FCX‐146, a potent allosteric inhibitor of Akt kinase in cancer cells: Lead optimization of the second‐generation arylidene indanone scaffold

Abstract

Akt, a serine‐threonine protein kinase, is regulated by class‐I PI3K signaling. Akt regulates a wide variety of cell processes including cell proliferation, survival, and angiogenesis through serine/threonine phosphorylation of downstream targets including mTOR and glycogen‐synthase‐kinase‐3‐beta (GSK3β). Targeting cancer‐specific overexpression of Akt protein could be an efficient way to control cancer‐cell proliferation. However, the ATP‐competitive inhibitors are challenged by the highly conserved ATP binding site, and by competition with high cellular concentrations of ATP. We previously developed an allosteric inhibitor, 2‐arylidene‐4, 7‐dimethyl indan‐1‐one (FXY‐1) that showed promising activity against several lung cancer models. In this work, we designed a congeneric series of molecules based on FXY‐1 and optimized lead based on computational, in vitro assays. Computational screening followed by enzyme‐inhibition and cell‐proliferation assays identified a derivative (FCX‐146) as a new lead molecule with threefold greater potency than the parent compound. FCX‐146 increased apoptosis in HL‐60 cells, mediated in part through decreased expression of antiapoptotic Bcl‐2 protein and increased levels of Bax‐2 and Caspase‐3. Molecular‐dynamic simulations showed stable binding of FCX‐146 to an allosteric (i.e., noncatalytic) pocket in Akt. Together, we propose FCX‐146 as a potent second‐generation arylidene indanone compound that binds to the allosteric pocket of Akt and potently inhibits its activation.

Structural modeling of GSK3β implicates the inactive (DFG-out) conformation as the target bound by TDZD analogs

“…Although unbiased docking indicates modest TDZD-8 affinity for the ATP-binding pocket of the active-conformation GSK3β (Supplementary Fig. 4), calculation of the solvent-based binding free energy (by the MMGBSA approach 27 , 28 ) predicted that the binding affinity of TDZD-8 for this pocket would be less than half that of ATP (Supplementary Fig. 4d).…”

Computational Target-Based Drug Repurposing of Elbasvir, an Antiviral Drug Predicted to Bind Multiple SARS-CoV-2 Proteins

“…The structures of SARS-CoV-2 proteins used in this study were retrieved from I-TASSER (neural networkbased structure predictions) [9]. Proteins were preprocessed using the Protein Preparation Wizard module of Schrödinger's Prime module by the MMGBSA method, using molecular mechanics, the generalized Born solvent model, and solvent accessibility [18][19][20].…”

“…The top 15 drug candidates were then selected for next-level screening. (2) The Gibbs Free Energy of binding (ΔGbinding) was calculated within Schrödinger's Prime module by the MMGBSA method, using molecular mechanics, the generalized Born solvent model, and solvent accessibility [18][19][20].…”

Computational Target-Based Drug Repurposing of Elbasvir, an Antiviral Drug Predicted to Bind Multiple SARS-CoV-2 Proteins

“…The system was next equilibrated using the NPT protocol (constant number of particles, pressure and temperature) with default temperature (300 o K) and pressure (1 bar). MD simulations were then conducted for 100-200 ns using Desmond's GPU-based simulation method [18][19][20][21][22]. Results were analyzed using the Simulation Interactions Diagram module from Schrödinger Maestro.…”

“…The top 15 drug candidates were then selected for next-level screening. (2) The Gibbs Free Energy of binding (ΔGbinding) was calculated withinSchrödinger's Prime module by the MMGBSA method, using molecular mechanics, the generalized Born solvent model, and solvent accessibility[18][19][20].…”