Identification of Potential Necroptosis Inhibitors using Pharmacophore Model: An In-silico Approach

Background:: Necrosis, a form of uncontrolled cell death, can be triggered by a variety of stressors, including infection, injury, toxins, and ischemia. Such necrotic events, particularly when induced by pathogenic infections, can lead to severe health complications. The mixed lineage kinase domain-like pseudokinase (MLKL) has been identified as a crucial drug target for mitigating necrosis. Objective:: The objective of this study is to identify potential MLKL inhibitors that act against necroptosis via a pharmacophore model and virtual screening. Methods:: In this study, we developed a ligand-based pharmacophore model to facilitate the identification of inhibitors that target MLKL. Comprehensive ADMET analysis, virtual screening, and molecular docking were employed to identify potential therapeutic candidates. Subsequently, molecular dynamics (MD) simulations and free energy calculation of a leading candidate were conducted using GROMACS and gmxMMPBSA tool to assess the stability of the MLKL-inhibitor complex. Results:: Our investigations identified 26 potential MLKL binders, with three compounds emerging as frontrunners on the basis of their favorable pharmacokinetic profiles, including high/low gastrointestinal absorption, optimal bioavailability, solubility, and non-hepatotoxicity. The MD simulations further corroborated the structural stability of the MLKL-drug complex. Conclusion:: The integrated computational approach adopted here could serve as a model for accelerating the discovery of drug candidates in other therapeutic areas as well. These findings necessitate further experimental validation before progressing to clinical trials.