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In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Representative Results
  • Discussion
  • Disclosures
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

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 chang....

Protocol

1. Secondary structure predictions of a single chain fragment variable (scFv) protein

  1. 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).
  2. Use the molecular modeling software to build the linker as a loop structure, and perform all these methods as described in previous studies2,19,20.

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

NameCompanyCatalog NumberComments
Autodock softwareCenter for Computational structural Biology AutoDock (scripps.edu)
Desmond Maestro 19.4 software Schrodingerwww.schrodinger.com 
Download Discovery Studio 2021  Dassault Systems https://discover.3ds.com/discovery-studio-visualizer-download.
Modeler Version 9.24[17] University of Californiahttps://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 SchrodingerPyMOL | pymol.org
Pyrx software Sourceforge Download PyRx - Virtual Screening Tool (sourceforge.net)
Python script 3.7.9 shell from the window (64)PythonPython Release Python 3.7.9 | Python.org
SPDBV software Expasyhttp://spdbv.vital-it.ch/disclaim.html

References

  1. Clark, J. J., Orban, Z. J., Carlson, H. A. Predicting binding sites from unbound versus bound protein structures. Sci Rep. 10 (1), 15856 (2020).
  2. Huang, Y., et al.

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