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Assessing Cellular Target Engagement by SHP2 PTPN11 Phosphatase Inhibitors
Published on: July 17, 2020
Mechanistic insights into marine-derived PDE6D inhibitors disrupting prenyl-binding to modulate leukemia-associated
Perwez Alam1, Ali Akhtar1, Sarfaraz Ahmed1
1Department of Pharmacognosy, College of Pharmacy, King Saud University, P.O. Box 2457, Riyadh, Saudi Arabia.
None:
Leukemia is a significant clinical issue, and some of its subtypes are characterized by dysregulated prenylation-dependent signaling that contributes to disease onset and therapeutic resistance. Intracellular trafficking of farnesylated cargos of oncogenic signaling involves prenyl-binding chaperone PDE6D. Herein, we report a systematic computational platform toward the identification of structurally new marine fungal metabolites as prospective inhibitors of PDE6D. Our pipeline integrates high-throughput virtual screens, machine learning-guided QSAR models of molecules, density functional theory (DFT)-based molecular optimization, redocking, and long-timescale molecular dynamics (MD) investigations. Three lead molecules (CMNPD26276, CMNPD27347, and CMNPD29044) were identified using this pipeline based on their calculated inhibitory potency (pIC₅₀), desired electronic properties, and dynamic conformational stability within the binding crevice of PDE6D. Among these molecules, CMNPD29044 registered the maximum binding free energy and formed sustained interactions with and toward crucial binding residues of the binding of the PDE6D cargos. Additional MM-GBSA calculation and free energy landscape investigation confirmed a strong and energetically favorable binding conformation. Principal component analysis of these ligands suggested that they stabilize individual conformational states of the PDE6D and favor a possible interaction with a functionally essential site. This work suggests the therapeutic potential of targeting the prenyl-binding chaperone PDE6D as a novel non-enzymatic approach to leukemia treatment and identifies the strength of combining machine learning, quantum chemical, and atomistic simulation methods for the early identification of candidate drugs. Proposed marine candidates show promising leads toward experimental confirmation and toward SAR development for the treatment of PDE6D-targeted leukemia.
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