Browsing by Subject "molecular dynamics"

Lecithin:cholesterol acyltransferase (LCAT), a key enzyme in maturating high-density lipoprotein (HDL) particles, has been targeted to promote the efficiency of reverse cholesterol transport by small molecular positive allosteric modulators (PAM) of Daiichi Sankyo. For a set of these compounds their Vmax and EC50 values and binding site in the membrane-binding domain (MBD) of LCAT have been determined. Through molecular dynamics (MD) simulations we previously found a metric that qualitatively described which compounds were active, so in this study we aimed to improve it by finding a quantitative metric. This led to the discovery of the Cα distance between CYS50 and ASN65, which correlates with this set’s Vmax values and which can be utilized to predict the Vmax values of novel compounds. Additional simulations were performed to discover whether this metric is changed by a lipid interface present, and to reveal a likely entry pathway PAMs take. As LCAT activation is likely a benign and potentially overlooked effect, we performed a virtual screen of FDA-approved compounds and secondary metabolites associated with LCAT. From secondary metabolites, a key finding was that flavonoids were overwhelmingly associated with LCAT and had a high binding potential to the MBD in docking simulations. The best binding compounds were subjected to MD simulations to discover their Vmax values using the discovered metric. This provided us with a set of compounds, which can be used to validate our in silico model in vitro. Should this model be validated, it can be used in optimising and discovering novel PAMs of LCAT, and it would bring evidence to the benefit of MD in drug discovery processes in general. Furthermore, if our discovered compounds can activate LCAT in vitro, they may be used as precursors for novel PAMs or as therapies by themselves not only for LCAT deficiencies, but perhaps for atherosclerotic cardiovascular diseases as well.