Insights into Serotonin-Receptor Binding and Stability via Molecular Dynamics Simulations: Key Residues for Electrostatic Interactions and Signal Transduction

15 April 2024, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Serotonin-receptor binding plays a key role in several neurological and biological processes, including mood, sleep, hunger, cognition, learning, and memory. In this article, we performed molecular dynamics simulation to examine the key residues that play an essential role in the binding of serotonin to the G-protein-coupled 5-HT$_{1B}$ receptor (5HT$_{1B}$R) via electrostatic interactions. Key residues for electrostatic interactions were identified via bond distance analysis and frustration analysis method. An end-point free energy calculation method determines the stability of the 5-HT$_{1B}$R due to serotonin binding. The single-point mutation of the polar/charged amino acid residues (Asp129, Thr134) on the binding sites and the calculation of binding free energy validates the quantitative contribution of these residues in the stability of the serotonin-receptor complex. The principal component analysis reflects that the serotonin-bound 5-HT$_{1B}$R is more stabilized than the apo-receptor regarding dynamical changes. The difference dynamic cross-correlations map shows the correlation between the transmembranes and mini-G$_{o}$, which indicates that the signal transduction happens between mini-G$_{o}$ and the receptor. Allosteric pathway analysis reveals the key nodes for signal transduction in 5-HT$_{1B}$R. These results provide useful insights into the study of signal transduction pathways and mutagenesis to regulate the functionality of the complex. The developed protocols can be applied to study local non-covalent interactions and long-range allosteric communications in any protein-ligand system for computer-aided drug design.

Keywords

Serotonin-receptor binding
molecular dynamics simulation
electrostatic interaction
allosteric pathways
signal transduction

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