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

Area of Science:

• Biotechnology
• Computational Biology
• Immunology

Background:

• Single-chain variable fragment (scFv) antibodies are engineered proteins comprising linked variable heavy and light chains.
• These antibodies are crucial in developing targeted therapies, particularly in oncology.
• Previous scFv constructions utilized a Gly4-Ser linker, modeled as a loop structure.

Purpose of the Study:

• To introduce an in silico protocol for analyzing a complete scFv antibody designed to interact with the epidermal growth factor receptor (EGFR).
• To evaluate the binding affinity and stability of the designed scFv antibody against EGFR using computational methods.
• To establish the potential of the designed scFv as a targeted immune-therapeutic agent for EGFR-driven diseases.

Main Methods:

• Homology modeling and protein structure modeling using Python were employed to construct the scFv antibody model.
• Protein-protein docking studies were performed using the Pyrx software platform.
• Molecular dynamics (MD) simulations were conducted to assess the stability and binding interactions of the EGFR-scFv complex.

Main Results:

• The homology modeling successfully generated the scFv antibody structure.
• Molecular docking revealed a binding energy of -5.4 kcal/M after energy minimization, indicating favorable interaction.
• MD simulations demonstrated the stability of the docked EGFR-scFv antibody complex for 20-75 ns, with structural movement stabilizing.

Conclusions:

• The in silico analysis, encompassing molecular docking and MD simulations, validated the designed scFv antibody's effectiveness.
• The study confirms the potential of this engineered scFv as a specific therapeutic agent for EGFR-targeted therapy.
• This computational approach provides a robust framework for designing and validating novel immune-therapeutic drugs.