Fragment-based design of small molecule PCSK9 inhibitors using simulated annealing of chemical potential simulations.

PCSK9 is a protein secreted by the liver that binds to the low-density lipoprotein receptor (LDLR), causing LDLR internalization, decreasing the clearance of circulating LDL particles. Mutations in PCSK9 that strengthen its interactions with LDLR result in familial hypercholesterolemia (FH) and early onset atherosclerosis, while nonsense mutations of PCSK9 result in cardio-protective hypocholesterolemia. These observations led to PCSK9 inhibition for cholesterol lowering becoming a high-interest therapeutic target, with antibody drugs reaching the market.

Hot-spot identification on a broad class of proteins and RNA suggest unifying principles of molecular recognition.

Chemically diverse fragments tend to collectively bind at localized sites on proteins, which is a cornerstone of fragment-based techniques. A central question is how general are these strategies for predicting a wide variety of molecular interactions such as small molecule-protein, protein-protein and protein-nucleic acid for both experimental and computational methods. To address this issue, we recently proposed three governing principles, (1) accurate prediction of fragment-macromolecule binding free energy, (2) accurate prediction of water-macromolecule binding free energy, and (3) locating sites on a macromolecule that have high affinity for a diversity of fragments and low affinity for water.

Design, synthesis and biological evaluation of renin inhibitors guided by simulated annealing of chemical potential simulations.

We have applied simulated annealing of chemical potential (SACP) to a diverse set of ∼150 very small molecules to provide insights into new interactions in the binding pocket of human renin, a historically difficult target for which to find low molecular weight (MW) inhibitors with good bioavailability. In one of its many uses in drug discovery, SACP provides an efficient, thermodynamically principled method of ranking chemotype replacements for scaffold hopping and manipulating physicochemical characteristics for drug development. We introduce the use of Constrained Fragment Analysis (CFA) to construct and analyze ligands composed of linking those fragments with predicted high affinity.