Evidence Supporting the Use of Peptides and Peptidomimetics As Potential SARS-CoV-2 (COVID-19) Therapeutics

Abstract

During a disease outbreak/pandemic situation such as COVID-19, researchers are in a prime position to identify and develop peptide-based therapies, which could be more rapidly and cost-effectively advanced into a clinical setting. One drawback of natural peptide drugs, however, is their proteolytic instability; peptidomimetics can help to overcome this caveat. In this review, we summarize peptide and peptide-based therapeutics that target one main entry pathway of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which involves the host angiotensin-converting enzyme-2 (ACE2) receptor and viral spike (S) protein interaction. Furthermore, we discuss the advantages of peptidomimetics and other potential targets that have been studied using peptide-based therapeutics for COVID-19.

Techniques assisting peptide vaccine and peptidomimetic design. Sidechain exposure in the SARS-CoV-2 spike glycoprotein

“…There has also been a growing understanding of the biological properties of peptidomimetics that are partly or wholly composed of D-amino acid residues [ 34 ], and how to select those likely to have the required activity [ 35 ]. As noted by vanPatten et al, peptidomimetics based on D-amino acids have a very desirable property of resistance to a patient’s proteases, but other options include design of peptidomimetics with reduced and functionalized amide bonds, peptoids, urea peptidomimetics, peptide sulfonamides, oligocarbamates, azapeptides, β-peptides, and N-modified peptides [ 36 ].…”

“…While it is well known that D-peptides are far less immunogenic than many considered in such studies, it is also being seen that peptides containing D-amino acids can be immunogenic and raise antibodies in judicious laboratory conditions [ 34 ]. It is also the case that a reflect-complement-reflect approach based on phage display has been productive in peptidomimetic design [ 36 ]. In principle, use of the animal immune system for the reflect-complement-reflect method is likely to be the most powerful approach: there are processes of refinement and maturation of molecular recognition by the immune system that show considerable sophistication, even though not perhaps yet fully understood.…”

“…It is therefore pleasing that antibody and immune response have been obtained to SARS-COV-1 spike protein peptides (See Section 61 and e.g. Refs [ 16 , 17 ] [ 37 , 38 , 39 , 40 ]) and recently SARS-COV-2 spike protein peptides [ 36 , 37 , 38 , 39 , 40 ]. Importantly, D-amino acid retro-inverso peptides of somewhat similar size and amino acid content have long been shown to capable of raising antibodies when attached to a suitable carrier protein (e.g.…”

Microscopic Factors Modulating the Interactions Between the SARS-CoV-2 Main Protease and α−Ketoamide Inhibitors

“…Several new drugs targeting the SARS-CoV-2 main viral protease M pro (also called 3CL pro ) have been shown to be promising (or promising lead) compounds to develop new antiviral treatments for COVID-19. [1][2][3][4][5] All of these inhibitors have been built from standard docking approaches by inferring the microscopic factors modulating the strength of their interaction with M pro from experimental structural data and then selected from experimental trial-and-error approaches. To speed up the optimization process or the development of new M pro inhibitors, an information of pivotal importance is the knowledge of reliable data that accurately quantify the strength of the microscopic interactions at the origin of the stability of M pro /inhibitor complexes.…”

Using Artificial Intelligence to Reduce Global Healthcare Costs through Discovery and Development of Nutritional Interventions

“…By contrast, the identification of antimicrobial therapeutic peptides is just beginning, as recent research implemented ML methods to identify a peptide that is not only anti-microbial, but potent against Acinetobacter baumannii, a pan-drug resistant microbe [45]. Peptide therapeutic discovery, some of which also incorporate MLbased research, will also allow us to respond quickly to new emerging epidemics where traditional pharmaceuticals have yet to provide an adequate treatment, as has been demonstrated through the intense and promising investigation of peptides as potential SARS-CoV-2 (COVID-19) therapeutics [46][47][48]. Developing traditional pharmaceutical drugs is also costly, for example, one recent study found the cost of developing a cancer drug to be in the region of $648 million [49].…”