Design and characterization of therapeutic peptides targeting the receptor binding domain of the spike glycoprotein from sars-cov-2

• Main Author: Ho, Chian
• Format: Thesis
• Language: English; English
• Published: 2023
• Subjects: QR180-189.5 Immunology
• Online Access: https://eprints.ums.edu.my/id/eprint/40845/1/24%20PAGES.pdf; https://eprints.ums.edu.my/id/eprint/40845/2/FULLTEXT.pdf; https://eprints.ums.edu.my/id/eprint/40845/
• Institution: Universiti Malaysia Sabah

Coronavirus Disease 2019 (COVID-19), a global pandemic which first emerged in Wuhan City, Hubei Province, China, in December 2019, was caused by a novel Betacoronavirus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). To date, there are only two Food and Drug Administration (FDA)-approved therapeutic drugs to counter COVID-19. Hence, development for COVID-19 treatment needs to be broadened. This study aims to explore an alternative treatment for COVID-19 using therapeutic peptides. This study hypothesised that therapeutic peptides that can bind with the receptor binding domain (RBD) of spike glycoprotein (S protein) of SARS-CoV-2 might inhibit the entry of the virus into host cells and prevent infection. Bioinformatics tools include PyMOL, UCSF chimera, PEP-FOLD3, HADDOCK (High Ambiguity Driven protein-protein DOCKing), and molecular dynamics simulation (MDS) are first utilised for peptide design. PyMOL and UCSF chimera were used to determine the amino acid residues involved in the binding interface. A total of 291 peptides were designed, and PEP-FOLD3 was used to generate the peptide models. Docking analysis on the peptides and RBD of S protein was performed via HADDOCK. The peptide-RBD complexes of peptides 65, 66, and 189 showed the highest HADDOCK score and hence were chosen for 200 ns of MDS analysis. MDS results showed that all three peptide-RBD complexes were compact and stable, and their interaction energy being -480.38 ± 118.61 kJ/mol, -410.92 ± 126.31 kJ/mol, and -338.49 ± 97.88 kJ/mol, respectively. The peptides were then subjected to a binding affinity test and competitive assay via ELISA (enzyme-linked immunosorbent assay). For the binding affinity test, ELISA was performed using the hemagglutinin (HA)-tagged peptides in a series of concentrations bound to RBD of S protein on a 96-well plate. A competitivee assay was performed using His-tagged ACE2 protein incubated with the peptides. Peptide 65 showed the best result with bioinformatics analysis and binding affinity test with a KD of 43.26 μM. However, the results of the competitive assay showed the that binding of peptide 65 to S protein is weak compared to the ACE2 protein. Bioinformatics tools can be utilised for preliminary analysis of the peptides designed and enables choosing of peptides with the best results for further laboratory testing. Peptide 65 can be further modified to improve its inhibiting ability and further develop into therapeutic drugs to counter COVID-19.