Mechanistic insights into interactions between ionizable lipid nanodroplets and biomembranes

References

• Abraham, M. J., Murtola, T., Schulz, R., Páll, S., Smith, J. C., Hess, B., & Lindahl, E. (2015). GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX, 1-2, 19–25. https://doi.org/10.1016/j.softx.2015.06.001
   Google Scholar
• Anderson, E., Bai, Z., Bischof, C., Blackford, S., Demmel, J., Dongarra, J., Du Croz, J., Greenbaum, A., Hammarling, S., McKenney, A., & Sorensen, D. (1999). LAPACK Users’ Guide. (3rd ed.). Society for Industrial and Applied Mathematics.
   Google Scholar
• Beg, M., Taka, J., Kluyver, T., Konovalov, A., Ragan-Kelley, M., Thiery, N. M., & Fangohr, H. (2021). Using Jupyter for reproducible scientific workflows. Computing in Science & Engineering, 23(2), 36–46. https://doi.org/10.1109/MCSE.2021.3052101
   Web of Science ®Google Scholar
• Berendsen, H. J. C., Postma, J. P. M., Van Gunsteren, W. F., DiNola, A., & Haak, J. R. (1984). Molecular dynamics with coupling to an external bath. The Journal of Chemical Physics, 81(8), 3684–3690. https://doi.org/10.1063/1.448118
   Web of Science ®Google Scholar
• Berendsen, H. J. C., Van Der Spoel, D., & Van Drunen, R. (1995). GROMACS: A message-passing parallel molecular dynamics implementation. Computer Physics Communications, 91(1-3), 43–56. https://doi.org/10.1016/0010-4655(95)00042-E
   Web of Science ®Google Scholar
• Brader, M. L., Williams, S. J., Banks, J. M., Hui, W. H., Zhou, Z. H., & Jin, L. (2021). Encapsulation state of messenger RNA inside lipid nanoparticles. Biophysical Journal, 120S0006349521002411. (14), 2766–2770. https://doi.org/10.1016/j.bpj.2021.03.012
   PubMed Web of Science ®Google Scholar
• Bruininks, B. M., Souza, P. C., Ingolfsson, H., & Marrink, S. J. (2020). A molecular view on the escape of lipoplexed DNA from the endosome. eLife, 9, e52012. https://doi.org/10.7554/eLife.52012
   PubMed Web of Science ®Google Scholar
• Carrasco, M. J., Alishetty, S., Alameh, M.-G., Said, H., Wright, L., Paige, M., Soliman, O., Weissman, D., Cleveland, T. E., Grishaev, A., & Buschmann, M. D. (2021). Ionization and structural properties of mRNA lipid nanoparticles influence expression in intramuscular and intravascular administration. Communications Biology, 4(1), 956. https://doi.org/10.1038/s42003-021-02441-2
   PubMed Web of Science ®Google Scholar
• Chapman, B., & Chang, J. (2000). Biopython: Python tools for computational biology. ACM SIGBIO Newsletter, 20(2), 15–19. https://doi.org/10.1145/360262.360268
   Google Scholar
• Chen, J., Zhou, G., Chen, L., Wang, Y., Wang, X., & Zeng, S. (2016). Interaction of graphene and its oxide with lipid membrane: A molecular dynamics simulation study. The Journal of Physical Chemistry C, 120(11), 6225–6231. https://doi.org/10.1021/acs.jpcc.5b10635
   Web of Science ®Google Scholar
• Cheng, M. H. Y., Brimacombe, C. A., Verbeke, R., & Cullis, P. R. (2022). Exciting times for lipid nanoparticles: How Canadian discoveries are enabling gene therapies. Molecular Pharmaceutics, 19(6), 1663–1668. https://doi.org/10.1021/acs.molpharmaceut.2c00365
   PubMed Web of Science ®Google Scholar
• Cock, P. J. A., Antao, T., Chang, J. T., Chapman, B. A., Cox, C. J., Dalke, A., Friedberg, I., Hamelryck, T., Kauff, F., Wilczynski, B., & De Hoon, M. J. L. (2009). Biopython: Freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics (Oxford, England), 25(11), 1422–1423. https://doi.org/10.1093/bioinformatics/btp163
   PubMed Web of Science ®Google Scholar
• COVID-19 vaccine doses administered by manufacturer. (n.d.). Retrieved October 5, 2023 https://ourworldindata.org/grapher/covid-vaccine-doses-by-manufacturer?country=European+Union∼USA
   Google Scholar
• Dehghani-Ghahnaviyeh, S., Smith, M., Xia, Y., Dousis, A., Grossfield, A., & Sur, S. (2023). Ionizable amino lipids distribution and effects on DSPC/cholesterol membranes: Implications for lipid nanoparticle structure. The Journal of Physical Chemistry. B, 127(31), 6928–6939. https://doi.org/10.1021/acs.jpcb.3c01296
   PubMed Web of Science ®Google Scholar
• Ding, W., Palaiokostas, M., Wang, W., & Orsi, M. (2015). Effects of lipid composition on bilayer membranes quantified by all-atom molecular dynamics. The Journal of Physical Chemistry. B, 119(49), 15263–15274. https://doi.org/10.1021/acs.jpcb.5b06604
   PubMed Web of Science ®Google Scholar
• Doktorova, M., Symons, J. L., & Levental, I. (2020). Structural and functional consequences of reversible lipid asymmetry in living membranes. Nature Chemical Biology, 16(12), 1321–1330. https://doi.org/10.1038/s41589-020-00688-0
   PubMed Web of Science ®Google Scholar
• Ermilova, I., & Swenson, J. (2020). DOPC versus DOPE as a helper lipid for gene-therapies: Molecular dynamics simulations with DLin-MC3-DMA. Physical Chemistry Chemical Physics: PCCP, 22(48), 28256–28268. https://doi.org/10.1039/D0CP05111J
   PubMed Web of Science ®Google Scholar
• Essmann, U., Perera, L., Berkowitz, M. L., Darden, T., Lee, H., & Pedersen, L. G. (1995). A smooth particle mesh Ewald method. The Journal of Chemical Physics, 103(19), 8577–8593. https://doi.org/10.1063/1.470117
   Web of Science ®Google Scholar
• Eygeris, Y., Gupta, M., Kim, J., & Sahay, G. (2022). Chemistry of lipid nanoparticles for RNA delivery. Accounts of Chemical Research, 55(1), 2–12. https://doi.org/10.1021/acs.accounts.1c00544
   PubMed Web of Science ®Google Scholar
• Gould, I. R., Skjevik, Å. A., Dickson, C. J., Madej, B. D., & Walker, R. C. (2018). Lipid17: A comprehensive AMBER force field for the simulation of zwitterionic and anionic lipids.
   Google Scholar
• Gowers, R., Linke, M., Barnoud, J., Reddy, T., Melo, M., Seyler, S., Domański, J., Dotson, D., Buchoux, S., Kenney, I., & Beckstein, O. (2016). MDAnalysis: A Python package for the rapid analysis of molecular dynamics simulations. 98–105. https://doi.org/10.25080/Majora-629e541a-00e
   Google Scholar
• Hamelryck, T., & Manderick, B. (2003). PDB file parser and structure class implemented in Python. Bioinformatics (Oxford, England), 19(17), 2308–2310. https://doi.org/10.1093/bioinformatics/btg299
   PubMed Web of Science ®Google Scholar
• Harayama, T., & Riezman, H. (2018). Understanding the diversity of membrane lipid composition. Nature Reviews. Molecular Cell Biology, 19(5), 281–296. https://doi.org/10.1038/nrm.2017.138
   PubMed Web of Science ®Google Scholar
• Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., Del Río, J. F., Wiebe, M., Peterson, P., … Oliphant, T. E. (2020). Array programming with NumPy. Nature, 585(7825), 357–362. https://doi.org/10.1038/s41586-020-2649-2
   PubMed Web of Science ®Google Scholar
• Hess, B. (2008). P-LINCS: A parallel linear constraint solver for molecular simulation. Journal of Chemical Theory and Computation, 4(1), 116–122. https://doi.org/10.1021/ct700200b
   PubMed Web of Science ®Google Scholar
• Hess, B., Kutzner, C., Van Der Spoel, D., & Lindahl, E. (2008). GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation. Journal of Chemical Theory and Computation, 4(3), 435–447. https://doi.org/10.1021/ct700301q
   PubMed Web of Science ®Google Scholar
• Hoover, W. G. (1985). Canonical dynamics: Equilibrium phase-space distributions. Physical Review. A, General Physics, 31(3), 1695–1697. https://doi.org/10.1103/PhysRevA.31.1695
   PubMedGoogle Scholar
• Hou, X., Zaks, T., Langer, R., & Dong, Y. (2021). Lipid nanoparticles for mRNA delivery. Nature Reviews. Materials, 6(12), 1078–1094. https://doi.org/10.1038/s41578-021-00358-0
   PubMed Web of Science ®Google Scholar
• Hub, J. S., De Groot, B. L., & Van Der Spoel, D. (2010). g_wham—A free weighted histogram analysis implementation including robust error and autocorrelation estimates. Journal of Chemical Theory and Computation, 6(12), 3713–3720. https://doi.org/10.1021/ct100494z
   Web of Science ®Google Scholar
• Humphrey, W., Dalke, A., & Schulten, K. (1996). VMD: Visual molecular dynamics. Journal of Molecular Graphics, 14(1), 33–38. https://doi.org/10.1016/0263-7855(96)00018-5
   PubMedGoogle Scholar
• Hunter, J. D. (2007). Matplotlib: A 2D graphics environment. Computing in Science & Engineering, 9(3), 90–95. https://doi.org/10.1109/MCSE.2007.55
   Web of Science ®Google Scholar
• Izadi, S., Anandakrishnan, R., & Onufriev, A. V. (2014). Building water models: A different approach. The Journal of Physical Chemistry Letters, 5(21), 3863–3871. https://doi.org/10.1021/jz501780a
   PubMed Web of Science ®Google Scholar
• Jayaraman, M., Ansell, S. M., Mui, B. L., Tam, Y. K., Chen, J., Du, X., Butler, D., Eltepu, L., Matsuda, S., Narayanannair, J. K., Rajeev, K. G., Hafez, I. M., Akinc, A., Maier, M. A., Tracy, M. A., Cullis, P. R., Madden, T. D., Manoharan, M., & Hope, M. J. (2012). Maximizing the potency of siRNA lipid nanoparticles for hepatic gene silencing in vivo. Angewandte Chemie (International ed. in English), 51(34), 8529–8533. https://doi.org/10.1002/anie.201203263
   PubMed Web of Science ®Google Scholar
• Jo, S., Kim, T., & Im, W. (2007). Automated builder and database of protein/membrane complexes for molecular dynamics simulations. PLoS One, 2(9), e880. https://doi.org/10.1371/journal.pone.0000880
   PubMed Web of Science ®Google Scholar
• Jo, S., Kim, T., Iyer, V. G., & Im, W. (2008). CHARMM-GUI: A web-based graphical user interface for CHARMM. Journal of Computational Chemistry, 29(11), 1859–1865. https://doi.org/10.1002/jcc.20945
   PubMed Web of Science ®Google Scholar
• Jo, S., Lim, J. B., Klauda, J. B., & Im, W. (2009). CHARMM-GUI membrane builder for mixed bilayers and its application to yeast membranes. Biophysical Journal, 97(1), 50–58. https://doi.org/10.1016/j.bpj.2009.04.013
   PubMed Web of Science ®Google Scholar
• Joung, I. S., & Cheatham, T. E. (2008). Determination of alkali and halide monovalent ion parameters for use in explicitly solvated biomolecular simulations. The Journal of Physical Chemistry. B, 112(30), 9020–9041. https://doi.org/10.1021/jp8001614
   PubMed Web of Science ®Google Scholar
• Kaasgaard, T., & Drummond, C. J. (2006). Ordered 2-D and 3-D nanostructured amphiphile self-assembly materials stable in excess solvent. Physical Chemistry Chemical Physics: PCCP, 8(43), 4957–4975. https://doi.org/10.1039/b609510k
   PubMed Web of Science ®Google Scholar
• Kulkarni, J. A., Darjuan, M. M., Mercer, J. E., Chen, S., van der Meel, R., Thewalt, J. L., Tam, Y. Y. C., & Cullis, P. R. (2018). On the formation and morphology of lipid nanoparticles containing ionizable cationic lipids and siRNA. ACS Nano, 12(5), 4787–4795. https://doi.org/10.1021/acsnano.8b01516
   PubMed Web of Science ®Google Scholar
• Kumar, S., Rosenberg, J. M., Bouzida, D., Swendsen, R. H., & Kollman, P. A. (1992). The weighted histogram analysis method for free-energy calculations on biomolecules. I. The method. Journal of Computational Chemistry, 13(8), 1011–1021. https://doi.org/10.1002/jcc.540130812
   Web of Science ®Google Scholar
• Kumari, P., Pillai, V. V. S., & Benedetto, A. (2020). Mechanisms of action of ionic liquids on living cells: The state of the art. Biophysical Reviews, 12(5), 1187–1215. https://doi.org/10.1007/s12551-020-00754-w
   PubMedGoogle Scholar
• Lazaratos, M., Karathanou, K., Mainas, E., Chatzigoulas, A., Pippa, N., Demetzos, C., & Cournia, Z. (2020). Coating of magnetic nanoparticles affects their interactions with model cell membranes. Biochimica et Biophysica Acta. General Subjects, 1864(11), 129671. https://doi.org/10.1016/j.bbagen.2020.129671
   PubMed Web of Science ®Google Scholar
• Lee, J., Cheng, X., Swails, J. M., Yeom, M. S., Eastman, P. K., Lemkul, J. A., Wei, S., Buckner, J., Jeong, J. C., Qi, Y., Jo, S., Pande, V. S., Case, D. A., Brooks, C. L., MacKerell, A. D., Klauda, J. B., & Im, W. (2016). CHARMM-GUI input generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM simulations using the CHARMM36 additive force field. Journal of Chemical Theory and Computation, 12(1), 405–413. https://doi.org/10.1021/acs.jctc.5b00935
   PubMed Web of Science ®Google Scholar
• Lee, J., Hitzenberger, M., Rieger, M., Kern, N. R., Zacharias, M., & Im, W. (2020). CHARMM-GUI supports the Amber force fields. The Journal of Chemical Physics, 153(3), 035103. https://doi.org/10.1063/5.0012280
   PubMed Web of Science ®Google Scholar
• Lee, J., Patel, D. S., Ståhle, J., Park, S.-J., Kern, N. R., Kim, S., Lee, J., Cheng, X., Valvano, M. A., Holst, O., Knirel, Y. A., Qi, Y., Jo, S., Klauda, J. B., Widmalm, G., & Im, W. (2019). CHARMM-GUI membrane builder for complex biological membrane simulations with glycolipids and lipoglycans. Journal of Chemical Theory and Computation, 15(1), 775–786. https://doi.org/10.1021/acs.jctc.8b01066
   PubMed Web of Science ®Google Scholar
• Leikin, S. L., Kozlov, M. M., Chernomordik, L. V., Markin, V. S., & Chizmadzhev, Y. A. (1987). Membrane fusion: Overcoming of the hydration barrier and local restructuring. Journal of Theoretical Biology, 129(4), 411–425. https://doi.org/10.1016/S0022-5193(87)80021-8
   PubMed Web of Science ®Google Scholar
• Leung, A. K. K., Hafez, I. M., Baoukina, S., Belliveau, N. M., Zhigaltsev, I. V., Afshinmanesh, E., Tieleman, D. P., Hansen, C. L., Hope, M. J., & Cullis, P. R. (2012). Lipid nanoparticles containing siRNA synthesized by microfluidic mixing exhibit an electron-dense nanostructured core. The Journal of Physical Chemistry. C, Nanomaterials and Interfaces, 116(34), 18440–18450. https://doi.org/10.1021/jp303267y
   PubMed Web of Science ®Google Scholar
• Lindahl, E., Hess, B., & Van Der Spoel, D. (2001). GROMACS 3.0: A package for molecular simulation and trajectory analysis. Journal of Molecular Modeling, 7(8), 306–317. https://doi.org/10.1007/s008940100045
   Web of Science ®Google Scholar
• Lorent, J. H., Levental, K. R., Ganesan, L., Rivera-Longsworth, G., Sezgin, E., Doktorova, M., Lyman, E., & Levental, I. (2020). Plasma membranes are asymmetric in lipid unsaturation, packing and protein shape. Nature Chemical Biology, 16(6), 644–652. https://doi.org/10.1038/s41589-020-0529-6
   PubMed Web of Science ®Google Scholar
• Malburet, C., Leclercq, L., Cotte, J.-F., Thiebaud, J., Bazin, E., Garinot, M., & Cottet, H. (2022). Size and charge characterization of lipid nanoparticles for mRNA vaccines. Analytical Chemistry, 94(11), 4677–4685. https://doi.org/10.1021/acs.analchem.1c04778
   PubMed Web of Science ®Google Scholar
• Marrink, S.-J., & Mark, A. E. (2004). Molecular view of hexagonal phase formation in phospholipid membranes. Biophysical Journal, 87(6), 3894–3900. https://doi.org/10.1529/biophysj.104.048710
   PubMed Web of Science ®Google Scholar
• Marrink, S.-J., & Tieleman, D. P. (2002). Molecular dynamics simulation of spontaneous membrane fusion during a cubic-hexagonal phase transition. Biophysical Journal, 83(5), 2386–2392. https://doi.org/10.1016/S0006-3495(02)75252-1
   PubMed Web of Science ®Google Scholar
• Mathieu, E., Ritchie, H., Ortiz-Ospina, E., Roser, M., Hasell, J., Appel, C., Giattino, C., & Rodés-Guirao, L. (2021). A global database of COVID-19 vaccinations. Nature Human Behaviour, 5(7), 947–953. https://doi.org/10.1038/s41562-021-01122-8
   PubMed Web of Science ®Google Scholar
• Michaud-Agrawal, N., Denning, E. J., Woolf, T. B., & Beckstein, O. (2011). MDAnalysis: A toolkit for the analysis of molecular dynamics simulations. Journal of Computational Chemistry, 32(10), 2319–2327. https://doi.org/10.1002/jcc.21787
   PubMed Web of Science ®Google Scholar
• Nosé, S., & Klein, M. L. (1983). Constant pressure molecular dynamics for molecular systems. Molecular Physics, 50(5), 1055–1076. https://doi.org/10.1080/00268978300102851
   Web of Science ®Google Scholar
• Páll, S., Abraham, M. J., Kutzner, C., Hess, B., & Lindahl, E. (2015). Tackling exascale software challenges in molecular dynamics simulations with GROMACS. In S. Markidis & E. Laure (Eds.), Solving software challenges for exascale (Vol. 8759, pp. 3–27). Springer International Publishing. https://doi.org/10.1007/978-3-319-15976-8_1
   Google Scholar
• Paloncýová, M., Čechová, P., Šrejber, M., Kührová, P., & Otyepka, M. (2021). Role of ionizable lipids in SARS-CoV-2 vaccines as revealed by molecular dynamics simulations: From membrane structure to interaction with mRNA fragments. The Journal of Physical Chemistry Letters, 12(45), 11199–11205. https://doi.org/10.1021/acs.jpclett.1c03109
   PubMed Web of Science ®Google Scholar
• Paloncýová, M., Fabre, G., DeVane, R. H., Trouillas, P., Berka, K., & Otyepka, M. (2014). Benchmarking of force fields for molecule–membrane interactions. Journal of Chemical Theory and Computation, 10(9), 4143–4151. https://doi.org/10.1021/ct500419b
   PubMed Web of Science ®Google Scholar
• Paloncýová, M., Šrejber, M., Čechová, P., Kührová, P., Zaoral, F., & Otyepka, M. (2023). Atomistic insights into organization of RNA-loaded lipid nanoparticles. The Journal of Physical Chemistry. B, 127(5), 1158–1166. https://doi.org/10.1021/acs.jpcb.2c07671
   PubMedGoogle Scholar
• Parrinello, M., & Rahman, A. (1981). Polymorphic transitions in single crystals: A new molecular dynamics method. Journal of Applied Physics, 52(12), 7182–7190. https://doi.org/10.1063/1.328693
   Web of Science ®Google Scholar
• Patel, P., Ibrahim, N. M., & Cheng, K. (2021). The importance of apparent pKa in the development of nanoparticles encapsulating siRNA and mRNA. Trends in Pharmacological Sciences, 42(6), 448–460. https://doi.org/10.1016/j.tips.2021.03.002
   PubMed Web of Science ®Google Scholar
• Patel, S., Kim, J., Herrera, M., Mukherjee, A., Kabanov, A. V., & Sahay, G. (2019). Brief update on endocytosis of nanomedicines. Advanced Drug Delivery Reviews, 144, 90–111. https://doi.org/10.1016/j.addr.2019.08.004
   PubMed Web of Science ®Google Scholar
• Pronk, S., Páll, S., Schulz, R., Larsson, P., Bjelkmar, P., Apostolov, R., Shirts, M. R., Smith, J. C., Kasson, P. M., van der Spoel, D., Hess, B., & Lindahl, E. (2013). GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics (Oxford, England), 29(7), 845–854. https://doi.org/10.1093/bioinformatics/btt055
   PubMed Web of Science ®Google Scholar
• Ramasubramani, V., Dice, B. D., Harper, E. S., Spellings, M. P., Anderson, J. A., & Glotzer, S. C. (2020). freud: A software suite for high throughput analysis of particle simulation data. Computer Physics Communications, 254, 107275. https://doi.org/10.1016/j.cpc.2020.107275
   Web of Science ®Google Scholar
• Ramezanpour, M., Schmidt, M. L., Bashe, B. Y. M., Pruim, J. R., Link, M. L., Cullis, P. R., Harper, P. E., Thewalt, J. L., & Tieleman, D. P. (2020). Structural properties of inverted hexagonal phase: A hybrid computational and experimental approach. Langmuir: The ACS Journal of Surfaces and Colloids, 36(24), 6668–6680. https://doi.org/10.1021/acs.langmuir.0c00600
   PubMed Web of Science ®Google Scholar
• Ramezanpour, M., Schmidt, M. L., Bodnariuc, I., Kulkarni, J. A., Leung, S. S. W., Cullis, P. R., Thewalt, J. L., & Tieleman, D. P. (2019). Ionizable amino lipid interactions with POPC: Implications for lipid nanoparticle function. Nanoscale, 11(30), 14141–14146. https://doi.org/10.1039/C9NR02297J
   PubMed Web of Science ®Google Scholar
• Sandoval-Perez, A., Pluhackova, K., & Böckmann, R. A. (2017). Critical comparison of biomembrane force fields: Protein–lipid interactions at the membrane interface. Journal of Chemical Theory and Computation, 13(5), 2310–2321. https://doi.org/10.1021/acs.jctc.7b00001
   PubMed Web of Science ®Google Scholar
• Schneck, E., Sedlmeier, F., & Netz, R. R. (2012). Hydration repulsion between biomembranes results from an interplay of dehydration and depolarization. Proceedings of the National Academy of Sciences of the United States of America, 109(36), 14405–14409. https://doi.org/10.1073/pnas.1205811109
   PubMed Web of Science ®Google Scholar
• Schrödinger, LLC. (2015). The PyMOL Molecular Graphics System, Version 2.5.
   Google Scholar
• Semple, S. C., Akinc, A., Chen, J., Sandhu, A. P., Mui, B. L., Cho, C. K., Sah, D. W. Y., Stebbing, D., Crosley, E. J., Yaworski, E., Hafez, I. M., Dorkin, J. R., Qin, J., Lam, K., Rajeev, K. G., Wong, K. F., Jeffs, L. B., Nechev, L., Eisenhardt, M. L., … Hope, M. J. (2010). Rational design of cationic lipids for siRNA delivery. Nature Biotechnology, 28(2), 172–176. https://doi.org/10.1038/nbt.1602
   PubMed Web of Science ®Google Scholar
• Shepherd, S. J., Han, X., Mukalel, A. J., El-Mayta, R., Thatte, A. S., Wu, J., Padilla, M. S., Alameh, M.-G., Srikumar, N., Lee, D., Weissman, D., Issadore, D., & Mitchell, M. J. (2023). Throughput-scalable manufacturing of SARS-CoV-2 mRNA lipid nanoparticle vaccines. Proceedings of the National Academy of Sciences of the United States of America, 120(33), e2303567120. https://doi.org/10.1073/pnas.2303567120
   PubMed Web of Science ®Google Scholar
• Shin, H., Park, S.-J., Yim, Y., Kim, J., Choi, C., Won, C., & Min, D.-H. (2018). Recent advances in RNA therapeutics and RNA delivery systems based on nanoparticles. Advanced Therapeutics, 1(7), 1800065. https://doi.org/10.1002/adtp.201800065
   Google Scholar
• Smith, P., & Lorenz, C. D. (2021). LiPyphilic: A Python toolkit for the analysis of lipid membrane simulations. Journal of Chemical Theory and Computation, 17(9), 5907–5919. https://doi.org/10.1021/acs.jctc.1c00447
   PubMed Web of Science ®Google Scholar
• Torres-Sánchez, A., Vanegas, J. M., & Arroyo, M. (2015). Examining the mechanical equilibrium of microscopic stresses in molecular simulations. Physical Review Letters, 114(25), 258102. https://doi.org/10.1103/PhysRevLett.114.258102
   PubMed Web of Science ®Google Scholar
• Torres-Sánchez, A., Vanegas, J. M., & Arroyo, M. (2016). Geometric derivation of the microscopic stress: A covariant central force decomposition. Journal of the Mechanics and Physics of Solids, 93, 224–239. https://doi.org/10.1016/j.jmps.2016.03.006
   Web of Science ®Google Scholar
• Trollmann, M. F. W., & Böckmann, R. A. (2022). mRNA lipid nanoparticle phase transition. Biophysical Journal, 121(20), 3927–3939. https://doi.org/10.1016/j.bpj.2022.08.037
   PubMed Web of Science ®Google Scholar
• Van Der Spoel, D., Lindahl, E., Hess, B., Groenhof, G., Mark, A. E., & Berendsen, H. J. C. (2005). GROMACS: Fast, flexible, and free. Journal of Computational Chemistry, 26(16), 1701–1718. https://doi.org/10.1002/jcc.20291
   PubMed Web of Science ®Google Scholar
• Vanegas, J. M., & Arroyo, M. (2014). Force transduction and lipid binding in MscL: A continuum-molecular approach. PloS One, 9(12), e113947. https://doi.org/10.1371/journal.pone.0113947
   PubMed Web of Science ®Google Scholar
• Vanegas, J. M., Torres-Sánchez, A., & Arroyo, M. (2014). Importance of force decomposition for local stress calculations in biomembrane molecular simulations. Journal of Chemical Theory and Computation, 10(2), 691–702. https://doi.org/10.1021/ct4008926
   PubMed Web of Science ®Google Scholar
• Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., … van Mulbregt, P. (2020). SciPy 1.0: Fundamental algorithms for scientific computing in Python. Nature Methods, 17(3), 261–272. https://doi.org/10.1038/s41592-019-0686-2
   PubMed Web of Science ®Google Scholar
• Wang, F., Zuroske, T., & Watts, J. K. (2020). RNA therapeutics on the rise. Nature Reviews. Drug Discovery, 19(7), 441–442. https://doi.org/10.1038/d41573-020-00078-0
   PubMed Web of Science ®Google Scholar
• Wang, J., Wolf, R. M., Caldwell, J. W., Kollman, P. A., & Case, D. A. (2004). Development and testing of a general amber force field. Journal of Computational Chemistry, 25(9), 1157–1174. https://doi.org/10.1002/jcc.20035
   PubMed Web of Science ®Google Scholar
• 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. (2014). CHARMM-GUI Membrane Builder toward realistic biological membrane simulations. Journal of Computational Chemistry, 35(27), 1997–2004. https://doi.org/10.1002/jcc.23702
   PubMed Web of Science ®Google Scholar