Native Structure-Based Peptides as Potential Protein–Protein Interaction Inhibitors of SARS-CoV-2 Spike Protein and Human ACE2 Receptor

Abstract

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is a positive-strand RNA virus that causes severe respiratory syndrome in humans, which is now referred to as coronavirus disease 2019 (COVID-19). Since December 2019, the new pathogen has rapidly spread globally, with over 65 million cases reported to the beginning of December 2020, including over 1.5 million deaths. Unfortunately, currently, there is no specific and effective treatment for COVID-19. As SARS-CoV-2 relies on its spike proteins (S) to bind to a host cell-surface receptor angiotensin-converting enzyme-2(ACE2), and this interaction is proved to be responsible for entering a virus into host cells, it makes an ideal target for antiviral drug development. In this work, we design three very short peptides based on the ACE2 sequence/structure fragments, which may effectively bind to the receptor-binding domain (RBD) of S protein and may, in turn, disrupt the important virus-host protein–protein interactions, blocking early steps of SARS-CoV-2 infection. Two of our peptides bind to virus protein with affinity in nanomolar range, and as very short peptides have great potential for drug development.

A Collection of Designed Peptides to Target SARS-CoV-2 Spike RBD—ACE2 Interaction

“…elements of the interface. In the case of RBD/ACE2 interface, different peptides recapitulated the main H1 helix (partially or entirely) with minor conformation adjustments (Figure 3A) Likewise, in the case of the ACE2/ACE2 interface, peptides also show a helical conformation similar to the helix that mediates the interaction between ACE2 monomers (Figure 3B) Redesigned native elements, such as the main H1 helix, has been shown to inhibit the interaction between RBD and ACE2 ( [8,[25][26][27]). Besides recapitulation of native structural elements, designed peptides also presented novel conformations not observed in the native complexes.…”

“…In the context of viral infection examples such as the FDA-approved peptide Enfurvirtide [16] and further research (reviewed in [17,18]) illustrate the use of peptides as potential agents to block PPIs. In fact, a number of recent publications has shown promising results on the use of peptides to blocks the entrance of SARS-CoV-2 virus using peptides derived from native element of the interaction humanACE2 and SARS-CoV-2 spike [19][20][21] including designed peptides targeting of the heptad repeat 1 region [22], the RBD domain [23][24][25], with validation in cell-cultures [26,27] and tissues [28]. While these approaches rely on the sequence diversification of existing native elements, ours complements these efforts by providing novel sequences (next).…”

Fruit Bromelain-Derived Peptide Potentially Restrains the Attachment of SARS-CoV-2 Variants to hACE2: A Pharmacoinformatics Approach

“…Notably, SARS-CoV-2 mutations in the RBD were not confined to these three variants. To date, several variants with various mutations in different positions have circulated world-wide, including the California, New York, Scotland, Nigeria, and Indian variants [ 6 , 7 , 8 , 9 , 10 ].…”

“…Recently, several studies have been directed toward investigating a peptide (a small part of a protein) that can prevent the binding of the SARS-CoV-2 RBD to hACE2 [ 8 , 9 , 10 ]. For example, an antiviral peptide is a form of antiviral agent that is intended to be used as a therapeutic agent against a particular disease, for example, COVID-19.…”

Inhibition Ability of Natural Compounds on Receptor-Binding Domain of SARS-CoV2: An In Silico Approach

“…The efficacy of many dietary flavanols as potential antiviral drugs for SARS-CoV-2 enzymes was performed by Patel et al using in silico assays and machine learning techniques [5]. Several other articles have studied the effectiveness of natural compounds in blocking the binding of the spike protein with the angiotensin-converting enzyme 2 (ACE2) receptor present on human cells [6][7][8][9][10][11]. Recent advances in machine learning (ML) methods have created the ability to identify new natural compounds for a given target [12,13].…”