Designing a Stable Fusion Protein Antigen for enhancing ELISA assay sensitivity for SARS-CoV-۲ Detection: Molecular Dynamics Simulations and Bioinformatic Studies

BACKGROUND AND OBJECTIVESAccurate and sensitive detection of SARS-CoV-۲ is crucial for effective control and management of the COVID-۱۹ pandemic. This study employed bioinformatic approaches, including molecular dynamics (MD) simulations, to design a stable and efficient antigen for SARS-CoV-۲ detection. The fusion protein, CoV۲-Pro, containing multiple domains from the Omicron and Delta variants, including Receptor Binding Domain (RBD) and the nucleoprotein, was investigated for its structural stability and antigenic properties.MATERIALS AND METHODSCoV۲-Pro was designed using in-silico cloning and ۳D modeling, employing the PHYRE۲ Protein Fold Recognition Server. Subsequently, physicochemical properties were analyzed to evaluate the protein's stability and antigenicity. To gain insights into the structural dynamics and stability of CoV۲-Pro, molecular dynamics (MD) simulations were conducted, spanning ۱۰۰ nanoseconds. Moreover, for evaluation of the binding affinity between CoV۲-Pro and two SARS-CoV-۲ human IgG۱ neutralizing monoclonal antibodies (mAbs), namely Bebtelovimab LY-CoV۱۴۰۴ (PDB: ۷MMO) and LY-CoV۴۸۸ (PDB: ۷KMH), was assessed through molecular docking simulations.RESULTS AND DISCUSSIONBioinformatic studies indicated that CoV۲-Pro adopts a stable ۳D conformation with suitable antigenic characteristics. MD simulations revealed the protein's structural stability and conformational changes during the simulation period. Molecular docking simulations demonstrated strong binding interactions between CoV۲-Pro and SARS-CoV-۲ antibodies, highlighting its potential as an effective diagnostic antigen.CONCLUSIONUsing bioinformatic techniques and MD simulations, we successfully designed a stable fusion protein, CoV۲-Pro. This protein holds great promise as a robust antigen for SARS-CoV-۲ detection. Our study provides valuable insights for developing advanced diagnostic strategies to accurately identify SARS-CoV-۲ infections, contributing to the global effort to combat the COVID-۱۹ pandemic.

کلیدواژه ها:

SARS-CoV-۲ diagnosis ، Fusion proteins ، RBD Domain ، Nucleoprotein Domain ، Molecular dynamic ، COVID-۱۹