In this award from the Chemistry of Life Processes Program in the Division of Chemistry, Professor Steven Regen and his team from Lehigh University use a bottom-up approach to the study of lipid sorting that combines synthetic organic chemistry with nearest-neighbor recognition (NNR) measurements. The latter will be used to quantify the preference of lipidated peptides to become a nearest neighbor of cholesterol and phospholipids in fluid bilayers. Monte Carlo monolayer simulations will be performed to provide a detailed molecular-level view of membrane organization. The immediate objectives of this research are to gain a fundamental understanding of how the lipidation of a simple dipeptide, glycine-cysteine- (Gly-Cys-) affects its lateral organization in systems that mimic cell membranes; that is, liposomal membranes in the liquid-ordered/liquid-disordered coexistence region. The Gly-Cys framework was selected for this research because the myristoyl-Gly-Cys(palmitoyl)-moiety, found in p56lck and the Src family of kinases, has been postulated as being optimal for associating with lipid rafts.
One of the greatest challenges facing chemists, biochemists and biophysicists is to understand how cell membranes are organized and how such organization influences cellular function. An intriguing idea that has emerged in recent years assumes that cholesterol favors association only with certain types of molecules. This research will test this hypothesis using simple model systems and a technique termed, the nearest-neighbor recognition method, which is capable of quantifying molecular association. The long term goal of this program is to provide a solid foundation for future studies that will help unravel the mystery surrounding membrane organization.
While conducting this work, Dr. Regen will involve a significant cohort of undergraduate students in intensive, original research activities. Therefore, the project has potential to empower students at an early stage of their academic development to become scientists.
