Structural Analyses of An Epidermal Growth Factor Receptor-Specific Single-Chain Fragment Variable via An In Silico Approach

Published: November 10, 2023

doi:

¹College of Arts and Sciences,Qatar University, ²Amity University

Summary

This antibody homology modeling prediction protocol is followed by antibody-receptor Pyrx docking and molecular dynamic simulation. These three primary methods are used to visualize the accurate antibody-receptor binding areas and the binding stability of the final structure.

Abstract

Single-chain fragment variable (scFv) antibodies were previously constructed of variable light and heavy chains joined by a (Gly4-Ser) 3 linker. The linker was created using molecular modeling software as a loop structure. Here, we introduce a protocol forin silico analysis of a complete scFv antibody that interacts with the epidermal growth factor receptor (EGFR). The homology modeling, with Pyrx of protein-protein docking and molecular dynamic simulation of the interacting scFv antibody and EGFR First, the authors used a protein structure modeling program and Python for homology modeling, and the antibody scFv structure was modeled for homology. The investigators downloaded Pyrx software as a platform in the docking study. The Molecular dynamic simulation was run using modeling software. Results show that when the MD simulation was subjected to energy minimization, the protein model had the lowest binding energy (-5.4 kcal/M). In addition, the MD simulation in this study showed that the docked EGFR-scFv antibody was stable for 20-75 ns when the movement of the structure increased sharply to 7.2 Å. In conclusion, in silicoanalysiswas performed, and the molecular docking and molecular dynamics simulations of the scFv antibody proved the effectiveness of the designed immune-therapeutic drug scFv as a specific drug therapy for EGFR.

Introduction

Conformational changes in the protein (ligand and receptor) always occur based on structure-based functions. The study of the possible binding grooves of the protein and prediction of the stable binding interaction is an advanced method to prepare drugs for better use in the human body. Homology modeling followed by docking and molecular dynamic simulation is a straightforward method for accurate prediction of stable interactions of binding between the residues of receptors and constructed antibodies that are used as specific personalized medicine¹^,². The predicted model structure can show conformational changes and rearrangements in ligand-receptor binding sites, particularly at the antibody-receptor interface. There are many reasons for these changes, such as the rotation of side chains, global structural transformation, or more complex modifications. The main reason for homology modeling is to distinguish a protein’s tertiary structure from its primary structure²^,³.

A tyrosine kinase receptor called epidermal growth factor receptor (EGFR) plays many biological roles in cancer cells, including apoptosis⁴^,⁵, differentiation⁶^,⁷, cell cycle progression⁸^,⁹, development⁹^,¹⁰, and transcription¹¹. EGFR is one of the well-known therapeutic targets for breast cancer¹². The overexpression of regular kinase activity such as EGFR usually leads to cancer cell progression, which can be repressed by many kinds of cancer inhibitors¹³. The epidermal growth factor receptor (EGFR) was used as a receptor for the single chain fragment variable specifically constructed to work against this receptor. Its predicted structure was used to test the antibody binding activity.

In this paper, the scFv antibody structure was modeled using modeling software with Python script and the homology modeling method¹⁴^,¹⁵. A homology model can be built from the protein and amino acid sequences of receptors and ligands¹⁶^,¹⁷. Additionally, advanced bioinformatics technologies such as molecular docking were employed to predict how small molecule ligands will bind to the correct target binding site. The docking would balance the development of novel drugs directed toward multiple diseases. The binding behavior is taken into consideration⁵^,¹⁸.

Furthermore, molecular docking is a critical technique to facilitate and speed up ligand-receptor binding development. Molecular docking enables scientists to virtually screen a library of ligands against a target protein and predict the binding conformations and affinities of the ligands to the target receptor protein. Molecular dynamic simulation (MNS) demonstrates how the residues move in space, simulates the antibody motions toward their receptors, and finally informs antibody design efforts. This study is a novel prediction of grid box dimensions that decided how the scFv antibody binds to EGFR and the detection of the energy and time of that binding in MDsimulation.

Protocol

1. Secondary structure predictions of a single chain fragment variable (scFv) protein Build the single-chain fragment variable (scFv) protein's 3D structure with BLAST protein data bank (PDB), KABAT numbering, and the modeling software. The scFv consists of a linker (Gly4-Ser) that connects a variable heavy chain (VH) and a variable light chain (VL). Use the molecular modeling software to build the linker as a loop structure, and perform all these methods as described in previou…

Representative Results

Using phage display technology, the scFv gene anti-EGFR was created from the mouse B-cell hybridoma line C3A820,21. The single chain fragment variable (scFv) structure models of the VH and VL structures were built separately, according to Chua et al.22. After that, the models were visible as ribbons produced using RasMol. Then, using molecular modeling software, a synthetic peptide [Gly4Ser)3 was used to join the separately modeled VH and …

Discussion

EGFR is the primary target receptor of breast cancer. EGFR overexpression increases breast cancer cases around the world. Meanwhile, specific antibodies such as single chain fragment variables are antibodies that move easily via blood circulation and have a fast clearance rate in the body. Antibodies are a wise solution and an effective immunotherapy drug³⁷. Therefore, structure-based drug design must identify inhibitory medicines, such as scFv antibodies, that work specifically against a target r…

Disclosures

The authors have nothing to disclose.

Acknowledgements

None.

Materials

Autodock software	Center for Computational structural Biology	AutoDock (scripps.edu)
Desmond Maestro 19.4 software	Schrodinger	www.schrodinger.com
Download Discovery Studio 2021	Dassault Systems	https://discover.3ds.com/discovery-studio-visualizer-download.
Modeler Version 9.24[17]	University of California	https://salilab.org/modeller/9.24/release.html
Pictorial database of 3D structures (pdbsum)	EMBL-EBI	www.ebi.ac.uk/thornton-srv/databases/pdbsum/
PyMOL software	Schrodinger	PyMOL \| pymol.org
Pyrx software	Sourceforge	Download PyRx – Virtual Screening Tool (sourceforge.net)
Python script 3.7.9 shell from the window (64)	Python	Python Release Python 3.7.9 \| Python.org
SPDBV software	Expasy	http://spdbv.vital-it.ch/disclaim.html

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