Molecular Modeling Guided Pipeline for the Inhibition of Death Associated Protein Kinase-1 (DAPK-1) in the Treatment of Temporal Lobe Epilepsy (TLE)

Abstract

Temporal Lobe Epilepsy (TLE) is the most prevalent chronic disorder of the nervous system. It is a recurring form of drug-resistant focal (partial) epilepsy that affects the two temporal lobes of the brain. Brain's injuries, infections, inflammations, tumors, developmental abnormalities, genetic mutations, strokes, heart attacks, and neuronal cell death are reported to cause scraping in the temporal lobe that leads to Mesial Temporal Lobe Epilepsy or Hippocampal Sclerosis (HS). The neuronal damage initiates functional modifications in substantial membrane depolarization and failure in synaptic transmission and hyperexcitability. Hyper-excited neurons instigate focal seizures in the temporal lobe due to the activation of glutamate receptors. Failure of synaptic transmission due to hyperexcitation triggers a signal for the induction of neuronal cell death pathway and the activation of Death Associated Protein Kinase-1 (DAPK-1). It is a pro-apoptotic Ser/Thr kinase protein that controls neuronal death signaling processes, such as apoptosis and autophagy. In ER stress signaling, DAPK-1 acts as a critical integration point because it forms direct interaction with NMDA receptor subunits. This interaction increases conductance for glutamate and induces brain damage by an ischemic stroke, ultimately causing focal seizures. In the present research study, DAPK-1 was identified as a potential target for the treatment of TLE. In molecular docking, all the specific inhibitors of DAPK-1 were docked at the binding site. Molecular dynamic simulation highlighted the role of the different regions (Entrance, Hinge, glycine-rich, and substrate-binding motif) that were crucial for selectivity and specificity. The binding residues of the target, such as Leu19, Glu94, Val96, and Glu100 were involved in stable interactions with highly actives ligands. The most stable complex, after MD, was selected for the pharmacophore model. This model contains one hydrophobic, one donor, and two acceptor hydrogen bond features. The developed model displayed 100% accuracy, sensitivity, specificity, and precision values. The model was used to screen the Zinc database containing natural compounds. Interestingly, some of the identified hits were used in the treatment of epilepsy by reducing the severity of seizures which further strengthen the applicability of our proposed pharmacophore model.