Discovery of AZD2716: A Novel Secreted Phospholipase A₂ (sPLA₂) Inhibitor for the Treatment of Coronary Artery Disease

Expedited structure-based optimization of the initial fragment hit <b>1</b> led to the design of (<i>R</i>)-<b>7</b> (AZD2716) a novel, potent secreted phospholipase A₂ (sPLA₂) inhibitor with excellent preclinical pharmacokinetic properties across species, clear <i>in vivo</i> efficacy, and minimized safety risk. Based on accumulated profiling data, (<i>R</i>)-<b>7</b> was selected as a clinical candidate for the treatment of coronary artery disease

Design of Selective sPLA₂‑X Inhibitor (−)-2-{2-[Carbamoyl-6-(trifluoromethoxy)‑1<i>H</i>‑indol-1-yl]pyridine-2-yl}propanoic Acid

A lead generation campaign identified indole-based sPLA₂-X inhibitors with a promising selectivity profile against other sPLA₂ isoforms. Further optimization of sPLA₂ selectivity and metabolic stability resulted in the design of (−)-<b>17</b>, a novel, potent, and selective sPLA₂-X inhibitor with an exquisite pharmacokinetic profile characterized by high absorption and low clearance, and low toxicological risk. Compound (−)-<b>17</b> was tested in an ApoE^–/– murine model of atherosclerosis to evaluate the effect of reversible, pharmacological sPLA₂-X inhibition on atherosclerosis development. Despite being well tolerated and achieving adequate systemic exposure of mechanistic relevance, (−)-<b>17</b> did not significantly affect circulating lipid and lipoprotein biomarkers and had no effect on coronary function or histological markers of atherosclerosis

Discovery of a Series of Indole‑2 Carboxamides as Selective Secreted Phospholipase A₂ Type X (sPLA₂‑X) Inhibitors

In order to assess the potential of sPLA₂-X as a therapeutic target for atherosclerosis, novel sPLA₂ inhibitors with improved type X selectivity are required. To achieve the objective of identifying such compounds, we embarked on a lead generation effort that resulted in the identification of a novel series of indole-2-carboxamides as selective sPLA2-X inhibitors with excellent potential for further optimization