A review article in the journal Molecular Pharmaceutics summarizes the computational methods currently used to study and design lipid-based drug carriers (LNCs). The article was co-authored by researchers from CATRIN at Palacký University, IT4Innovations at VSB-TUO and colleagues from French universities and Sanofi. The valuable insights gained from integrating experimental and theoretical approaches can contribute to improving the properties of lipid nanocarriers, thereby ensuring more effective and safer drug therapy.
Liposomes and lipid nanoparticles are used to transport drugs into cells. Thanks to computational methods, researchers can explore the structure of these nanoparticles and the individual steps involved in their transport.
“These insights are crucial for designing new and efficient therapeutics that enhance the effectiveness of drug delivery systems. Our review article examines how computational methods, particularly molecular dynamics simulations, can reveal complex relationships between the composition, structure and function of LNCs. Additionally, we present the potential of machine learning—data-driven learning—in the design of lipid carriers,” summarized the key contributions of the article its first author, Markéta Paloncýová from CATRIN.
The researchers also utilized the computing power of supercomputers at the IT4Innovations National Supercomputing Center. The study, which was conducted with the support of the TECHSCALE, MINIGRAPH and REFRESH projects, is accompanied by a supplementary cover art in the journal.
LNCs are nanoparticles composed of lipids used for delivering active pharmaceutical ingredients (APIs) in medicine. Their advantage lies in their ability to transport even water-insoluble substances, protect the body from certain adverse drug effects and safeguard fragile molecules such as nucleic acids or proteins. They enhance treatment effectiveness by enabling targeted drug delivery to specific locations in the body. In modern medicine, LNCs are used, for example, in mRNA vaccines and targeted cancer therapy.