Autoencoder-based detection of the residues involved in G protein-coupled receptor signaling

Yuko Tsuchiya,Kei Taneishi,Yasushige Yonezawa

doi:10.1038/s41598-021-99019-z

Abstract

Regulator binding and mutations alter protein dynamics. The transmission of the signal of these alterations to distant sites through protein motion results in changes in protein expression and cell function. The detection of residues involved in signal transmission contributes to an elucidation of the mechanisms underlying processes as vast as cellular function and disease pathogenesis. We developed an autoencoder (AE) based method that detects residues essential for signaling by comparing the fluctuation data, particularly the time fluctuation of the side-chain distances between residues, during molecular dynamics simulations between the ligand-bound and -unbound forms or wild-type and mutant forms of proteins. Here, the AE-based method was applied to the G protein-coupled receptor (GPCR) system, particularly a class A-type GPCR, CXCR4, to detect the essential residues involved in signaling. Among the residues involved in the signaling of the homolog CXCR2, which were extracted from the literature based on the complex structures of the ligand and G protein, our method could detect more than half of the essential residues involved in G protein signaling, including those spanning the fifth and sixth transmembrane helices in the intracellular region, despite the lack of information regarding the interaction with G protein in our CXCR4 models.

Highlights

Abbreviations AE Autoencoder molecular dynamics (MD) Molecular dynamics GPCR G protein-coupled receptor EC Extracellular TM Transmembrane IC Intracellular PDB Protein data bank electron microscopy (EM) Electron microscopy root mean square deviation (RMSD) Root mean square deviation root mean square fluctuation (RMSF) Root mean square fluctuation mean squared error (MSE) Mean squared error
We focused on the detection of essential residues involved in the transmission of the signal of ligand binding to allosteric sites without large conformational deformations
This method can detect most of the essential residues involved in the signaling in PDZ2 that were detected through an NMR study[13], and the number of detected residues was larger than that in other MD s tudies[9,10,11,12], which focused on the changes in the degree of conformational fluctuation and correlation between fluctuations of two residues through ligand binding

Summary

Introduction

Abbreviations AE Autoencoder MD Molecular dynamics GPCR G protein-coupled receptor EC Extracellular TM Transmembrane IC Intracellular PDB Protein data bank EM Electron microscopy RMSD Root mean square deviation RMSF Root mean square fluctuation MSE Mean squared error. The fluctuation data obtained through molecular dynamics (MD) simulations of the protein in apo and holo forms were compared in terms of the similarity of the fluctuation patterns using an unsupervised neural network, an autoencoder (AE), and the residues essential in signaling were detected based on the results of the inspection using the AE.

Results

Conclusion