Identification of naturally originated molecules as γ-aminobutyric acid receptor antagonist

Abstract

γ-aminobutyric acid, being a principle neuromediator in humans controlling the inhibition signals, acts on the ligand-gated pentameric type A receptors to transmit their response. Any dysfunction of these receptors leads to neurological disorders and mental illness. Benzodiazepine has been used extensively for the treatment of these disorders, which shows its effect by reducing the threshold concentration of γ-aminobutyric acid required to activate the receptor. Being a central nervous system depressant, benzodiazepine is also a common substance of abuse along with other recreational drugs that show affinity towards the benzodiazepine binding site. Flumazenil is considered the first line of treatment for the overdose of these substances, which competes with them to bind with the receptor having a higher binding affinity towards the receptor. Like most of the synthetic drugs, Flumazenil also has some side-effects associated with it. Here we focus our work towards finding specific naturally originated antagonist of the benzodiazepine binding site to suggest an alternative for Flumazenil by performing various computational analysis like docking experiments followed by simulations and molecular mechanics poisson-boltzmann surface area analysis. Molecular docking experiments filtered out four ligand molecules specific for the benzodiazepine binding site, namely, ligand-1,7,9 and 17. Further, molecular dynamics simulations showed ligand-17 to have stable conformation in the binding site as well as a lower binding free energy as compared to Flumazenil. Due to its natural origin, ligand-17 is supposed to have lower side effects; therefore, its backbone can be further explored to develop specific antagonists of benzodiazepines.

Communicated by Ramaswamy H. Sarma

Graphical Abstract

Keywords:

• GABA
• molecular docking
• MM-PBSA
• molecular dynamics simulations
• benzodiazepines

Acknowledgements

The authors are thankful to the Director, CSIR-IHBT for providing necessary facilities and support. RP gratefully acknowledges the Board of Research in Nuclear Sciences, Department of Atomic Energy, Mumbai, India for financial support vide letter No: 37(1)/14/26/2015/BRNS. VB acknowledges the Department of Science and Technology, New Delhi, India for providing junior research fellowship SERB File No: ECR/2016/000031. The CSIR support in the form of projects MLP0201 for bioinformatics studies and MLP0140 for providing project fellowship is highly acknowledged. This manuscript represents CSIR-IHBT communication no. 4491.

Disclosure statement

No potential conflict of interest was reported by the author(s).