Insights of ligand binding in modeled h5-HT_1A receptor: homology modeling, docking, MM-GBSA, screening and molecular dynamics

Abstract

The pharmacologically characterized receptor subtype of the serotonin family, the 5HT1A receptor is implicated in the pathophysiology and treatment of depression and anxiety-related disorders. Being the most extensively targeted receptor for developing novel antidepressants and anxiolytics, a near-ideal theoretical model can aid in high-throughput screening of promising drug candidates. However, the design of potential drug candidates suffers owing to a lack of complete structural information. In this work, homology models of 5-HT1A receptor are generated using two distinct alignments (CW and PSTA) and model building methods (KB and EB). The developed models are validated for virtual screening using a ligand dataset of agonists and antagonists. The best-suited model was efficient in discriminating agonist/antagonist binding. Correlation plots between pKi and docking (R²_agonist≥ 0.6, R²_antagonist≥ 0.7) and MM-GBSA dG bind values (R²_agonist≥ 0.5, R²_antagonist≥ 0.7) revealed optimum corroboration between in vitro and in silico outcomes, which further suggested the usefulness of the developed model for the design of high-affinity probes for the neurological disorders.

Communicated by Ramaswamy H. Sarma

Keywords:

• h5-HT_1A receptor
• homology modeling
• docking
• ligand binding
• molecular dynamics

Disclosure statement

The authors report no potential conflict of intrest.

Additional information

Funding

The work was supported by Defence Research and Development Organization, Ministry of Defence and carried under the Project INMAS-SAMEER funded by Meity. We endorse SCFBio, IIT Delhi and M/S Schrödinger, Bangalore for providing the computational support for MD simulations.