Rapid Quantum Computation of Ionizable Lipid Acidity Constants

Abstract

The COVID-19 vaccine showcased the power of lipid nanoparticles (LNPs) as a novel system for delivering therapies targeting infectious diseases and potentially other illnesses like cancer. Despite the fantastic versatility of LNPs, they require specific changes in physical properties at pHs of around 6.5 to 7.0. Ionizable lipids comprise the only pH sensitive component of the LNP. Matching the pKa of the ionizable lipid to the desired pH range should yield a change in physical properties in that range. However, no current high through-put experimental or computational approach for determining the ionizable lipid’s pKa features practical timeframes (days to months). Using faster but more approximate quantum methods than the literature standard, we found a slightly wider error margin for the predicted pKas but with significantly faster completion times, indicating a viable alternative to the literature standard. Much like the literature standard, our method does not distinguish between effective and ineffective ionizable lipids. Because of the speed increase, this method offers the opportunity to investigate potential beneficial improvements such as including the effects of lipid conformation on predicted pKa.