An insight into the epitope-based peptide vaccine design strategy and studies against COVID-19

Designing and development of efficient multi-epitope-based peptide vaccine candidate against emerging avian rotavirus strains: A vaccinomic approach

BACKGROUND

Enteric avian rotavirus (ARV) is the etiological agent of several health problems that pose a global threat to commercial chickens. Therefore, to avoid these widespread epidemics and high mortality rates, only vaccine and strict biosecurity are required.

METHOD

The present study employs computational techniques to design a unique multi-epitope-based vaccine candidate that successfully activates immune cells against the ARV by combining adjuvant, linker, and B and T-cell epitopes. Starting, homologous sequences in the various ARV serotypes were revealed in the NCBI BLAST database, and then the two surface proteins (VP4 and VP7) of the ARV were retrieved from the UniprotKB database. The Clustal Omega server was then used to identify the conserved regions among the homologous sequences, and the B and T-cell epitopes were predicted using IEDB servers. Then, superior epitopes-2 MHC-1 epitopes, 2 MHC-2 epitopes, and 3B-cell epitopes-were combined with various adjuvants to create a total of four unique vaccine candidates. Afterward, the designed vaccine candidates underwent computational validation to assess their antigenicity, allergenicity, and stability. The vaccine candidate (V2) that demonstrated non-antigenicity, a high VaxiJen score, and non-allergenicity was ultimately chosen for molecular docking and dynamic simulation.

RESULTS

Although the V2 and V4 vaccine candidates were highly immunogenic, V2 had a higher solubility rate. The predicted values of the aliphatic index and GRAVY value were 30.4 and 0.417, respectively. In terms of binding energy, V2 outperformed V4. Being successfully docked with TLRs, V2 was praised as the finest. After adaptation, the sequence's 50.73 % GC content outside of the BglII or ApaI restriction sites indicated that it was equivalently safe to clone. The chosen sequence was then inserted into the pET28a(+) vector within the BglII and ApaI restriction sites. This resulted in a final clone that was 4914 base pairs long, with the inserted sequence accounting for 478 bp and the vector accounting for the remainder.

CONCLUSIONS

The immune-mediated simulation results for the selected vaccine construct showed significant response; thus, the study confirmed that the selected V2 vaccine candidate could enhance the immune response against ARV.

Multi-epitope peptide vaccines targeting dengue virus serotype 2 created via immunoinformatic analysis

The Middle East has witnessed a greater spread of infectious Dengue viruses, with serotype 2 (DENV-2) being the most prevalent form. Through this work, multi-epitope peptide vaccines against DENV-2 that target E and nonstructural (NS1) proteins were generated through an immunoinformatic approach. MHC class I and II and LBL epitopes among NS1 and envelope E proteins sequences were predicted and their antigenicity, toxicity, and allergenicity were investigated. Studies of the population coverage denoted the high prevalence of NS1 and envelope-E epitopes among different countries where DENV-2 endemic. Further, both the CTL and HTL epitopes retrieved from NS1 epitopes exhibited high conservancies' percentages with other DENV serotypes (1, 3, and 4). Three vaccine constructs were created and the expected immune responses for the constructs were estimated using C-IMMSIM and HADDOCK (against TLR 2,3,4,5, and 7). Molecular dynamics simulation for vaccine construct 2 with TLR4 denoted high binding affinity and stability of the construct with the receptor which might foretell favorable in vivo interaction and immune responses.

Enhancing explainable SARS-CoV-2 vaccine development leveraging bee colony optimised Bi-LSTM, Bi-GRU models and bioinformatic analysis

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA virus that caused the outbreak of the coronavirus disease 2019 (COVID-19). The COVID-19 outbreak has led to millions of deaths and economic losses globally. Vaccination is the most practical solution, but finding epitopes (antigenic peptide regions) in the SARS-CoV-2 proteome is challenging, costly, and time-consuming. Here, we proposed a deep learning method based on standalone Recurrent Neural networks to predict epitopes from SARS-CoV-2 proteins easily. We optimised the standalone Bidirectional Long Short-Term Memory (Bi-LSTM) and Bidirectional Gated Recurrent Unit (Bi-GRU) with a bioinspired optimisation algorithm, namely, Bee Colony Optimization (BCO). The study shows that LSTM-based models, particularly BCO-Bi-LSTM, outperform all other models and achieve an accuracy of 0.92 and AUC of 0.944. To overcome the challenge of understanding the model predictions, explainable AI using the Shapely Additive Explanations (SHAP) method was employed to explain how Blackbox models make decisions. Finally, the predicted epitopes led to the development of a multi-epitope vaccine. The multi-epitope vaccine effectiveness evaluation is based on vaccine toxicity, allergic response risk, and antigenic and biochemical characteristics using bioinformatic tools. The developed multi-epitope vaccine is non-toxic and highly antigenic. Codon adaptation, cloning, gel electrophoresis assess genomic sequence, protein composition, expression and purification while docking and IMMSIM servers simulate interactions and immunological response, respectively. These investigations provide a conceptual framework for developing a SARS-CoV-2 vaccine.

Immunoinformatics Study: Multi-Epitope Based Vaccine Design from SARS-CoV-2 Spike Glycoprotein

The coronavirus disease 2019 outbreak has become a huge challenge in the human sector for the past two years. The coronavirus is capable of mutating at a higher rate than other viruses. Thus, an approach for creating an effective vaccine is still needed to induce antibodies against multiple variants with lower side effects. Currently, there is a lack of research on designing a multiepitope of the COVID-19 spike protein for the Indonesian population with comprehensive immunoinformatic analysis. Therefore, this study aimed to design a multiepitope-based vaccine for the Indonesian population using an immunoinformatic approach. This study was conducted using the SARS-CoV-2 spike glycoprotein sequences from Indonesia that were retrieved from the GISAID database. Three SARS-CoV-2 sequences, with IDs of EIJK-61453, UGM0002, and B.1.1.7 were selected. The CD8+ cytotoxic T-cell lymphocyte (CTL) epitope, CD4+ helper T lymphocyte (HTL) epitope, B-cell epitope, and IFN-γ production were predicted. After modeling the vaccines, molecular docking, molecular dynamics, in silico immune simulations, and plasmid vector design were performed. The designed vaccine is antigenic, non-allergenic, non-toxic, capable of inducing IFN-γ with a population reach of 86.29% in Indonesia, and has good stability during molecular dynamics and immune simulation. Hence, this vaccine model is recommended to be investigated for further study.

CD8+ T-cell immune escape by SARS-CoV-2 variants of concern

Despite the efficacy of antiviral drug repositioning, convalescent plasma (CP), and the currently available vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the worldwide coronavirus disease 2019 (COVID-19) pandemic is still challenging because of the ongoing emergence of certain new SARS-CoV-2 strains known as variants of concern (VOCs). Mutations occurring within the viral genome, characterized by these new emerging VOCs, confer on them the ability to efficiently resist and escape natural and vaccine-induced humoral and cellular immune responses. Consequently, these VOCs have enhanced infectivity, increasing their stable spread in a given population with an important fatality rate. While the humoral immune escape process is well documented, the evasion mechanisms of VOCs from cellular immunity are not well elaborated. In this review, we discussed how SARS-CoV-2 VOCs adapt inside host cells and escape anti-COVID-19 cellular immunity, focusing on the effect of specific SARS-CoV-2 mutations in hampering the activation of CD8⁺ T-cell immunity.

IntegralVac: A Machine Learning-Based Comprehensive Multivalent Epitope Vaccine Design Method

In the growing field of vaccine design for COVID and cancer research, it is essential to predict accurate peptide binding affinity and immunogenicity. We developed a comprehensive machine learning method, ‘IntegralVac,’ by integrating three existing deep learning tools: DeepVacPred, MHCSeqNet, and HemoPI. IntegralVac makes predictions for single and multivalent cancer and COVID-19 epitopes without manually selecting epitope prediction possibilities. We performed several rounds of optimization before integration, then re-trained IntegralVac for multiple datasets. We validated the IntegralVac with 4500 human cancer MHC I peptides obtained from the Immune Epitope Database (IEDB) and with cancer and COVID epitopes previously selected in our laboratory. The other data referenced from existing deep learning tools served as a positive control to ensure successful prediction was possible. As evidenced by increased accuracy and AUC, IntegralVac improved the prediction rate of top-ranked epitopes. We also examined the compatibility between other servers’ clinical checkpoint filters and IntegralVac. This was to ensure that the other servers had a means for predicting additional checkpoint filters that we wanted to implement in IntegralVac. The clinical checkpoint filters, including allergenicity, antigenicity, and toxicity, were used as additional predictors to improve IntegralVac’s prediction accuracy. We generated immunogenicity scores by cross-comparing sequence inputs with each other and determining the overlap between each individual peptide sequence. The IntegralVac increased the immunogenicity prediction accuracy to 90.1% AUC and the binding affinity accuracy to 95.4% compared to the control NetMHCPan server. The IntegralVac opens new avenues for future in silico methods, by building upon established models for continued prediction accuracy improvement.

A novel vaccine based on SARS-CoV-2 CD4+ and CD8+ T cell conserved epitopes from variants Alpha to Omicron

COVID-19 caused, as of September, 1rst, 2022, 599,825,400 confirmed cases, including 6,469,458 deaths. Currently used vaccines reduced severity and mortality but not virus transmission or reinfection by different strains. They are based on the Spike protein of the Wuhan reference virus, which although highly antigenic suffered many mutations in SARS-CoV-2 variants, escaping vaccine-generated immune responses. Multiepitope vaccines based on 100% conserved epitopes of multiple proteins of all SARS-CoV-2 variants, rather than a single highly mutating antigen, could offer more long-lasting protection. In this study, a multiepitope multivariant vaccine was designed using immunoinformatics and in silico approaches. It is composed of highly promiscuous and strong HLA binding CD4+ and CD8+ T cell epitopes of the S, M, N, E, ORF1ab, ORF 6 and ORF8 proteins. Based on the analysis of one genome per WHO clade, the epitopes were 100% conserved among the Wuhan-Hu1, Alpha, Beta, Gamma, Delta, Omicron, Mµ, Zeta, Lambda and R1 variants. An extended epitope-conservancy analysis performed using GISAID metadata of 3,630,666 SARS-CoV-2 genomes of these variants and the additional genomes of the Epsilon, Lota, Theta, Eta, Kappa and GH490 R clades, confirmed the high conservancy of the epitopes. All but one of the CD4 peptides showed a level of conservation greater than 97% among all genomes. All but one of the CD8 epitopes showed a level of conservation greater than 96% among all genomes, with the vast majority greater than 99%. A multiepitope and multivariant recombinant vaccine was designed and it was stable, mildly hydrophobic and non-toxic. The vaccine has good molecular docking with TLR4 and promoted, without adjuvant, strong B and Th1 memory immune responses and secretion of high levels of IL-2, IFN-γ, lower levels of IL-12, TGF-β and IL-10, and no IL-6. Experimental in vivo studies should validate the vaccine's further use as preventive tool with cross-protective properties.

Predicting epitopes for vaccine development using bioinformatics tools

Epitope-based DNA vaccine development is one application of bioinformatics or in silico studies, that is, computational methods, including mathematical, chemical, and biological approaches, which are widely used in drug development. Many in silico studies have been conducted to analyze the efficacy, safety, toxicity effects, and interactions of drugs. In the vaccine design process, in silico studies are performed to predict epitopes that could trigger T-cell and B-cell reactions that would produce both cellular and humoral immune responses. Immunoinformatics is the branch of bioinformatics used to study the relationship between immune responses and predicted epitopes. Progress in immunoinformatics has been rapid and has led to the development of a variety of tools that are used for the prediction of epitopes recognized by B cells or T cells as well as the antigenic responses. However, the in silico approach to vaccine design is still relatively new; thus, this review is aimed at increasing understanding of the importance of in silico studies in the design of vaccines and thereby facilitating future research in this field.

The role of microbiota in colorectal cancer

Cancer is one of the most important causes of death throughout the world, and the mortality rate is increasing significantly due to the aging of the population. One of the most common types of cancer is colorectal cancer (CRC). Human microbial ecosystems use metabolism to make important impacts on the body physiology. An intensive literature review was made to investigate the correlations between human gut microbiota and the incidence of CRC. The results of these studies show that there are differences in the composition of microbiota between CRC patients and normal people and the microorganisms in CRC patients are very different from healthy individuals. Therefore, changes in the microbiome can be used as a biomarker for the early detection of CRC. On the other hand, the intestinal flora is may be act as a powerful weapon against CRC in the future.

Peptides for Vaccine Development

This review discusses peptide epitopes used as antigens in the development of vaccines in clinical trials as well as future vaccine candidates. It covers peptides used in potential immunotherapies for infectious diseases including SARS-CoV-2, influenza, hepatitis B and C, HIV, malaria, and others. In addition, peptides for cancer vaccines that target examples of overexpressed proteins are summarized, including human epidermal growth factor receptor 2 (HER-2), mucin 1 (MUC1), folate receptor, and others. The uses of peptides to target cancers caused by infective agents, for example, cervical cancer caused by human papilloma virus (HPV), are also discussed. This review also provides an overview of model peptide epitopes used to stimulate non-specific immune responses, and of self-adjuvanting peptides, as well as the influence of other adjuvants on peptide formulations. As highlighted in this review, several peptide immunotherapies are in advanced clinical trials as vaccines, and there is great potential for future therapies due the specificity of the response that can be achieved using peptide epitopes.

Therapeutic peptides: current applications and future directions

Peptide drug development has made great progress in the last decade thanks to new production, modification, and analytic technologies. Peptides have been produced and modified using both chemical and biological methods, together with novel design and delivery strategies, which have helped to overcome the inherent drawbacks of peptides and have allowed the continued advancement of this field. A wide variety of natural and modified peptides have been obtained and studied, covering multiple therapeutic areas. This review summarizes the efforts and achievements in peptide drug discovery, production, and modification, and their current applications. We also discuss the value and challenges associated with future developments in therapeutic peptides.

Cytotoxic T-Cell-Based Vaccine against SARS-CoV-2: A Hybrid Immunoinformatic Approach

This paper presents an alternative vaccination platform that provides long-term cellular immune protection mediated by cytotoxic T-cells. The immune response via cellular immunity creates superior resistance to viral mutations, which are currently the greatest threat to the global vaccination campaign. Furthermore, we also propose a safer, more facile, and physiologically appropriate immunization method using either intranasal or oral administration. The underlying technology is an adaptation of synthetic long peptides (SLPs) previously used in cancer immunotherapy. The overall quality of the SLP constructs was validated using in silico methods. SLPs comprising HLA class I and class II epitopes were designed to stimulate antigen cross-presentation and canonical class II presentation by dendritic cells. The desired effect is a cytotoxic T cell-mediated prompt and specific immune response against the virus-infected epithelia and a rapid and robust virus clearance. Epitopes isolated from COVID-19 convalescent patients were screened for HLA class I and class II binding (NetMHCpan and NetMHCIIpan) and highest HLA population coverage (IEDB Population Coverage). 15 class I and 4 class II epitopes were identified and used for this SLP design. The constructs were characterized based on their toxicity (ToxinPred), allergenicity (AllerCatPro), immunogenicity (VaxiJen 2.0), and physico-chemical parameters (ProtParam). Based on in silico predictions, out of 60 possible SLPs, 36 candidate structures presented a high probability to be immunogenic, non-allergenic, non-toxic, and stable. 3D peptide folding followed by 3D structure validation (PROCHECK) and molecular docking studies (HADDOCK 2.4) with Toll-like receptors 2 and 4 provided positive results, suggestive for favorable antigen presentation and immune stimulation.

Peptide Multimerization as Leads for Therapeutic Development

Multimerization of peptide structures has been a logical evolution in their development as potential therapeutic molecules. The multivalent properties of these assemblies have attracted much attention from researchers in the past and the development of more complex branching dendrimeric structures, with a wide array of biocompatible building blocks is revealing previously unseen properties and activities. These branching multimer and dendrimer structures can induce greater effect on cellular targets than monomeric forms and act as potent antimicrobials, potential vaccine alternatives and promising candidates in biomedical imaging and drug delivery applications. This review aims to outline the chemical synthetic innovations for the development of these highly complex structures and highlight the extensive capabilities of these molecules to rival those of natural biomolecules.

Does immune recognition of SARS-CoV2 epitopes vary between different ethnic groups?

The SARS-CoV2 mediated Covid-19 pandemic has impacted humankind at an unprecedented scale. While substantial research efforts have focused towards understanding the mechanisms of viral infection and developing vaccines/ therapeutics, factors affecting the susceptibility to SARS-CoV2 infection and manifestation of Covid-19 remain less explored. Given that the Human Leukocyte Antigen (HLA) system is known to vary among ethnic populations, it is likely to affect the recognition of the virus, and in turn, the susceptibility to Covid-19. To understand this, we used bioinformatic tools to probe all SARS-CoV2 peptides which could elicit T-cell response in humans. We also tried to answer the intriguing question of whether these potential epitopes were equally immunogenic across ethnicities, by studying the distribution of HLA alleles among different populations and their share of cognate epitopes. Results indicate that the immune recognition potential of SARS-CoV2 epitopes tend to vary between different ethnic groups. While the South Asians are likely to recognize higher number of CD8-specific epitopes, Europeans are likely to identify higher number of CD4-specific epitopes. We also hypothesize and provide clues that the newer mutations in SARS-CoV2 are unlikely to alter the T-cell mediated immunogenic responses among the studied ethnic populations. The work presented herein is expected to bolster our understanding of the pandemic, by providing insights into differential immunological response of ethnic populations to the virus as well as by gaging the possible effects of mutations in SARS-CoV2 on efficacy of potential epitope-based vaccines through evaluating ∼40,000 viral genomes.

Introduction of novel putative immunogenic targets against Proteus mirabilis using a reverse vaccinology approach

Multi-drug resistance of Proteus mirabilis, a frequent cause of catheter-associated urinary tract infections, renders ineffective treatment. Therefore, new advanced strategies are needed to overcome it. In the meantime, vaccination may be the most effective and promising method. In this study antigenicity, allergenicity, subcellular localization, human homology, B-cell epitopes and MHC-II binding sites, conserved domains and protein-protein interactions were predicted using different reverse vaccinology methods and bioinformatics databases to find new putative immunogenic targets against P. mirabilis. Finally, 5 putative immunogenic targets against P. mirabilis were identified. Considering all criteria, QKQ94350.1 (Cell envelope opacity-associated protein A), QKQ94681.1 (Porin), QKQ95001.1 (TonB-dependent hemoglobin/ transferrin/ lactoferrin family receptor), QKQ95221.1 (AsmA) and QKQ94335.1 (N-acetylmuramoyl-L-alanine amidase) are excellent putative immunogenic targets. Finally, a multi-epitope vaccine was designed using the conserved linear epitopes of two OMPs (QKQ94681.1 and QKQ95001.1) and N-acetylmuramoyl-L-alanine amidase (QKQ94335.1), which have promising properties for immunization. These findings can simplify the development of efficient vaccines against P. mirabilis.

Various theranostics and immunization strategies based on nanotechnology against Covid-19 pandemic: An interdisciplinary view

COVID-19 pandemic is still a major risk to human civilization. Besides the global immunization policy, more than five lac new cases are documented everyday. Some countries newly implement partial/complete nationwid lockdown to mitigate recurrent community spreading. To avoid the new modified stain of SARS-CoV-2 spreading, some countries imposed any restriction on the movement of the citizens within or outside the country. Effective economical point of care diagnostic and therapeutic strategy is vigorously required to mitigate viral spread. Besides struggling with repurposed medicines, new engineered materials with multiple unique efficacies and specific antiviral potency against SARS-CoV-2 infection may be fruitful to save more lives. Nanotechnology-based engineering strategy sophisticated medicine with specific, effective and nonhazardous delivery mechanism for available repurposed antivirals as well as remedial for associated diseases due to malfeasance in immuno-system e.g. hypercytokinaemia, acute respiratory distress syndrome. This review will talk about gloomy but critical areas for nanoscientists to intervene and will showcase about the different laboratory diagnostic, prognostic strategies and their mode of actions. In addition, we speak about SARS-CoV-2 pathophysiology, pathogenicity and host specific interation with special emphasis on altered immuno-system and also perceptualized, copious ways to design prophylactic nanomedicines and next-generation vaccines based on recent findings.

Bursal peptide BP-IV as a novel immunoadjuvant enhances the protective efficacy of an epitope peptide vaccine containing T and B cell epitopes of the H9N2 avian influenza virus

Short peptide antigens covering conserved T or B cell epitopes have been investigated in influenza vaccines. Bursal pentapeptide V (BPP-V) and bursal peptide IV (BP-IV) are small molecular peptides that were isolated and identified from the bursa of Fabricius (BF) and induce a strong immune response at both the humoural and cellular levels. To explore the molecular adjuvant potential of BPP-V and BP-IV with an epitope vaccine, an epitope peptide (HA_284-298, GNCVVQCQTERGGLN) rich in T and B cell epitopes for the H9N2 avian influenza virus (AIV) haemagglutinin (HA) protein was selected. BPP-V and BP-IV were coupled with the epitope peptide sequence to form BPP-V and BP-IV-epitope vaccines, respectively. The immunoefficacy of BPP-V and BP-IV-epitope peptide vaccines was evaluated. The results showed that the epitope peptide had weak immunogenicity. The BPP-V-epitope peptide vaccine promoted only the secretion of anti-HA IgG and IgG1 antibodies. The BP-IV-epitope peptide vaccine not only promoted the production of anti-HA IgG and IgG1 antibodies but also significantly induced the production of the IgG2a antibody. The BP-IV-epitope peptide vaccine significantly promoted the production of interleukin (IL-4) and interferon-γ (IFN-γ) (the BPP-V epitope peptide vaccine promoted only the production of IL-4), enhanced the cytotoxic T lymphocyte (CTL) response, and increased the proportion of CD3⁺ T lymphocytes. Moreover, the BP-IV-epitope peptide vaccine promoted a cell-mediated immune response similar to that of the AIV vaccine group. Furthermore, BPP-V and BP-IV-epitope peptide vaccines could also accelerate the clearance of pulmonary virus and reduce pathological damage after the challenge with H9N2 AIV. This study demonstrates the potential of BP-IV as an effective adjuvant for the epitope peptide vaccine for the H9N2 AIV.

A computational study to disclose potential drugs and vaccine ensemble for COVID-19 conundrum

The nucleocapsid (N) protein of SARS-COV-2, a virus responsible for the current COVID-19 pandemic, is considered a potential candidate for the design of new drugs and vaccines. The protein is central to several critical events in virus production, with its highly druggable nature and rich antigenic determinants making it an excellent anti-viral biomolecule. Docking-based virtual screening using the Asinex anti-viral library identified binding of drug molecules at three specific positions: loop 1 region, loop 2 region and β-sheet core pockets, the loop 2 region being the most common binding and stable site for the bulk of the molecules. In parallel, the protein was characterized by vaccine design perspective and harboured three potential B cell-derived T cell epitopes: PINTNSSPD, GVPINTNSS, and DHIGTRNPA. The epitopes are highly antigenic, virulent, non-allergic, non-toxic, bind with good affinity to the highly prevalent DRB*0101 allele and show an average population coverage of 95.04%. A multi-epitope vaccine ensemble which was 83 amino acids long was created. This was highly immunogenic, robust in generating both humoral and cellular immune responses, thermally stable, and had good physicochemical properties that could be easily analyzed in in vivo and in vitro studies. Conformational dynamics of both drug and vaccine ensemble with respect to the receptors are energetically stable, shedding light on favourable conformation and chemical interactions. These facts were validated by subjecting the complexes to relative and absolute binding free energy methods of MMGB/PBSA and WaterSwap. A strong agreement on the system stability was disclosed that supported ligand high affinity potential for the receptors. Collectively, this work sought to provide preliminary experimental data of existing anti-viral drugs as a possible therapy for COVID-19 infections and a new peptide-based vaccine for protection against this pandemic virus.

Antimicrobial and Amyloidogenic Activity of Peptides. Can Antimicrobial Peptides Be Used against SARS-CoV-2?

At present, much attention is paid to the use of antimicrobial peptides (AMPs) of natural and artificial origin to combat pathogens. AMPs have several points that determine their biological activity. We analyzed the structural properties of AMPs, as well as described their mechanism of action and impact on pathogenic bacteria and viruses. Recently published data on the development of new AMP drugs based on a combination of molecular design and genetic engineering approaches are presented. In this article, we have focused on information on the amyloidogenic properties of AMP. This review examines AMP development strategies from the perspective of the current high prevalence of antibiotic-resistant bacteria, and the potential prospects and challenges of using AMPs against infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Peptides: Prospects for Use in the Treatment of COVID-19

There is a vast practice of using antimalarial drugs, RAS inhibitors, serine protease inhibitors, inhibitors of the RNA-dependent RNA polymerase of the virus and immunosuppressants for the treatment of the severe form of COVID-19, which often occurs in patients with chronic diseases and older persons. Currently, the clinical efficacy of these drugs for COVID-19 has not been proven yet. Side effects of antimalarial drugs can worsen the condition of patients and increase the likelihood of death. Peptides, given their physiological mechanism of action, have virtually no side effects. Many of them are geroprotectors and can be used in patients with chronic diseases. Peptides may be able to prevent the development of the pathological process during COVID-19 by inhibiting SARS-CoV-2 virus proteins, thereby having immuno- and bronchoprotective effects on lung cells, and normalizing the state of the hemostasis system. Immunomodulators (RKDVY, EW, KE, AEDG), possessing a physiological mechanism of action at low concentrations, appear to be the most promising group among the peptides. They normalize the cytokines' synthesis and have an anti-inflammatory effect, thereby preventing the development of disseminated intravascular coagulation, acute respiratory distress syndrome and multiple organ failure.