Scientists develop a potent peptide inhibitor of SARS-CoV-2 in vitro

By Dr. Sanchari Sinha Dutta, Ph.D.Aug 2 2021

In a recently published article in the journal Drugs in R&D, scientists have described the development and validation of a 13-amino acid peptide inhibitor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

The findings reveal that the peptide inhibitor binds with high affinity to the spike receptor binding domain (RBD) of SARS-CoV-2 at the angiotensin-converting enzyme 2 (ACE2) binding site and prevents the RBD – ACE2 interaction.

Study: A Novel Therapeutic Peptide Blocks SARS-CoV-2 Spike Protein Binding with Host Cell ACE2 Receptor. Image Credit: vchal / Shutterstock

Background

The first step to SARS-CoV-2 entry into host cells is the interaction between viral spike RBD and host cell ACE2 receptor. This is followed by proteolytic cleavage and activation of the spike protein by host cell protease TMPRSS2 and subsequent fusion of the viral envelope with the host cell membrane. Thus, small molecule or peptide inhibitors capable of blocking the RBD – ACE2 interaction are expected to play vital roles in preventing entry of SARS-CoV-2 into host cells and controlling the infection at early stages.

Several approaches have been considered to block RBD -ACE2 interaction, including soluble ACE2, convalescent plasma-derived antibodies, epitope-specific vaccines, repurposed antiviral drugs, and peptide inhibitors. Compared to small molecule- and protein-based interventions, peptides exhibit several advantages, including high structural compatibility with target proteins and specific blocking of protein – protein interactions.

In the current study, the scientists have developed a novel peptide inhibitor of SARS-CoV-2 using computational biology tools.

Study design

Using in silico approaches, the scientists designed and developed a 13-amino acid peptide inhibitor against the spike RBD of SARS-CoV-2 and confirmed its binding specificity for the spike RBD using molecular docking models. To determine the stability of peptide – spike RBD complex, they performed molecular dynamics simulation. Furthermore, they determined the physicochemical and pharmacokinetic (absorption, distribution, metabolism, excretion, and toxicity) properties of the peptide using web-based tools.

To validate the functionality of the peptide in in vitro setups, they conducted an enzyme-linked immunosorbent assay (ELISA) that determines the percentage of spike RBD – ACE2 binding in presence of the peptide.  

Structural validation of the peptide inhibitor

The findings of peptide – protein docking experiments revealed that the peptide binds to spike RBD specifically at the same pocket where the ACE2 binds. Three residues K417, Y489, and Q493 of the spike RBD that bind to ACE2, were found to interact with the peptide. Moreover, molecular dynamics simulation findings reveal no significant alteration in the ACE2 binding interface of the spike RBD and no fluctuations in protein – peptide binding interface. These findings indicate that the peptide forms a stable complex with spike RBD to efficiently block the RBD – ACE2 interaction.

Regarding physicochemical properties, the findings revealed that the peptide is stable and water-soluble with an estimated half-life of 1.1 hours. Moreover, the findings revealed that the peptide is not permeable to the blood-brain barrier and has no skin toxicity or carcinogenicity.  

Functional validation of the peptide inhibitor

The findings of the ELISA-based spike – ACE2 inhibitor screening assay revealed that the peptide significantly inhibits the spike RBD – ACE2 interaction in a concentration-dependent manner. Specifically, at a concentration of 100 µM, the peptide inhibited the interaction by more than 40%.

Study significance

In this study, a 13-amino acid peptide inhibitor of SARS-CoV-2 has been developed, which binds with affinity at the RBD – ACE2 binding interface and efficiently inhibits the RBD – ACE2 interaction. The peptide possesses several advantages, including easy and low-cost manufacturing, low toxicity, good solubility and stability, high specificity and selectivity for the target, and considerable half-life.

Taken together, the study highlights the importance of computational tools in designing and developing peptide inhibitors that can be potentially used as therapeutics to prevent SARS-CoV-2 infection at early stages.