Accelerating Lead Optimization Away from Anti-Targets: Navigating the Structural Complexity of Promiscuous ADMET Proteins
Howook Hwang, Mee Shelley, Andrew Placzek, Kevin DeMarco, Steven Albanese, Andreas Verras, Neelu Kaila, Joshua McElwee, Sebastien Campos, Justin A. Caravella, Samantha Carreiro, Scott D. Edmondson, Kevin D. Kreutter, Sheetal Kumar, Angela V. Toms, Peter J. Tummino, Lewis Whitehead, Sung-Sau So, Daigo Inoyama, Kyle Konze, Robert Pelletier, Tianchuan Xu, Robert Abel, Richard A. Friesner, Edward B. MillerAbstract
The development of a small molecule suitable for clinical use involves optimization of ligand binding to an identified target protein but also frequently the reduction of binding to a variety of anti-target proteins known to pose translational risk. These anti-targets, often referred to as ADMET proteins, often contain large, highly flexible binding sites, leading to promiscuous binding of small molecules. This property often frustrates efforts to execute structure-based design against these anti-targets. Here, we demonstrate the application of a combination of induced fit docking and free energy perturbation to structurally enable several of the most common anti-targets: cytochrome P450 isoforms 3A4 and 2D6, the hERG ion channel, and PXR. Crucially, the enforcement of a consensus binding mode across a congeneric series allowed for the efficient exploration of a wide range of receptor conformational space. Results are presented for both public retrospective datasets and prospective application in active drug discovery programs.