjevik Å. A.; Betz R. M.; Teigen K.; Gould I. R.; Walker R. C. Lipid14: The amber lipid force field. J. Chem. Theory Comput. 2014, 10, 865–879. 10.1021/ct4010307. PubMed DOI PMC

Jämbeck J. P.; Lyubartsev A. P. An extension and further validation of an all-atomistic force field for biological membranes. J. Chem. Theory Comput. 2012, 8, 2938–2948. 10.1021/ct300342n. PubMed DOI

Jämbeck J. P.; Lyubartsev A. P. Derivation and systematic validation of a refined all-atom force field for phosphatidylcholine lipids. J. Phys. Chem. B 2012, 116, 3164–3179. 10.1021/jp212503e. PubMed DOI PMC

Jämbeck J. P.; Lyubartsev A. P. Another piece of the membrane puzzle: Extending slipids further. J. Chem. Theory Comput. 2013, 9, 774–784. 10.1021/ct300777p. PubMed DOI

Grote F.; Lyubartsev A. P. Optimization of Slipids Force Field Parameters Describing Headgroups of Phospholipids. J. Phys. Chem. B 2020, 124, 8784–8793. 10.1021/acs.jpcb.0c06386. PubMed DOI PMC

Michaud-Agrawal N.; Denning E. J.; Woolf T. B.; Beckstein O. MDAnalysis: A toolkit for the analysis of molecular dynamics simulations. J. Comput. Chem. 2011, 32, 2319–2327. 10.1002/jcc.21787. PubMed DOI PMC

Starke L. J.; Allolio C.; Hub J. S. Pore formation in complex biological membranes: torn between evolutionary needs. bioRxiv 2024, 10.1101/2024.05.06.592649. DOI

Hub J. S.; De Groot B. L.; Van Der Spoel D. G-whams-a free Weighted Histogram Analysis implementation including robust error and autocorrelation estimates. J. Chem. Theory Comput. 2010, 6, 3713–3720. 10.1021/ct100494z. DOI

Nencini R.; Tempra C.; Biriukov D.; Riopedre-Fernandez M.; Chamorro V. C.; Polák J.; Mason P. E.; Ondo D.; Heyda J.; Ollila O. H. S.; Jungwirth P.; Javanainen M.; Martinez-Seara H. Effective Inclusion of Electronic Polarization Improves the Description of Electrostatic Interactions: The prosECCo75 Biomolecular Force Field. J. Chem. Theory Comput. 2024, 20, 7546–7559. 10.1021/acs.jctc.4c00743. PubMed DOI PMC

Lira R. B.; Leomil F. S.; Melo R. J.; Riske K. A.; Dimova R. To Close or to Collapse: The Role of Charges on Membrane Stability upon Pore Formation. Adv. Sci. 2021, 8, 200406810.1002/advs.202004068. PubMed DOI PMC

Åqvist J. Ion-water interaction potentials derived from free energy perturbation simulations. J. Phys. Chem. 1990, 94, 8021–8024. 10.1021/j100384a009. DOI

Smith D. E.; Dang L. X. Computer simulations of NaCl association in polarizable water. J. Chem. Phys. 1994, 100, 3757–3766. 10.1063/1.466363. DOI

Wang Z. J.; Frenkel D. Pore nucleation in mechanically stretched bilayer membranes. J. Chem. Phys. 2005, 123, 154701.10.1063/1.2060666. PubMed DOI

Shinoda W.; Nakamura T.; Nielsen S. O. Free energy analysis of vesicle-to-bicelle transformation. Soft Matter 2011, 7, 9012–9020. 10.1039/c1sm05404j. DOI

Kabelka I.; Vácha R. Optimal conditions for opening of membrane pore by amphiphilic peptides. J. Chem. Phys. 2015, 143, 243115.10.1063/1.4933229. PubMed DOI

Bennett W. F.; Sapay N.; Tieleman D. P. Atomistic simulations of pore formation and closure in lipid bilayers. Biophys. J. 2014, 106, 210–219. 10.1016/j.bpj.2013.11.4486. PubMed DOI PMC

Akimov S. A.; Volynsky P. E.; Galimzyanov T. R.; Kuzmin P. I.; Pavlov K. V.; Batishchev O. V. Pore formation in lipid membrane I: Continuous reversible trajectory from intact bilayer through hydrophobic defect to transversal pore. Sci. Rep. 2017, 7, 12152.10.1038/s41598-017-12127-7. PubMed DOI PMC

Srividya N.; Muralidharan S. Determination of the line tension of giant vesicles from pore-closing dynamics. J. Phys. Chem. B 2008, 112, 7147–7152. 10.1021/jp7119203. PubMed DOI

Antila H. S.; Ferreira T. M.; Ollila O. H.; Miettinen M. S. Using Open Data to Rapidly Benchmark Biomolecular Simulations: Phospholipid Conformational Dynamics. J. Chem. Inf. Model. 2021, 61, 938–949. 10.1021/acs.jcim.0c01299. PubMed DOI PMC

Kiirikki A. M.; et al. Overlay databank unlocks data-driven analyses of biomolecules for all. Nat. Commun. 2024, 15, 1136.10.1038/s41467-024-45189-z. PubMed DOI PMC

Richardson J. D.; Van Lehn R. C. Free Energy Analysis of Peptide-Induced Pore Formation in Lipid Membranes by Bridging Atomistic and Coarse-Grained Simulations. J. Phys. Chem. B 2024, 36, 8737–8752. 10.1021/acs.jpcb.4c03276. PubMed DOI

Levadny V.; Tsuboi T. A.; Belaya M.; Yamazaki M. Rate constant of tension-induced pore formation in lipid membranes. Langmuir 2013, 29, 3848–3852. 10.1021/la304662p. PubMed DOI

Karal M. A. S.; Billah M. M.; Ahamed M. K. Determination of pore edge tension from the kinetics of rupture of giant unilamellar vesicles using the Arrhenius equation: effects of sugar concentration, surface charge and cholesterol. Phys. Chem. Chem. Phys. 2024, 26, 6107–6117. 10.1039/D3CP04451C. PubMed DOI

Kramar P.; Miklavčič D.; Lebar A. M. A system for the determination of planar lipid bilayer breakdown voltage and its applications. IEEE Trans. Nanobioscience 2009, 8, 132–138. 10.1109/TNB.2009.2022834. PubMed DOI

Lebar A. M.; Miklavčič D.; Kotulska M.; Kramar P. Water pores in planar lipid bilayers at fast and slow rise of transmembrane voltage. Membranes 2021, 11, 263.10.3390/membranes11040263. PubMed DOI PMC

Catte A.; Girych M.; Javanainen M.; Loison C.; Melcr J.; Miettinen M. S.; Monticelli L.; Määttä J.; Oganesyan V. S.; Ollila O. H.; Tynkkynen J.; Vilov S. Molecular electrometer and binding of cations to phospholipid bilayers. Phys. Chem. Chem. Phys. 2016, 18, 32560–32569. 10.1039/C6CP04883H. PubMed DOI

Pajtinka P.; Vácha R. Amphipathic Helices Can Sense Both Positive and Negative Curvatures of Lipid Membranes. J. Phys. Chem. Lett. 2024, 15, 175–179. 10.1021/acs.jpclett.3c02785. PubMed DOI PMC

Mou Q.; Xu M.; Deng J.; Hu N.; Yang J. Studying the roles of salt ions in the pore initiation and closure stages in the biomembrane electroporation. APL Bioeng. 2023, 7, 02610310.1063/5.0147104. PubMed DOI PMC

Karal M. A. S.; Orchi U. S.; Towhiduzzaman M.; Ahamed M. K.; Ahmed M.; Ahammed S.; Mokta N. A.; Sharmin S.; Sarkar M. K. Electrostatic effects on the electrical tension-induced irreversible pore formation in giant unilamellar vesicles. Chem. Phys. Lipids 2020, 231, 10493510.1016/j.chemphyslip.2020.104935. PubMed DOI

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