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Lipid Nanoparticles in Drug Delivery
Doctoral study program
Life Sciences (Faculty of Science, Masaryk University)
Research area
Computational biophysics
Supervisor
Annotation
With nearly 10 million lives claimed annually, cancer remains one of the leading causes of mortality worldwide, highlighting the urgent need for more effective treatments. One promising strategy involves mRNA-based cancer immunotherapy vaccines, which require a drug delivery system capable of reliably reaching the cytosol. Developing such delivery systems is challenging: they must ensure cytosolic delivery and therapeutic efficacy while maintaining safety, long-term stability, and compliance with scalable manufacturing standards—including high mRNA loading efficiency and uniform particle size. Current lipidand polymer-based systems offer distinct advantages but integrating lessons from both may help develop more effective next-generation carriers. A major limitation remains the incomplete understanding of nanoparticle assembly and disassembly under diverse physiological conditions (e.g., extracellular fluids, endosomal compartments, cytosol). This project will use coarse-grained molecular simulations, complemented by in-house experimental validation, to gain molecular insights in the controlled system assembly and disassembly. Our goal is to guide the rational design of improved mRNA delivery systems to advance the efficacy of cancer immunotherapy.
Recommended literature
- Paunovska K., et al.: Nat Rev Genet 2022, 23, 265–280, Doi: 10.1038/s41576-021-00439-4
- Hou X., et al.: Nat Rev Mater 2021, 6, 1078–1094, Doi: 10.1038/s41578-021-00358-0
- Yasuda I. et al.: J. Chem. Theory Comput. 2025, 21, 5, 2766–2779, Doi: 10.1021/acs.jctc.4c01646
- Chew P.Y., et al.: Chem. Sci., 2023,14, 1820-1836, Doi: 10.1039/D2SC05873A
Funding
National Institute of Virology and Bacteriology, ERC, GACR grants
Requirements on candidates
- Msc in computational biophysics/chemistry/physics and related fields
- Experience with Molecular Dynamics using coarse grained or atomistic models
- Advantage is experience with simulations of disordered proteins/polymers and membranes
- Excellent track record
- Good English language – spoken and written
- Motivated person with collaborative mind set
Keywords
Computer simulations, Coarse-grained model, Molecular dynamics, protein-protein interactions, protein-membrane interactions
Information on the supervisor
Current group:
7 postdocs, 5 PhD students,1 Master student, 3 technicians
Current projects are:
National Institute of Virology and Bacteriology, ERC consolidator grant, ERC proof of concept grant, Czech Science Foundation grant
In total 81 publications with more than 4500 citations (WoS) and H-index 36.
Recent publications:
Bartoš, L.; Lund, M.; Vácha, R.: Enhanced Diffusion through Multivalency. Soft Matter 2025, 21, 179-185,
Linhartova, K.; Falginella, F.L.; Matl, M.; Šebesta, M.; Vácha, R.; Štefl, R.: Sequence and structural determinants of RNAPII CTD phase-separation and phosphorylation by CDK7. Nature Communications 2024, 15, 9163
Hazrati, M.K.; Vácha, R.: Membrane Adsorption Enhances Translocation of Antimicrobial Peptide Buforin 2. The Journal of Physical Chemistry B 2024, 128, 35, 8469–847
Deb, R.; Torres, M.D.T.; Boudný, M.; Koběrská, M.; Cappiello, F.; Popper, M.; Dvořáková Bendová, K.; Drabinová, M.; Hanáčková, A.; Jeannot, K.; Petřík, M.; Mangoni, M.L.; Balíková Novotná, G.; Mráz, M.; de la Fuente-Nunez, C.; Vácha, R.: Computational Design of Pore-Forming Peptides with Potent Antimicrobial and Anticancer Activities. Journal of Medicinal Chemistry 2024, 67, 16, 14040–14061
Blasco S.; Sukeník, L.; Vácha, R.: Nanoparticle induced fusion of lipid membranes. Nanoscale 2024, 16, 10221-10229