Computationally Aided Design of Ionizable Cholesteryl Lipids for Lipid Nanoparticles to Modulate Hepatic mRNA...

mRNA therapeutics are emerging as a revolutionary therapeutic modality, providing a versatile platform for the treatment and prevention of a broad spectrum of diseases. Nonviral nanoparticle-based delivery systems, particularly lipid nanoparticles (LNPs), are essential for their successful clinical translation. However, the currently FDA-approved four-component lipid nanoparticle (LNP) formulations primarily accumulate in the liver due to apolipoprotein E/Low-Density Lipoprotein Receptor (ApoE/LDLR)-mediated uptake by hepatic cells following systemic administration, which significantly limits extrahepatic mRNA delivery and restricts its broader therapeutic applications. Herein, we present a computationally assisted design approach to identify and optimize ionizable cholesteryl (iChol) lipids with extrahepatic delivery properties while formulating a three-component LNP system. Using DiffDock-L-assisted design, we rationally integrated two key components of LNPs, cholesterol and ionizable lipid, into a single chemical entity and developed a novel class of ionizable cholesteryl (iChol) lipids that exhibit attenuated interactions with ApoE. These iChol lipids, along with phospholipids and PEGylated lipids, can self-assemble into stable three-component lipid nanoparticles (Tc-LNPs). The Tc-LNPs exhibit decreased ApoE adsorption compared to conventional four-component LNP counterparts. Importantly, the Tc-LNPs show reduced hepatic accumulation via modulating ApoE/LDLR-mediated endocytosis in hepatocytes and improved spleen enrichment compared to commercially available LNPs. Additionally, this approach is applicable to other ionizable lipids, including the commercially available ALC-0315 lipid, paving a new way for accelerating the development of extrahepatic delivery LNPs and potentially expanding the applications of mRNA-based therapeutics.