Probing voltage sensing domain of KCNQ2 channel as a potential target to combat epilepsy: a comparative study

Abstract

Multidrug resistance along with side-effects of available anti-epileptic drugs and unavailability of potent and effective agents in submicromolar quantities presents the biggest therapeutic challenges in anti-epileptic drug discovery. The molecular modeling techniques allow us to identify agents with novel structures to match the continuous urge for its discovery. KCNQ2 channel represents one of the validated targets for its therapy. The present study involves identification of newer anti-epileptic agents by means of a computer-aided drug design adaptive protocol involving both structure-based virtual screening of Asinex library using homology model of KCNQ2 and 3D-QSAR based virtual screening with docking analysis, followed by dG bind and ligand efficiency calculations with ADMET studies, of which 20 hits qualified all the criterions. The best ligands of both screenings with least potential for toxicity predicted computationally were then taken for molecular dynamic simulations. All the crucial amino acid interactions were observed in hits of both screenings such as Glu130, Arg207, Arg210 and Phe137. Robustness of docking protocol was analyzed through Receiver operating characteristic (ROC) curve values 0.88 (Area under curve AUC = 0.87) in Standard Precision and 0.84 (AUC = 0.82) in Extra Precision modes. Novelty analysis indicates that these compounds have not been reported previously as anti-epileptic agents.

Graphical Abstract

Keywords:

• Structure-based screening
• KCNQ2 channel openers
• epilepsy
• 3D-QSAR based screening
• ADMET
• ROC

Acknowledgments

Authors are grateful to Central University of Rajasthan for providing licensed Schrodinger molecular modeling and ADMET Predictor™ softwares. Authors are thankful to Prof. Huaiyu Yang for providing the homology model of KCNQ2 channel.

Disclosure statement

Authors have no conflicts of interest.

Additional information

Funding

Authors are thankful to the Department of Science and Technology for providing financial support with DST-Rajasthan Grant No L7(3) S&T/R&D/2016/2616 and Inspire fellowship Grant No. DST/INSPIRE/Fellowship/2014/241.