Open access peer-reviewed chapter

Perspective Chapter: Repurposing Natural Products to Target COVID-19 – Molecular Targets and New Avenues for Drug Discovery

Written By

Farid A. Badria

Submitted: 20 October 2021 Reviewed: 09 February 2022 Published: 06 May 2022

DOI: 10.5772/intechopen.103153

From the Edited Volume

Antiviral Drugs - Intervention Strategies

Edited by Farid A. Badria

Chapter metrics overview

138 Chapter Downloads

View Full Metrics

Abstract

World Health Organization (WHO) declared on March 11, 2020, coronavirus disease, which erupted in December 19th, 2019 in Wuhan, China (COVID-19) as worldwide pandemic disease. Researchers worldwide were successful to provide a prophylactic approach via developing several vaccines, which were swiftly approved by WHO under Emergency Use Listing (EUL) status. So far, lopinavir, chloroquine, azithromycin, hydroxychloroquine, favipiravir, umifenovir, ribavirin, remdesivir, and darunavir have been tested clinically. Hydroxychloroquine, favipiravir, and chloroquine exhibited a high ratio of distribution for the lung and were reported to minimize viral tonnage in respiratory system of many COVID-19 cases. However, none of the tested drugs showed a conclusive, safe, and efficient activity against COVID-19. This prompted many experts in drug discovery to fetch in the treasure of many available old drugs of natural origin to repurpose based upon their well-studied pharmacology, pharmacodynamics, virtual screening, and artificial intelligence studies. In this review chapter, we will address the repurposing of natural products and their derivatives to be used in treatment of COVID-19 via targeting host cells machinery and viral proteins either in early stages by blocking virus entry to cells or lately through inhibition of viral replication.

Keywords

  • COVID-19
  • inflammation
  • viral replication
  • drug repurposing
  • artificial intelligence
  • natural products

1. Introduction

SARS-CoV-2 is a relatively large virus with single-stranded RNA genome, belongs to beta coronaviruses that affects the lower respiratory system to cause viral pneumonia. The gastrointestinal system, kidney, heart, liver, and central nervous system may also be attacked leading to multiple organ failure. It is surrounded by an envelope composed of a lipid bilayer and envelope proteins [1].

1.1 The life cycle of COVID-19

The COVID-19 viral infection is mediated by three main stages: the first one involves host cell entry through endocytosis and transportation proteins; the second stage initiates viral RNA translation to polyprotein, which is subjected to cleavage by the main viral proteinases Mpro and Papain-like proteases PLpro to produce the effector proteins; in the final stage, the negative-strand viral RNA is translocated to the Golgi apparatus to produce new virions, and the newly produced virus are released by exocytosis [1].

1.2 Host cell viral entry and nuclear translocation

The viral entry was found to be mediated by endocytic pathways, which is initiated by the binding of spike protein (S protein), a protein found on the envelope of the virus, to a receptor protein located on the host cell surface membrane, known as angiotensin-converting enzyme 2 (ACE2). The S protein is cleaved into S1 and S2 by a human cell-derived protease that is assumed to be Furin. S1 then binds to its receptor, ACE2. The other fragment, S2, is cleaved by TMPRSS2, a serine protease. Thus, ACE2 and TMPRSS2 are essential in airway cells for SARS-CoV-2 infection [2].

Also the viral entry was found to be facilitated through endocytosis [3], especially clathrin-mediated endocytosis (CME) helps in translocation of ACE-2/virus complex to endosome where the virus is uncoated by the action of acidic proteases such as cathepsins, which are cysteine proteases in host cells involved in facilitating viral entry of several viruses such as SARS-COV and MERS-COV [4]. It’s worthy to note that cathepsins are also involved in S protein cleavage [5, 6].

After uncoating, the viral RNA expression and replication require subcellular localization of viral and cellular proteins from cytoplasm to the nucleus. The viral infection induces the translocation and expression of group of suprafamily protein in the host cells called karyopherin, Importins (IMP) α/β heterodimer. These proteins are reported to be utilized by the virus not only for translocation purposes, but also for disruption of self-antiviral defenses in response to interferon via intervening with the nuclear import of signal transducer and activator of transcription proteins (STAT). Chromosome Region Maintenance-1 (CRM1) is one of those proteins that contribute significantly in nuclear export of viral protein and RNA in wide range of viruses [7].

1.3 Translation of viral RNA to nonstructural protein

The SARS-Cov-2 genome has a large replicase gene, which contains nonstructural proteins (NSPs), structural proteins, and accessory genes. The replicase gene encodes two open reading frames (ORFs) after frameshifting, translated into two large polyproteins pp1a and pp1ab, then processed by two viral proteases: papain-like protease (PLpro, encoded within Nsp3) and Mpro aslo called 3C-like protease (3CLpro, encoded by Nsp5) to produce 16 viral Nsps that their function has been linked to RNA replication. PLpro is believed to play important role to protect the virus from immune response by inactivating ubiquitin-dependent cellular responses to viral infection and blocking of cytokine production [8, 9].

1.4 Genome replication and production of new viruses

After cell invasion, a full-length negative-strand RNA template is synthesized by nonstructural protein 12 (Nsp12) RNA-dependent RNA polymerase (RdRp) to produce more viral genomic RNA [10].

Another important nonstructural protein is RNA helicase, which has main role in the replication of viruses by catalyze unwinding of double-stranded RNA. It is structurally conserved among different types of viruses, thereby making it an excellent target for development of broad-spectrum antiviral agents [11, 12].

1.5 Translation of structural protein virion assembly and release

In this stage, the viral RNA is translocated to endoplasmic reticulum (ER) where it is translated to transmembrane structural proteins (S, HE, M, and E) and some membrane-associated accessory proteins, except for the N protein, which is translated by free ribosomes in the cytoplasm [13]. These structural proteins play the main role in virion morphogenesis and the structural components recruitment to the proper assembly site. Then they are released from the cell by exocytosis by the help of several host factors [14].

However, in the COVID-19 pandemic, an integrated approach encompassing prophylaxis, diagnosis, and treatment must be adopted worldwide.

Advertisement

2. Approaches for prophylaxis, diagnosis, and therapy

Among the top priorities for regulating and monitoring COVID-19 are:

  1. An appropriate prophylactic procedure (vaccination).

  2. Accurate diagnostic battery.

  3. An unambiguous therapeutic regimen.

2.1 An appropriate prophylactic procedure (vaccination)

WHO stated that “vaccine must supply a quite convenient beneficial environment for dealing with jeopardy; with high performance, only passing with mild effects and with no danger effects.” The vaccine should be appropriate for lactating, gravid women and for all ages and has many production sources dwell in high-, middle-, and low-income countries [15]. There is a race among several pharmaceutical companies to provide a treatment for COVID-19. Unfortunately, this completion had led to a big controversy, which was refuted by WHO issued on 20 November 2020 “there is a conditional recommendation against the use of remdesivir since there isn’t enough evidence to support its use.” Moreover, WHO has issued a conditional recommendation against the use of remdesivir in hospitalized patients, regardless of disease severity, as there is currently no evidence that remdesivir improves survival and other outcomes in these patients (https://www.who.int/news-room/feature-stories/detail/who-recommends-against-the-use-of-remdesivir-in-covid-19-patients).

However, by the end of 2020 (exactly December 2020), Pfizer/BioNTech was able to get an Emergency Use Listing approval (EUL) for vaccine against COVID-19. Currently and as reported by on January 20th, 2022, nine vaccines were granted EUL status [16, 17].

  • The Pfizer/BioNTech Comirnaty vaccine, 31 December 2020.

  • The SII/COVISHIELD and AstraZeneca/AZD1222 vaccines, 16 February 2021.

  • The Janssen/Ad26.COV 2.S vaccine developed by Johnson & Johnson, 12 March 2021.

  • The Moderna COVID-19 vaccine (mRNA 1273), 30 April 2021.

  • The Sinopharm COVID-19 vaccine, 7 May 2021.

  • The Sinovac-CoronaVac vaccine, 1 June 2021.

  • The Bharat Biotech BBV152 COVAXIN vaccine, 3 November 2021.

  • The Covovax (NVX-CoV2373) vaccine, 17 December 2021.

  • The Nuvaxovid (NVX-CoV2373) vaccine, 20 December 2021

2.2 Diagnosis

2.2.1 Clinical laboratory

  • The clinical laboratory is an important and essential tool for the diagnosis, follow-up, and evolution, as well as in the prognosis of any pathology that is active or not. In the COVID-19 pandemic, several biomarkers’ involvement as indicators of the disease’s current state has been reported, while others have proved to be useful prognostic markers. Some of these characteristics are as follows [18].

  • General laboratory findings in SARS-CoV-2 infection sometimes indicate leukocytosis or leukopenia, with marked lymphopenia in the disease’s first stages. Besides, the neutrophilia presence has been related to an unfavorable prognosis [19].

  • Thrombocytopenia, lymphopenia, thrombocytopenia, D-dimer, elevated C-reactive protein (CRP) (happened repeatedly in critical cases), and leukopenia are not distinctive laboratory factors [20].

  • COVID-19 patients who have diabetes mellitus of type 2 (T2DM) expressed minimized levels of lymphocytes, body mass index (BMI), albumin, and uric acid (UA), and increased CRP levels. The reduced levels of albumin, UA, and BMI may be related to nutritional consumption and oxidative stress response. The increased CRP levels and decreased lymphocyte counts may be related to the infection [21].

2.2.2 Imaging

Medical imaging, such as Computed Tomography (CT) and X-ray, plays a significant function in the combat against the pandemic. So, the current AI methods can be used to help medical specialists and strengthen imaging tools. Also, AI could also increase work performance by effective detection of CT and X-ray diseases. The Computer-Aided Diagnosis (CAD) models enable physicians to take correct clinical choices on disease diagnosis, monitoring, and prognosis [22]. Many radiological characteristics are used to categorize the disease and help in discovering the treatment, such as the following:

  • The most direct method to identify the degree of disease is imaging, as it is effective and accurate. Consolidation and diffuse lesions are features of severe pneumonia. Doubled ground-glass opacity, unification, and interlobular septal thick ply in the right and left lungs are the popular chest CT discoveries for COVID-19, which are particularly spread under the pleura. The serious part of the pandemic diagnosis and examination is computed tomography [23].

  • A sensitive examination method is called spiral CT. It can be used for diagnosis in the early stages and estimation of development. This method has diagnostic allergy and precision preferable to the disclosure of nucleic acid [24]. During the first week of the illness, appearance and blended predominance with opacity in the lower lung are quite dubious of COVID-19. However, few illness cases may have a normal chest outcome despite positive testing for COVID-19 [25].

  • The proportion of infected cases with mild COVID-19 symptoms was relatively high-rise. Misdiagnosis in some cases can result from checking for COVID-19 with only chest CT, which would result in a possibility of contagion risk. It was not appropriate as a separate screening device. Visual, quantitative interpretation depended on CT images with great diagnostic capability and good matchmaking. It can help in clinical classification; it is predictable to strictly evaluate the severe COVID-19 cases and combining with the clinical information to guide the clinical treatment [26].

2.3 Therapy

Therapeutic interferences can be categorized into four main classes: general treatment, antiviral treatments, particular medications, and other medications.

The effectiveness and safety of COVID-19 have been tested using several drugs, such as chloroquine, remdesivir, favipiravir, and hydroxychloroquine. Some of them had presented antiviral impacts against COVID-19 but no conclusive evidences [27].

Although the serious disease has been related to hyperinflammation induced by COVID-19, the immune responses of acute COVID-19 stay ambiguous. Some researchers comprehensively analyzed circumferential immune troubles in blood for 42 recovered and infected by COVID-19. The activation of various immune strains is recognized, including oligoclonal plasmablast expansion, trafficking receptor modulation on granulocytes, innate lymphocytes, and T cell activation, which separated acute COVID-19 patients or moderate-severe patients from healthy donors or COVID-19-recovered. One of the predictive biomarkers is the ratio between neutrophil and lymphocyte of organ failure and disease gravity. Results appeared wide innate and adaptive leukocyte annoyances that characterize dysregulated have an infection in extreme COVID-19 disease, and medication examination is required. There were no efficacious antiviral medications, even common drugs with strong effect as abidol, ritonavir/lopinavir showed no exceptional impact on clinical progression, virus clearance, or deaths [28].

The meta-analysis of corticosteroid treatment and available observational studies suggested maximized death rates and subaltern contagion rates in influenza, maximized viremia, weakened antibody response, and weakened infection riddance MERS-CoV and SARS-CoV, and corticosteroid treatment complications in recovered patients [29]. Therefore, in the medication of COVID-19, corticosteroids should not be supported or even applied for acute patients.

The plasma of convalescent for severe influenza infection and SARS-CoV medication was proposed to minimize the mortality rate and days number in hospital, particularly after symptom appearance and administered plasma early [30].

As for inoculation, if any cross-reactive epitopes were recognized among COVID-19 and SARS-CoV, the preceding vaccine of SARS-CoV might be reused to expedite the COVID-19 vaccine progression. It is recommended for prophylaxis, streptococcus pneumonia, and influenza vaccination, especially in the elderly [31].

2.4 Drug repurposing and COVID-19

Drug repurposing is also a quick tool that creates a shortcut to find a safe and effective therapy for this exciting pandemic. It depends on the fact that their safety profile, side effects, posology, and drug interactions are well known [27]. Currently, several FDA-approved drugs are tested for their potential to treat COVID-19 infection such as lopinavir, chloroquine, azithromycin, hydroxychloroquine, favipiravir, umifenovir, ribavirin, remdesivir, and darunavir have been tested in many COVID-19 clinical experiments for hopeful use under emergency protocol. Unfortunately, none of these tested drugs showed a conclusive results and satisfactory outcomes among treated patients. Therefore, several studies used in silico tools for prediction of the ability of drugs to interact with molecular targets important for viral replications.

In that aspect, the liver research laboratory (FAB-Lab, Faculty of Pharmacy, Mansoura University, Mansoura, Egypt) has applied several approaches for not only improving the pharmacological effect of easily accessible natural products, but also identifying new applications for them. Drug repositioning or repurposing may reveal a new approach to rediscover new uses for clinically approved existing old drugs [32].This book revealed the theory, applications, and/or hazardous outcomes on drug discovery in different disciplines in medicine; e.g. dermatology [33, 34], cancer [35, 36, 37], and neurological disorders [38].

A hopeful mechanism to cure COVID-19 patients is the reusing of trusted antiviral treatments in opposition to COVID-19. Viral loads are reduced by employing the antiviral treatments that have risen lung allocations, which is helpful to COVID-19 cases. There are a number of antiviral medications such as [39].

2.4.1 Natural products inhibitors for targeting COVID-19

Some results depended on molecular docking and network direct pharmacology action on COVID-19, for examples:

  • Kaempferol, aloe-emodin, quercetin, luteolin, forsythoside E, rutin, and hyperoside in Lianhua Qinwen might be the buoyant components in hindering COVID-19 by computer-assisted treatment design (CADD) of virtual checking and network pharmacology analysis through JAK-STAT signaling pathway [40, 41, 42].

  • Patchouli alcohol, saikosaponin ergosterol, 23-acetate alisol B, shionone, B (Bupleuri Radix) could act straight on the COVID-19 3CL pro to restrain infection multiplication. On differentiate, shionone (Asteris Radix et Rhizoma), tussilagone, patchouli alcohol, asarinin, ephedrine hydrochloride, and ergosterol might work on steward cells ACE2 to restrain the attack [43, 44, 45, 46].

  • Licorice glycoside E, (2R)-7-hydroxy-2-(4-hydroxyphenyl) chroman-4-ketone, robinin, naringenin, quercetin, kaempferol, irisolidone, and isorhamnetin from Huoxiang Zhengqi as 3CL pro restraints, which may block COVID-19 repetition by focusing on E2F1 and PIK3CG by PI3K-Akt signaling path [44]. Rosmarinic acid could block virus repetition through the PI3K-Akt signal path [47].

  • Quercetin, Kaempferol, luteolin, baicalein, glyasperin C, licochalcone B, and oroxylin A were suggested to tie with organizing different signals paths and ACE2, as BCL2, PTGS2, Kaposi sarcoma-related herpesvirus contagion, CASP3, hepatitis C, Epstein-Barr virus infection, measles, and human cytomegalovirus contagion.

  • Baicalein, kaempferol, luteolin, rhubarb wogonin, and quercetin had a great partiality with COVID-19 3CL hydrolase [48].

As previously explained, nonstructural proteins of COVID-19 and several factors and receptors in host cells are essential for viral entry and replication, which means that both should be considered in the process of the development of effective antiviral agents as depicted in Figure 1. In this section, we will address known natural products inhibitors to the key targets controlling viral entry and replication.

Figure 1.

Different approaches for targeting viral entry and replication of the COVID-19. (1) Inhibition of S protein binding to ACE2, (2) disruption of endocytic pathways, (3) inhibition of nuclear translocation of viral RNA and protein by host cell mediators, (4) inhibition of the proteolysis of viral polyprotein to the nonstructural proteins (Nsp), (5) inhibition of transcription and replication of viral RNA.

2.4.1.1 Inhibition of viral invasion process

2.4.1.1.1 Inhibition of SARS-CoV-2 lipid-dependent attachment to host cells

Targeting host lipids is an intriguing antiviral strategy. Coronaviruses are a class of viruses with a lipid envelope that requires a plasma membrane fusion process mediated by endocytosis, a mechanism that involves certain cholesterol-rich microdomains and its ACE2 receptor [49] and mediates the early stages of internalization of coronaviruses [50].

Macromolecules such as methyl-β-cyclodextrin have been used to inhibit attachment of coronaviruses to host cells. These nontoxic macromolecules mimic attack sites for the enveloped virus, competing with host cell attack sites. It could also decrease ACE2 expression in the cell membrane, thereby reducing the infectivity of coronaviruses, such as SARS-CoV-2 [51].

Natural compounds including phytosterols and triterpenes (Figure 2) can exert the same action. For example, betulinic acid also has the same lipophilic properties as cholesterol, so it may therefore compete with cholesterol, replacing it in plasma membranes, or it may bind to the virus instead of raft cholesterol, acting as a soluble competitor [52].

Figure 2.

Chemical structures of the most common phytosterols. They are considered as potential inhibitors of SARS-CoV-2 lipid-dependent attachment to host cells, a possible approach for decreasing its infectivity.

2.4.1.1.2 Blocking the viral entry process by inhibiting TMPRSS2 activity

TMPRSS2, a human cell surface serine protease, results in membrane fusion. ACE2 and TMPRSS2 are essential in airway cells for SARS-CoV-2 infection [53]. ACE2 inhibition should not be tracked as a treatment strategy as ACE inhibitors upregulate the expression of ACE receptors providing more binding sites for SARS-CoV-2. On the other hand, blocking TMPRSS2 is accessible and will prevent the fusion of the envelope of the virus with host cell surface membranes. Nafamostat, an existing safe drug used for pancreatitis, may inhibit SARS-CoV-2 entry by inhibiting TMPRSS2 activity.

In this context, several reported serine protease inhibitors from nature could be repurposed to target TMPRSS2.

Potent serine protease inhibitors have been reported from filamentous marine cyanobacteria. Most of these molecules are 3-amino-6 hydroxy-piperidone (AHP-containing cyclic depsipeptides). The AHP moiety is crucial for serine protease inhibitory activity, and any structural or conformational variations to this unit will affect activity (Figure 3) [54].

Figure 3.

Serine protease inhibitors isolated from marine cyanobacteria. Potential blockers for the requisite viral entry process (inhibition of the S protein-initiated membrane fusion by inhibiting TMPRSS2 activity).

2.4.1.1.3 Inhibition of endocytic pathway.

2.4.1.1.3.1 Increase of the endosomal and lysosomal pH using lysosomotropism agents

It’s now well established that endocytosis is the nick bottle for COVID-19 entry to the host cells, thus inhibiting this pathway could reduce the infectivity of the virus dramatically. This could be achieved by increasing of the endosomal and lysosomal pH using lysosomotropism agents, which disrupt the proteolytic action of host cell proteases, which work optimally in acidic pH and prevent the cleavage of the S Protein of the virus [55]. While chloroquine (CQ) and its derivative are developed originally for treatment of malaria, but since they demonstrated potent activity by direct acting on the virus and by preventing its endocytosis, they were repurposed for treatment of several viral infection and currently used widely used in therapeutic protocol for treatment of COVID-19 [56]. Bafilomycin A1, a vacuolar-type H+−ATPase inhibitor, lies in the same category and could explain the use of azithromycin, a structurally related macrolide antibiotic for treatment of COVID-19 patients [57].

2.4.1.1.3.2 Cathepsins inhibitors

Inhibition of cysteine proteases such as cathepsins could be an important approach due to their role in viral entry, and luckily the incorporation of these protein in the pathogenesis of several diseases such as cancer, metabolic conditions, and Alzheimer’s has led to the discovery and development of several inhibitors that could be repurposed for treatment of COVID-19 infection. E-64, a compound isolated from the fungus Aspergillus japonicus, can bind irreversibly to this target without showing toxic activity; also gallinamide A and Miraziridine A marine natural products were reported to possess the same activity. There are a number of natural compounds that possess a promising cathepsins inhibition with IC50 range from 2 to 10 micromolar, such as panduratin A, guttiferone A, ursolic acid, and agathisflavone [58].

2.4.1.1.3.3 Clathrin-mediated endocytosis (CME) pathway blockage

As addressed earlier, CME is one of the main mechanisms for viral entry; hence, its inhibition could be a reliable method for control of the infection. Ouabain and bufalin cardiotonic steroids, which are used for treatment of cardiovascular diseases, have demonstrated antiviral activity against MERS-CoV infection at nanomolar concentrations by affecting the CME pathway [59]. This is consistent with recent report by Jeon et al., where ouabain, lanatoside C, and digitoxin were able to reduce viral viability of COVID-19 in micromolar concentrations [60].

Bolinaquinone, a sesquiterpenoid derivative with quinone ring, isolated from marine Dysidea sp., which is known to possess anti-inflammatory activity, however, affinity chromatography coupled with mass spectrometry revealed the ability of this molecule to inhibit clathrin in a concentration comparable to chlorpromazine, a well-known inhibitor of this target [61]. Also, ikarugamycin, an antibiotic that was found to specifically inhibit CEM effectively [62].

2.4.1.1.4 Inhibition of translocation mechanisms

Like other viruses, COVID-19 uses the replication machinery of the host cell for transcription and replication of Viral RNA; this means that viral materials such as nonstructural proteins and negative-strand RNA should be relocated to the nucleus and endoplasmic reticulum.

2.4.1.1.4.1 Importin (IMP) α/β1 heterodimer inhibition

Interestingly, ivermectin, an antiparasitic FDA-approved drug, has been reported to inhibit nuclear transport in host cells such as (IMP) α/β1 heterodimer preventing the translocation of viral DNA integrase in HIV-1 and other viruses. Recently, ivermectin has shown potent antiviral activity against COVID-19 [63]. In fact, such effect was linked to the broad-spectrum antiviral activity of this molecule [64].

2.4.1.1.4.2 Chromosomal maintenance 1 (CRM-1 also known as exportin 1 (XPO1)) inhibition

Finally, leptomycin B (LMB), a compound isolated from Streptomyces sp, with prominent anticancer and anti-inflammatory activity, which is attributed to its ability to block CRM-1. While the main research focus of this target was on its role in tumorigenesis; it’s now known that it contributes in the infection of different viruses. There are a lot of natural compounds reported to target CRM-1 such as valtrate, which is anxiolytic compound isolated from valerian roots, acetoxychavicol, curcumin, goniothalamin, piperlongumine, and plumbagin. These compounds share the presence of alpha, beta unsaturated ketone, making structure similarly to LMB, which seems to be important feature to interact with Cys528 via Michael-type addition and exert their inhibitory actions. Despite the reported antiviral activity of these molecules, there are no studies addressing this effect in COVID-19. Figure 4 shows the chemical structure of compounds that inhibit endocytic pathway and translocation mechanisms.

Figure 4.

Chemical structure of compounds that inhibit endocytic pathway and translocation mechanisms.

2.4.1.2 Inhibition of nonstructural proteins formation

We have addressed the role of host cells factor and protein inhibition in controlling viral infection. So, we will focus mainly on some important targets of the virus itself. The proteolysis of polypeptide to the 16 NSp is a rate-limiting step in viral replication; thus, it is obvious that targeting viral proteases could achieve significant antiviral activity.

2.4.1.2.1 Inhibition of SARS-CoV-2 main protease (Mpro, also called 3CLpro)

Mpro is one of the best characterized drug targets among coronaviruses. This enzyme is essential for processing the translated polyproteins from the viral RNA. The Mpro works at not less than 11 cleavage sites on the large polyprotein 1ab (replicase 1ab, ~790 kDa); the recognition sequence at most sites is Leu-Gln↓(Ser,Ala,Gly).

The viral replication could be blocked by Mpro inhibitors [65, 66, 67]. There are no human proteases with a similar cleavage specificity. Therefore, these inhibitors are not supposed to be toxic. Peptidomimetic alpha keto-amides were reported to be potential Mpro inhibitors [68]. The natural α-keto amides such as eurystatin A and B, complestatin, and aplidine display prolyl endopeptidase inhibitor, HIV replication inhibitor, and antitumor activity, respectively [68]. Also, theaflavin-3,3′-digallate was reported as natural protease inhibitor in SARS-CoV [9]. Other flavonoids are reported to strongly block Mpro activity such as pectolinarin, rhoifolin, herbacetin [69].

2.4.1.2.2 Inhibition of SARS-CoV-2 papain-like protease (PLpro)

PLpro has dual function, beside its role in release of other nonstructural protein, it neutralizes the immune response by the host cell due its deubiquitinating activity, so its inhibition will not only stop the replication cascade but will help the immune system to regain the ability to recognize and destroy the virus [70, 71]. Hirsutenone, a diarylheptanoid from Alnus Japonica, was able to inhibit Plpro in uncompetitive manner at IC50 = 4.1 μM, which was attributed to the presence of catechol ring and alpha-beta unsaturated ketone [72]. Also tanshinone IIA achieved significant inhibition at IC50 = 0.8 μM, the binding of this compound with PLpro was noticed to increase with time indicating the possibility of covalent bond inhibition [73]. Tomentin E geranylated flavonoid was discovered to be mixed-type inhibitor of this target by bio-guided isolation, its IC50 = 5.0 μM. The inhibition assay demonstrated that flavonoid bearing dihydropyran ring might be superior inhibitor in comparison to parent compounds. Figure 5 shows chemical structure of SARS-COV proteases inhibitor from natural products [74].

Figure 5.

Chemical structure of natural compounds that inhibit viral proteases (Mpro and PLpro).

2.4.1.3 Inhibition of viral replication

After the transcription of viral RNA to the required structural protein, the hijack of the host cell continues to make many replicas of the viral RNA that will be packed and released. The new virus, RNA helicase was found to be crucial to viral genome replication, which explains why it is a potential target for antiviral drug development. Scutellarin inhibits 90% of SARS-COV RNA helicase activity at 10 μM probably by binding to the ADP active site, myricetin showed the same activity but with much lower extent [75]. Interestingly, ivermectin has shown the ability to inhibit RNA helicase of flavivirus [76], taking in consideration that helicase are structurally conservative among most of the viruses. Ivermectin might also be able to exert the same activity in COVID-19, which in fact may explain the potent antiviral activity addressed previously. Figure 6 shows the chemical structure of the natural helicase inhibitor.

Figure 6.

Chemical structure of the natural helicase inhibitors.

2.4.1.4 The role of natural products in immunity modulation and alleviation of inflammation associated with COVID-19

One of the hallmarks of late-phase COVID-19 infection is uncontrolled intense release of proinflammatory mediators, which is known as cytokines storm. Different types of viruses tend to activate mitogen-activated protein kinase (MAPKs) cascades, which control proliferation and inflammation in order to stimulate the replication process of the virus RNA. Since the upregulation of MAPKs was linked to several inflammatory and autoimmune diseases, it can lead to multiorgan failure and potentially death.

Clinically, in some patients, it has been reported that their immune response to the SARS-CoV-2 virus results in the increase of cytokines IL-6 and IL-10 [77].

Both hydroxychloroquine and chloroquine have immunomodulatory effects and can suppress the increase of immune factors. Bearing this in mind, it is possible that early treatment with either of the drugs may help prevent the progression of the disease to a critical, life-threatening state. In critically ill SARS-CoV-2-infected patients, the use of corticosteroids may be harmful. While the use of immunosuppressants (e.g., tocilizumab) is not ideal either as it can suppress the immune system and lead to an increased risk of infection. In this setting, hydroxychloroquine may be an ideal drug to treat SARS-CoV-2 infection as it can inhibit the virus via its antiviral effects and help mediate the cytokine storm via its immunomodulatory effects [78].

Fortunately, natural products could serve as the perfect solution in such case as they would not only work as antiviral agents but also could help to downregulate proinflammatory gene and protein expression via affecting a plethora of MAPKs and transcriptional factors. LPS-induced expression of proinflammatory cytokine could be considered as an excellent model for screening, since LPS also activates the inflammatory mediators through several pathways.

For example, diarylheptanoids, flavonoids, and triterpenes, which possess antiviral activity as mentioned earlier, were able to suppress the gene expression of TNF-alpha, IL-1β, IL-6 in different types of cells such as macrophages and HepG2 induced by LPS by modulating multiple intracellular signaling pathways in macrophages and prevent LPS-induced IL-6 production by reducing the mRNA stability via inhibiting ERK1/2 activation. This could be achieved by natural compounds such as flavokawain A, curcumin, quercetin curculigoside, syringic acid or vanillic acid, licochalcone A, chrysin, apigenin, and luteolin at transcriptional level [78, 79]. In brief, the anti-inflammatory effect of natural products is so prominent to be summarized in this chapter, and they can contribute significantly at reducing the mortality rates associated with COVID-19 complications (Figure 7).

Figure 7.

Chemical structures for the potential natural immunomodulators for cytokine storm associated with COVID-19 infection.

Advertisement

3. Artificial intelligence (AI) and machine learning (ML) technologies in drug discovery, diagnosis, and health care of COVID-19

3.1 Drug discovery

Therapeutics: AI and ML in treatment discovery development and/or drug repurposing for COVID-19 based on:

  • EHR data and clinical guidelines

  • Interaction of human-AI in robotic surgery

  • Pharmacogenomics for directing the management of medications

AI may contribute to the advancement of resources to support doctors and ultimately enhance medical outcomes. Fuzzy logic can be used in decision support systems to replicate patient decision-making processes [80, 81, 82]. Admittedly, machine learning applied is to clinical data that are regularly collected will produce new knowledge and potentially new perspectives that clinicians lack.

Drug repurposing is hoped to offer a way to establish COVID-19 avoidance and cure policies. For instance, the researchers built a DL approach to classifying current and mercantile medicines for “drug-repurposing,” i.e., identifying a quick treatment using existing medicines that can be introduced to patients immediately. The idea that recently created treatment typically needs years to succeed is reviewed before getting to the public motivates research. Although the results are not accepted clinically, new approaches to combat COVID-19 disease are already opening up [83]. In silico medicine is suggested in [84] using the deep generative model to explore drugs (identifying new medicines). This analysis may be used for simulations and computer modeling to obtain compounds for COVID-19 coronavirus by new molecular entities.

IBM reported that it is now offering an analysis service based on the cloud using the COVID-19 dataset that has been educated [85]. Besides, IBM has implemented its proposed drug discovery AI technology, in which 3000 novel COVID-19 molecules have been produced [86]. In the year 2020, a systematic analysis was developed by Zeng et al. [87] to find drugs for COVID-19. With the support of active Amazon Web Services (AWS), a DL-based model was developed, and 41 data on drug types were validated. As for performance metrics, true-positive rate (TPR), false-positive rate (FPR), etc., have been presented, and the approach suggested by the author is explicit that DL serves as an important instrument for exploring therapeutics.

3.2 Diagnostics

Earlier, our research team had presented the usefulness of AI and ML in diagnosis of several diseases [88, 89, 90]. However, COVID-19 diagnosis was based on AI.

  • Multiomics and clinical data

  • Records of Electronic Health (HER) data and expert knowledge

3.2.1 Image data and deep learning

Nour et al. [91] have developed a DL model for COVID-19 detection, as CNN is applied as a feature extractor. For performance assessment, chest X-ray images dataset is taken into account. For feeding ML methods such as K-nearest neighbour (KNN), Decision Tree (DT), and support vector machines (SVM), the deep feature that has been extracted with the aid of CNN is utilized. Precision, F-score, etc., are used as output variables. Among other suggested approaches, SVM yields greater precision.

Pereira et al. [92] proposed a new model for forecasting the dynamics of COVID-19 that have cases that have happened in other countries or places with similar emission patterns. For all subregions and accessible countries, they implemented a grouping algorithm.

3.3 Health care

Big data in the administration of hospitals, epidemiology, insurance, medication interactions and complications, outcomes reviews based on quality, epidemic tracking.

Speech datasets include breath sounds and cough, which can be utilized for COVID-19 diagnoses and its prediction for illness seriousness. Machine learning, statistical techniques, and big data may be used to the datasets for prediction functions about the disease. Various open-source datasets for COVID-19 included mobility, diagnosis, contagion assessment, NPI analysis, statistic relationships, and sentiment analysis.

Advertisement

4. Concluding remarks and future perspective

COVID-19 causes a gigantic load to the healthcare system, particularly in patients with preexisting conditions comorbidities. A comprehensive study is presented about COVID-19 symptoms, clinical classification (mild, moderate, severe, critical cases), and the risk indicators for COVID-19 infection with comorbidities.

Natural products (NPs) have been used for centuries for treatments of different maladies and inspired scientists to develop safer and more effective drugs. The COVID-19 is complex clinical condition that comprises inflammatory components. Although selective inhibitor could be developed for inhibiting critical molecular target in the life of cycle, compounds with multitargeting activity may be more favorable to reduce the possibility of mutation development. Optimum drug should be able to modulate host cell and viral-related mechanisms. This is where natural products could play important role since their ability to bind effectively to targets with completely different homology. Nevertheless, the anti-inflammatory attribute of NPs is another advantage that should be considered during choosing therapeutic protocol. Finally, the observed antiviral activity of different phytochemicals should initiate repurposing campaign of untested NPs to identify new antiviral compounds, which could be exploited to design more effective drugs with optimum pharmacokinetic properties. This study presents briefly the value of AI and ML as powerful tools in healthcare, clinical, drug industry, diagnosis, decision-making, and improvement of the selection criteria for the most appropriate protocol for the treatment of COVID-19.

Advertisement

Acknowledgments

The author would like to thank Ms. Rowida Omar (Department of Pharmacognosy, Faculty of Pharmacy, Delta University, Gamsa, Egypt) and Mr. Abdullah A. Elgazar (Department of Pharmacognosy, Faculty of Pharmacy, Kafrelsheikh University, Egypt) for their great efforts in providing valuable materials of the first draft and Mrs. Zahraa Tarek (Computer Science Department, Faculty of Computer and Information, Mansoura University, Egypt) for providing materials on artificial intelligence section.

Advertisement

Conflict of interest

The authors declare no conflict of interest.

References

  1. 1. Su S, Wong G, Shi W, Liu J, Lai AC, Zhou J, et al. Epidemiology, genetic recombination, and pathogenesis of coronaviruses. Trends in Microbiology. 2016;24(6):490-502
  2. 2. Hoffmann M, Kleine-Weber H, Schroeder S, Krüger N, Herrler T, Erichsen S, et al. SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor. Cell. 2020;181:271-280
  3. 3. Yang N, Shen H-M. Targeting the endocytic pathway and autophagy process as a novel therapeutic strategy in COVID-19. International Journal of Biological Sciences. 2020;16(10):1724-1731
  4. 4. Inoue Y, Tanaka N, Tanaka Y, Inoue S, Morita K, Zhuang M, et al. Clathrin-dependent entry of severe acute respiratory syndrome coronavirus into target cells expressing ACE2 with the cytoplasmic tail deleted. Journal of Virology. 2007;81(16):8722-8729
  5. 5. Huang IC, Bosch BJ, Li F, Li W, Lee KH, Ghiran S, et al. SARS coronavirus, but not human coronavirus NL63, utilizes cathepsin L to infect ACE2-expressing cells. The Journal of Biological Chemistry. 2006;281(6):3198-3203
  6. 6. Simmons G, Gosalia DN, Rennekamp AJ, Reeves JD, Diamond SL, Bates P. Inhibitors of cathepsin L prevent severe acute respiratory syndrome coronavirus entry. Proceedings of the National Academy of Sciences of the United States of America. 2005;102(33):11876-11881
  7. 7. Mathew C, Ghildyal R. CRM1 inhibitors for antiviral therapy. Frontiers in Microbiology. 2017;8:1171
  8. 8. Cui J, Li F, Shi Z-L. Origin and evolution of pathogenic coronaviruses. Nature Reviews Microbiology. 2019;17(3):181-192
  9. 9. Báez-Santos YM, St John SE, Mesecar AD. The SARS-coronavirus papain-like protease: Structure, function and inhibition by designed antiviral compounds. Antiviral Research. 2015;115:21-38
  10. 10. Liu C, Zhou Q , Li Y, Garner LV, Watkins SP, Carter LJ, et al. Research and Development on Therapeutic Agents and Vaccines for COVID-19 and Related Human Coronavirus Diseases. Washington, D.C., USA: ACS Publications; 2020
  11. 11. Keum Y-S, Jeong Y-J. Development of chemical inhibitors of the SARS coronavirus: Viral helicase as a potential target. Biochemical Pharmacology. 2012;84(10):1351-1358
  12. 12. Masters PS. The molecular biology of coronaviruses. Advances in Virus Research. 2006;66:193-292
  13. 13. Fung TS, Liu DX. Human coronavirus: Host-pathogen interaction. Annual Review of Microbiology. 2019;73:529-557
  14. 14. Amanat F, Krammer F. SARS-CoV-2 vaccines: Status report. Immunity. 2020:583-589
  15. 15. Khalili M, Karamouzian M, Nasiri N, Javadi S, Mirzazadeh A, Sharifi H. Epidemiological characteristics of COVID-19: A systemic review and meta-analysis. MedRxiv. 2020;148:1-7
  16. 16. Available from: https://www.who.int/news-room/questions-and-answers/item/coronavirus-disease-(covid-19) vaccines?
  17. 17. Xavier AR, Silva JS, Almeida JPC, Conceição JFF, Lacerda GS, Kanaan S. COVID-19: Clinical and laboratory manifestations in novel coronavirus infection. Jornal Brasileiro de Patologia e Medicina Laboratorial. 2020;56
  18. 18. He S, Tang S, Rong L. A discrete stochastic model of the COVID-19 outbreak: Forecast and control. Mathematical Biosciences and Engineering. 2020;17:2792-2804
  19. 19. Guan W, Ni Z, Hu Y, Liang W, Ou C, He J, et al. Clinical characteristics of coronavirus disease 2019 in China. New England Journal of Medicine. 2020;382(18):1708-1720
  20. 20. Li X, Xu Z, Wang T, Xu X, Li H, Sun Q , et al. Clinical laboratory characteristics of severe patients with coronavirus disease 2019 (COVID-19): A systematic review and meta-analysis. Clinical Epidemiology and Global Health. 2020
  21. 21. Liang JJ, Liu J, Chen Y, Ye B, Li N, Wang X, et al. Characteristics of laboratory findings of COVID-19 patients with comorbid diabetes mellitus. Diabetes Research and Clinical Practice. 2020;167(108351):1-5
  22. 22. Brooks SK, Webster RK, Smith LE, Woodland L, Wessely S, Greenberg N, et al. The psychological impact of quarantine and how to reduce it: Rapid review of the evidence. The Lancet. 2020;395(10227):912-920
  23. 23. Wu J, Wu X, Zeng W, Guo D, Fang Z, Chen L, et al. Chest CT findings in patients with coronavirus disease 2019 and its relationship with clinical features. Investigative Radiology. 2020;55(5):257
  24. 24. Wang K, Kang S, Tian R, Zhang X, Wang Y. Imaging manifestations and diagnostic value of chest CT of coronavirus disease 2019 (COVID-19) in the Xiaogan area. Clinical Radiology. 2020;75(5):341-347
  25. 25. Yang W, Cao Q , Qin L, Wang X, Cheng Z, Pan A, et al. Clinical characteristics and imaging manifestations of the 2019 novel coronavirus disease (COVID-19): A multi-center study in Wenzhou city, Zhejiang, China. Journal of Infection. 2020;80(4):388-393
  26. 26. Li K, Fang Y, Li W, Pan C, Qin P, Zhong Y, et al. CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19). European Radiology. 2020:1-10
  27. 27. Wang M, Cao R, Zhang L, Yang X, Liu J, Xu M, et al. Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro. Cell Research. 2020;30(3):269-271
  28. 28. Jun C, Yun L, Xiuhong X, Ping L, Feng L, Tao L, et al. Efficacies of lopinavir/ritonavir and abidol in the treatment of novel coronavirus pneumonia. Chinese Journal of Infectious Diseases. 2020:E008-E008
  29. 29. Zumla A, Hui DS, Azhar EI, Memish ZA, Maeurer M. Reducing mortality from 2019-nCoV: Host-directed therapies should be an option. The Lancet. 2020;395(10224):e35-e36
  30. 30. Mair-Jenkins J, Saavedra-Campos M, Baillie JK, Cleary P, Khaw F-M, Lim WS, et al. The effectiveness of convalescent plasma and hyperimmune immunoglobulin for the treatment of severe acute respiratory infections of viral etiology: A systematic review and exploratory meta-analysis. The Journal of Infectious Diseases. 2015;211(1):80-90
  31. 31. Chen Q , Wang L, Xie M, Li X, Recommendations for Influenza, Streptococcus pneumoniae Vaccination in Elderly People in China Writing Group, Geriatric Respiratory Group and Chinese Society of Geriatrics. Recommendations for influenza and Streptococcus pneumoniae vaccination in elderly people in China. Aging Medicine. 2020;3(1):4-14
  32. 32. Badria FA, (Ed.). Drug Repurposing—Hypothesis, Molecular Aspects and Therapeutic Applications. London, UK: IntechOpen; 2020. DOI: 10.5772/intechopen.83082
  33. 33. Badria F, Fayed HA, Ibraheem AK, Mazyed EA. Formulation of sodium valproate nanospanlastics as a promising approach for drug repurposing in the treatment of androgenic alopecia. Pharmaceutics. 2020;12(9):866
  34. 34. Badria F, Elgazar A. Drug repurposing in dermatology: Molecular biology and omics approach. In: Badria F, editor. Drug Repurposing: Hypothesis, Molecular Aspects and Therapeutic Applications. London: IntechOpen; 2020. DOI: 10.5772/intechopen.93344
  35. 35. El-Mesery M, Seher A, El-Shafey M, El-Dosoky M, Badria FA. Repurposing of quinoline alkaloids identifies their ability to enhance doxorubicin-induced sub-G0/G1 phase cell cycle arrest and apoptosis in cervical and hepatocellular. Biotechnology and Applied Biochemistry. 2021;68(4):832-840
  36. 36. Ibrahim MG, El-Senduny FF, Youssef MM, Elimam DM, Bar FMA. Acetyl glycyrrhetinic acid methyl ester as a promising glycyrrhizin derivative against the breast cancer cells (MCF-7). Journal of Reports in Pharmaceutical Sciences. 2019;8(2):161
  37. 37. El-Senduny FF, Zidane MM, Youssef MM, Badria FA. An approach to treatment of liver cancer by novel glycyrrhizin derivative. Anti-Cancer Agents in Medicinal Chemistry. 2019;19(15):1863-1873
  38. 38. Bar FMA, Elimam DM, Mira AS, El-Senduny FF, Badria FA. Derivatization, molecular docking and in vitro acetylcholinesterase inhibitory activity of glycyrrhizin as a selective anti-Alzheimer agent. Natural Product Research. 2019;33(18):2591-2599
  39. 39. Wang Y, Chen L. Tissue distributions of antiviral drugs affect their capabilities of reducing viral loads in COVID-19 treatment. European Journal of Pharmacology. 2020;889:173634
  40. 40. Ye C, Gao M, Lin W, Yu K, Li P, Chen G. Theoretical study of the anti-NCP molecular mechanism of traditional Chinese Medicine Lianhua-Qingwen Formula (LQF). Polar. 2020;2(21.52):10-68
  41. 41. Wu H, Wang J, Yang Y, Li T, Cao Y, Qu Y, et al. Preliminary exploration of the mechanism of Qingfei Paidu decoction against novel coronavirus pneumonia based on network pharmacology and molecular docking technology. Acta Pharmaceutica Sinica. 2020;55:374-383
  42. 42. Xu D, Xu Y, Wang Z, Lv Y, Zhu H, Song T. Mechanism of Qingfeipaidu decoction on COVID-19 based on network pharmacology. Pharmacol Clin Chin Materia. 2020;158(104939):1-11
  43. 43. Fan J-X, Qin X-M, Li Z-Y. Mechanism of Farfarae Flos in Qingfei Paidu Decoction against COVID-19 based on network pharmacology and molecular docking. Chinese Traditional and Herbal Drugs. 2020;11:2317-2325
  44. 44. Huang YF, Bai C, He F, Xie Y, Zhou H. Review on the potential action mechanisms of Chinese medicines in treating coronavirus disease 2019 (COVID-19). Pharmacological Research. 2020;158:104939. DOI: 10.1016/j.phrs.2020.104939
  45. 45. Deng YJ, Liu BW, He ZX, Liu T, Zheng RL, Di Yang A, et al. Study on active compounds from Huoxiang Zhengqi oral liquid for prevention of coronavirus disease 2019 (COVID-19) based on network pharmacology and molecular docking. Chinese Traditional and Herbal Drugs. 2020;51(5):1113-1122
  46. 46. Shi Y, Wei J, Liu M, Jin X, Zhou H, Zhu W, et al. Study on the overall regulation of Xuebijing injection in treating corona virus disease 2019. Shanghai Journal of Traditional Chinese Medicine. 2020;54:1-7
  47. 47. Jimilihan S et al. Study on the active components in the adjuvant treatment of novel coronavirus pneumonia (COVID-19) with Jinhua Qinggan Granules based on network pharmacology and molecular docking. Journal of Chinese Medicinal Materials. 2020;225:1-10
  48. 48. Glende J, Schwegmann-Wessels C, Al-Falah M, Pfefferle S, Qu X, Deng H, et al. Importance of cholesterol-rich membrane microdomains in the interaction of the S protein of SARS-coronavirus with the cellular receptor angiotensin-converting enzyme 2. Virology. 2008;381(2):215-221
  49. 49. Heaton NS, Randall G. Multifaceted roles for lipids in viral infection. Trends in Microbiology. 2011;19(7):368-375
  50. 50. Guo H, Huang M, Yuan Q , Wei Y, Gao Y, Mao L, et al. The important role of lipid raft-mediated attachment in the infection of cultured cells by coronavirus infectious bronchitis virus Beaudette strain. PLoS One. 2017;12(1):e0170123. DOI: 10.1371/journal.pone.0170123
  51. 51. Baglivo M, Baronio M, Natalini G, Beccari T, Chiurazzi P, Fulcheri E, et al. Natural small molecules as inhibitors of coronavirus lipid-dependent attachment to host cells: A possible strategy for reducing SARS-COV-2 infectivity? Acta Bio-medica: Atenei Parmensis. 2020;91(1):161
  52. 52. Andrade PB, Valentão P, Pereira DM, editors. Natural Products Targeting Clinically Relevant Enzymes. 3rd ed. Hoboken, New Jersey, U.S: Wiley Online Library; 2017. ISBN: 978-3-527-34205-1
  53. 53. de Haan CA, Rottier PJ. Molecular interactions in the assembly of coronaviruses. Advances in Virus Research. 2005;64:165-230
  54. 54. Devaux CA, Rolain J-M, Colson P, Raoult D. New insights on the antiviral effects of chloroquine against coronavirus: What to expect for COVID-19? International Journal of Antimicrobial Agents. 2020;55(5):105938:1-6
  55. 55. Yang Z-Y, Huang Y, Ganesh L, Leung K, Kong W-P, Schwartz O, et al. pH-dependent entry of severe acute respiratory syndrome coronavirus is mediated by the spike glycoprotein and enhanced by dendritic cell transfer through DC-SIGN. Journal of Virology. 2004;78(11):5642-5650
  56. 56. Vidal-Albalat A, González FV. Chapter 6—Natural products as cathepsin inhibitors. In: Atta ur R, editor. Studies in Natural Products Chemistry. Vol. 50. Amsterdam, The Netherlands: Elsevier; 2016. pp. 179-213
  57. 57. Burkard C, Verheije MH, Haagmans BL, van Kuppeveld FJ, Rottier PJ, Bosch BJ, et al. ATP1A1-mediated Src signaling inhibits coronavirus entry into host cells. Journal of Virology. 2015;89(8):4434-4448
  58. 58. Jeon S, Ko M, Lee J, Choi I, Byun SY, Park S, et al. Identification of antiviral drug candidates against SARS-CoV-2 from FDA-approved drugs. bioRxiv. 2020.03.20.999730. 2020:480-485
  59. 59. Margarucci L, Monti MC, Fontanella B, Riccio R, Casapullo A. Chemical proteomics reveals bolinaquinone as a clathrin-mediated endocytosis inhibitor. Molecular Biosystems. 2011;7(2):480-485
  60. 60. Elkin SR, Oswald NW, Reed DK, Mettlen M, MacMillan JB, Schmid SL. Ikarugamycin: A natural product inhibitor of clathrin-mediated endocytosis. Traffic (Copenhagen, Denmark). 2016;17(10):1139-1149
  61. 61. Caly L, Druce JD, Catton MG, Jans DA, Wagstaff KM. The FDA-approved drug ivermectin inhibits the replication of SARS- CoV-2 in vitro. Antiviral Research. 2020;178:104787-104803
  62. 62. Yang SNY, Atkinson SC, Wang C, Lee A, Bogoyevitch MA, Borg NA, et al. The broad spectrum antiviral ivermectin targets the host nuclear transport importin α/β1 heterodimer. Antiviral Research. 2020;177:104760
  63. 63. Hilgenfeld R. From SARS to MERS: Crystallographic studies on coronaviral proteases enable antiviral drug design. The FEBS Journal. 2014;281(18):4085-4096
  64. 64. García-Fernández R, Ziegelmüller P, González L, Mansur M, Machado Y, Redecke L, et al. Two variants of the major serine protease inhibitor from the sea anemone Stichodactyla helianthus, expressed in Pichia pastoris. Protein Expression and Purification. 2016;123:42-50
  65. 65. Zhang L, Lin D, Sun X, Curth U, Drosten C, Sauerhering L, et al. Crystal structure of SARS-CoV-2 main protease provides a basis for design of improved α-ketoamide inhibitors. Science. 2020;368(6489):409-412
  66. 66. Muthukumar A, Sangeetha S, Sekar G. Recent developments in functionalization of acyclic α-keto amides. Organic & Biomolecular Chemistry. 2018;16(39):7068-7083
  67. 67. Chen C-N, Lin CPC, Huang K-K, Chen W-C, Hsieh H-P, Liang P-H, et al. Inhibition of SARS-CoV 3C-like protease activity by Theaflavin-3,3′-digallate (TF3). Evidence-based Complementary and Alternative Medicine. 2005;2(2):209-215
  68. 68. Jo S, Kim S, Shin DH, Kim M-S. Inhibition of SARS-CoV 3CL protease by flavonoids. Journal of Enzyme Inhibition and Medicinal Chemistry. 2020;35(1):145-151
  69. 69. Barretto N, Jukneliene D, Ratia K, Chen Z, Mesecar AD, Baker SC. The papain-like protease of severe acute respiratory syndrome coronavirus has deubiquitinating activity. Journal of Virology. 2005;79(24):15189-15198
  70. 70. Park J-Y, Jae Jeong H, Hoon Kim J, Min Kim Y, Park S-J, Kim D, et al. Diarylheptanoids from Alnus japonica inhibit papain-like protease of severe acute respiratory syndrome coronavirus. Biological & Pharmaceutical Bulletin. 2012;35(11):2036-2042
  71. 71. Park J-Y, Kim JH, Kim YM, Jeong HJ, Kim DW, Park KH, et al. Tanshinones as selective and slow-binding inhibitors for SARS-CoV cysteine proteases. Bioorganic & Medicinal Chemistry. 2012;20(19):5928-5935
  72. 72. Cho JK, Curtis-Long MJ, Lee KH, Kim DW, Ryu HW, Yuk HJ, et al. Geranylated flavonoids displaying SARS-CoV papain-like protease inhibition from the fruits of Paulownia tomentosa. Bioorganic & Medicinal Chemistry. 2013;21(11):3051-3057
  73. 73. Yu M-S, Lee J, Lee JM, Kim Y, Chin Y-W, Jee J-G, et al. Identification of myricetin and scutellarein as novel chemical inhibitors of the SARS coronavirus helicase, nsP13. Bioorganic & Medicinal Chemistry Letters. 2012;22(12):4049-4054
  74. 74. Mastrangelo E, Pezzullo M, De Burghgraeve T, Kaptein S, Pastorino B, Dallmeier K, et al. Ivermectin is a potent inhibitor of flavivirus replication specifically targeting NS3 helicase activity: New prospects for an old drug. Journal of Antimicrobial Chemotherapy. 2012;67(8):1884-1894
  75. 75. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The Lancet. 2020;395(10223):497-506
  76. 76. Yao X, Ye F, Zhang M, Cui C, Huang B, Niu P, et al. In vitro antiviral activity and projection of optimized dosing design of hydroxychloroquine for the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Clinical Infectious Diseases. 2020;71(15):732-739
  77. 77. Grigore A. Plant phenolic compounds as immunomodulatory agents. In: Phenolic Compounds–Biological Activity. London, UK: IntechOpen; 2017. pp. 75-98
  78. 78. Badria FA, Abdelaziz EA, Hassan AH, Elgazar AE, Mazyed EA. Development of provesicular nanodelivery system of curcumin as a safe and effective antiviral agent: Statistical optimization, in vitro characterization, and antiviral effectiveness. Molecules. 2020;25(23):5668
  79. 79. Badria F, Mazyed E. Formulation of nanospanlastics as a promising approach for improving the topical delivery of a natural leukotriene inhibitor (3-Acetyl-11-keto-β-Boswellic acid): Statistical optimization, in vitro characterization, and ex vivo permeation study. Drug Design, Development and Therapy. 2020;14:3697-3721
  80. 80. Elmogy M, Elfetouh A, Elhefny M, Badria F. Foorc: A fuzzy ontology-based representation for obesity related cancer knowledge, Ain Shams University, Faculty of Computer and Information Science. IJIC1S. 2016;6(3):15-32
  81. 81. Elhefny MA, Elmogy M, Elfetouh AA, Badria FA. Developing a fuzzy OWL ontology for obesity related cancer domain. International Journal of Medical Engineering and Informatics. 2017;9(2):162-187
  82. 82. Shoaip N, Elmogy M, Riad AM, Badria FA. Missing data treatment using interval-valued fuzzy rough sets with svm. International Journal of Advancements in Computing Technology. 2015;7(5):37
  83. 83. Beck BR, Shin B, Choi Y, Park S, Kang K. Predicting commercially available antiviral drugs that may act on the novel coronavirus (SARS-CoV-2) through a drug-target interaction deep learning model. Computational and Structural Biotechnology Journal. 2020;18:784-790
  84. 84. Zhavoronkov A, Aladinskiy V, Zhebrak A, Zagribelnyy B, Terentiev V, Bezrukov DS, et al. Potential COVID-2019 3C-like protease inhibitors designed using generative deep learning approaches. Insilico Medicine Hong Kong Ltd A. 2020;307:E1
  85. 85. A I F A et al. COVID-19 Open Research Dataset Challenge (CORD-19): An AI Challenge with AI2, CZI, MSR, Georgetown, NIH & The White House. USA: Kaggle; 2020
  86. 86. Gil D. IBM releases novel AI-powered technologies to help health and research community accelerate the discovery of medical insights and treatments for COVID-19. IBM. 2020
  87. 87. Zeng X, Song X, Ma T, Pan X, Zhou Y, Hou Y, et al. Repurpose open data to discover therapeutics for COVID-19 using deep learning. Journal of Proteome Research. 2020;19(11):4624-4636
  88. 88. Badria FA, Shoaip N, Elmogy M, Riad AM, Zaghlou H. In: Hassanien AE, Tolba MF, Taher AA, editors. A framework for ovarian cancer diagnosis based on amino acids using fuzzyrough sets with SVM, Advanced Machine Learning Technologies and Applications. AMLTA 2014. Communications in Computer and Information Science. Vol. 488. Cham: Springer; 2014. pp. 389-400
  89. 89. Sweidan S, El-Sappagh S, El-Bakry H, Sabbeh S, Badria FA, Kwak KS. A fibrosis diagnosis clinical decision support system using fuzzy knowledge. Arabian Journal for Science and Engineering. 2019;44(4):3781-3800
  90. 90. Shoaip N, Elmogy MM, Riad AM, Zaghloul H, Badria FA. Early-stage ovarian cancer diagnosis using fuzzy rough sets with SVM classification. In: Handbook of Research on Machine Learning Innovations and Trends. Vol. 43-60. 2017
  91. 91. Nour M, Cömert Z, Polat K. A novel medical diagnosis model for COVID-19 infection detection based on deep features and Bayesian optimization. Applied Soft Computing. 2020;97:106580
  92. 92. Pereira I, Guérin J, Junior A, Garcia G, Piscitelli P, Miani A, et al. Forecasting Covid-19 dynamics in Brazil: A data driven approach. International Journal of Environmental Research and Public Health. 2020;17:5115

Written By

Farid A. Badria

Submitted: 20 October 2021 Reviewed: 09 February 2022 Published: 06 May 2022