Computational binding study with α7 nicotinic acetylcholine receptor of Anvylic-3288: an allosteric modulator

ABSTRACT

Nicotinic receptors are ligand-gated ion channels, involved in the generation of action potential in post synaptic membrane and motor endplate. The α7 Nicotinic Acetylcholine Receptor (nAChR) is a class of nicotinic receptor involved in cognition. It is distributed in hippocampus, thalamus, sensory and information processing regions of the brain. The receptor is implicated in various diseases, including Alzheimer’s disease, Parkinsonism, Schizophrenia, Autism, Rett syndrome etc. Therefore, targeting the modulation of the receptor would be advantageous. Positive allosteric modulators (PAMs) potentiate the response i.e. peak current of the receptor. Type I allosteric modulator, Anvylic-3288 (AVL-3288), increases peak current without altering the response of α7-nAChR upon acetylcholine binding. In present study, in silico approach was used to identify the plausible binding model of AVL-3288 involved in modulation. Docking study displayed that a1 binding modes had better binding energies than the t1 and v1 modes. The MD (Molecular Dynamics) simulation produced stable complex for a1 pose, binding to agonist subpocket, with α7-nAChR having protein and ligand RMSD (Root Mean Square Deviation) in the acceptable limits, and comparable to MM/PBSA (Molecular Mechanics Poisson-Boltzmann Surface Area) results.

KEYWORDS:

• AVL-3288
• positive allosteric modulators
• α7-nAChR
• Amber
• docking

Acknowledgements

Authors would like to acknowledge the financial support from Ministry of Human Resource and Development (MHRD), New Delhi, India in the form of teaching assistantship to AG, RS, DK, D and SS. The authors would also like to extend their gratitude toward Professor David A. Case, Department of Chemistry & Chemical Biology, Rutgers University, New Jersey, USA for granting a license for Amber 18 and Dr Stefano Forli, Department of Integrative Structural and Computational Biology, Scripps Research, California Campus for providing python script (vstools_v0.16).

Disclosure statement

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

Additional information

Funding

Authors would like to acknowledge the financial support from Ministry of Human Resource and Development (MHRD), New Delhi, India in the form of teaching assistantship to AG, RS, DK, D and SS.