Current use of existing antiviral drugs for COVID-19 [56].
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Kneyber",authors:[{id:"67620",title:"Dr.",name:"Martin",middleName:null,surname:"Kneyber",fullName:"Martin Kneyber",slug:"martin-kneyber"}]},{id:"27966",title:"Septic Shock in Neonates",slug:"septic-shock-in-neonates",signatures:"Lidia Decembrino ,Giulia Ruffinazzi, Armando D’Angelo,Nunzia Decembrino, Paolo Manzoni, Agata Boncimino and Mauro Stronati",authors:[{id:"80461",title:"Dr.",name:"Lidia",middleName:null,surname:"Decembrino",fullName:"Lidia Decembrino",slug:"lidia-decembrino"},{id:"80598",title:"Dr.",name:"Giulia",middleName:null,surname:"Ruffinazzi",fullName:"Giulia Ruffinazzi",slug:"giulia-ruffinazzi"},{id:"81627",title:"Dr.",name:"Mauro",middleName:null,surname:"Stronati",fullName:"Mauro Stronati",slug:"mauro-stronati"},{id:"81630",title:"Prof.",name:"Armando",middleName:"G",surname:"D'Angelo",fullName:"Armando D'Angelo",slug:"armando-d'angelo"},{id:"83467",title:"Dr.",name:"Agata",middleName:null,surname:"Boncimino",fullName:"Agata Boncimino",slug:"agata-boncimino"},{id:"83468",title:"Dr.",name:"Paolo",middleName:null,surname:"Manzoni",fullName:"Paolo Manzoni",slug:"paolo-manzoni"},{id:"123066",title:"Dr.",name:"Nunzia",middleName:null,surname:"Decembrino",fullName:"Nunzia Decembrino",slug:"nunzia-decembrino"}]},{id:"27967",title:"Septic Shock in Obstetrics and Gynecology",slug:"septic-shock-in-obstetrics-and-gynecology",signatures:"Apostolos Kaponis, Theodoros Filindris and George Decavalas",authors:[{id:"72677",title:"Dr.",name:"Apostolos",middleName:null,surname:"Kaponis",fullName:"Apostolos Kaponis",slug:"apostolos-kaponis"},{id:"80514",title:"Prof.",name:"George",middleName:"Odissefs",surname:"Decavalas",fullName:"George Decavalas",slug:"george-decavalas"},{id:"120719",title:"Dr.",name:"Theodoros",middleName:null,surname:"Filindris",fullName:"Theodoros Filindris",slug:"theodoros-filindris"}]},{id:"27968",title:"Alternative Therapies for Septic Shock: Beyond Early Goal-Directed Therapy",slug:"alternative-therapies-for-septic-shock-beyond-early-goal-directed-therapy",signatures:"Megan Rech, Megan Prasse and Payal Gurnani",authors:[{id:"76900",title:"Dr.",name:"Megan",middleName:null,surname:"Rech",fullName:"Megan Rech",slug:"megan-rech"},{id:"125483",title:"Dr.",name:"Megan",middleName:null,surname:"Prasse",fullName:"Megan Prasse",slug:"megan-prasse"},{id:"125485",title:"Dr.",name:"Payal",middleName:null,surname:"Gurnani",fullName:"Payal Gurnani",slug:"payal-gurnani"}]},{id:"27969",title:"Hormonal Therapies in Severe Sepsis",slug:"hormonal-therapies-in-severe-sepsis",signatures:"Karen Choong",authors:[{id:"78430",title:"Dr",name:null,middleName:null,surname:"Choong",fullName:"Choong",slug:"choong"}]},{id:"27970",title:"Anti-Inflammatory Role of Natural Polyphenols and Their Degradation Products",slug:"anti-inflammatory-role-of-natural-polyphenolic-compounds",signatures:"Balázs Veres",authors:[{id:"71968",title:"Dr.",name:"Balazs",middleName:null,surname:"Veres",fullName:"Balazs Veres",slug:"balazs-veres"}]},{id:"27971",title:"Cellular and Molecular Markers of Outcome in Septic Shock",slug:"cellular-and-molecular-markers-of-outcome-in-septic-shock",signatures:"Jorge Monserrat, Raúl de Pablo, David Díaz, Miguel-Angel Sánchez, Eduardo Reyes, Alfredo Prieto and Melchor Álvarez de Mon",authors:[{id:"79032",title:"Dr.",name:"Jorge",middleName:null,surname:"Monserrat",fullName:"Jorge Monserrat",slug:"jorge-monserrat"},{id:"120705",title:"Dr.",name:"Raúl",middleName:null,surname:"De Pablo",fullName:"Raúl De Pablo",slug:"raul-de-pablo"},{id:"120706",title:"Dr.",name:"David",middleName:null,surname:"Díaz",fullName:"David Díaz",slug:"david-diaz"},{id:"120707",title:"Dr.",name:"Miguel-Angel",middleName:null,surname:"Sanchez",fullName:"Miguel-Angel 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Killer",isOpenForSubmission:!1,hash:"7ac9a759048ec9ec47c283813a4131cc",slug:"severe-sepsis-and-septic-shock-understanding-a-serious-killer",bookSignature:"Ricardo Fernandez",coverURL:"https://cdn.intechopen.com/books/images_new/802.jpg",editedByType:"Edited by",editors:[{id:"76827",title:"Dr.",name:"Ricardo",surname:"Fernandez",slug:"ricardo-fernandez",fullName:"Ricardo Fernandez"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],publishedBooksByAuthor:[{type:"book",id:"1737",title:"Emergency Medicine",subtitle:"An International Perspective",isOpenForSubmission:!1,hash:"937b8698946595f200066b643e153534",slug:"emergency-medicine-an-international-perspective",bookSignature:"Michael Blaivas",coverURL:"https://cdn.intechopen.com/books/images_new/1737.jpg",editedByType:"Edited by",editors:[{id:"106834",title:"Dr.",name:"Michael",surname:"Blaivas",slug:"michael-blaivas",fullName:"Michael Blaivas"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},onlineFirst:{chapter:{type:"chapter",id:"80145",title:"Antiviral Drugs and Their Roles in the Treatment of Coronavirus Infection",doi:"10.5772/intechopen.101717",slug:"antiviral-drugs-and-their-roles-in-the-treatment-of-coronavirus-infection",body:'Coronaviruses (CoVs) belong to the subfamily Orthocoronavirinae in the family of Coronaviridae. In this family, there are four types of viruses: α-coronavirus, β-coronavirus, γ-coronavirus, δ-coronavirus [1]. The CoV genome is an enveloped, positive-sense, and single-stranded RNA, and it has the largest genome of known RNA viruses. It is known that α- and β-CoV types cause infections in mammals as δ- and γ-CoVs infect birds [2]. Severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome (MERS) belonging to β-CoVs are the most aggressive strains of coronaviruses and cause viral pneumonia outbreaks [3, 4]. SARS-CoV disease is a kind of pneumonia and caused by novel CoV whose genome structure was more than 82% identical to those of SARS-CoV, named coronavirus disease 2019 (COVID-19) [5, 6]. SARS-Cov-2 is a beta gene virus genetically very close to bat-CoVRaTG13, and bat-SL-CoVZC45 Covs can cause severe illness. As the COVID-19 outbreak turned into a global threat, the World Health Organization (WHO) announced it as a global pandemic on 12 March 2020. The COVID-19 pandemic has changed the scenario of the entire world. COVID-19 outbreak started in Wuhan, China, has globally spread to 219 countries and territories [7]. Currently, there are few vaccines for COVID-19. Their acceptance and efficacy are an issue of debate across the whole world. Therefore, there is an urgent need to find drugs or vaccines for the treatment of COVID-19 infections effectively. However, there are some studies related to the use of known drugs such as remdesivir and chloroquine that have proved efficacy on COVID-19 infection. We summarize some antiviral drugs as therapeutic options for the treatment of COVID-19 [8].
COVID-19 mainly attacks the respiratory-tract-associated organs. Additionally, the virus has shown impact various to other organs or systems such as the gastrointestinal system, nervous system, etc. [9]. The most common symptoms in COVID-19 patients are fever, dry cough, loss of taste, lethargy, shortness of breath, dyspnea, chest pain, fatigue, myalgia, whereas headache, dizziness, abdominal pain, diarrhea, nausea, and vomiting are less commonly observed [10, 11]. Anosmia is also one of the most critical symptoms in COVID-19 patients [12]. COVID-19 is more contagious than other coronaviruses, and its transmission rate is higher than the closely related strain, SARS-CoV-10 [13]. Currently, new variants of COVID-19 are reported from different regions of the world. Coronavirus interacts with cell surface receptors such as angiotensin-converting enzyme-2 (ACE-2) and neuropilin to gain entry inside the cell. The receptor-binding domain of viral spike protein is essential in SARS-CoV-2 entry into the host cell via surface ACE-2 [14]. Recently, another cell receptor Neuropilin-1 was found to be involved in SARS-CoV-2 entry. After binding to the receptor, the conformational change in the spike protein leads to virus fusion with the host cell membrane. The virus may transfer the RNA directly inside the cells or may proceed through the endosomal pathway [15]. Upon translation of viral RNA, the viral replicase polyprotein PP1a and PP1ab are produced and cleaved into small products by viral endopeptidase [16]. RNA-dependent RNA polymerase (RdRp) produces subgenomic RNAs by discontinuous transcription [16, 17]. This further gets translated into respective viral proteins. After processing through the endoplasmic reticulum (ER), ER-Golgi intermediate compartment (ERGIC), and Golgi complex, the viral RNA and proteins are assembled into virions. These virions are transported through vesicles and exocytosed for transmission. These steps of the viral life cycle are beneficial virus inhibition targets for different drugs. The coronaviruses are ribonucleic acid (RNA) viruses, which have a positive single-strand RNA [14, 18]. When SARS-CoV-2 enters the body and comes in contact with the host cell membrane, some changes occur in the structure of the virus. The human TMPRSS2 protein alters the conformation of the spike glycoprotein in the virus. Two substantial protease enzymes, 3-chymotrypsin-like protease (3CLpro) and papain-like protease (PLPro), have essential roles in its viral replication process after it enters the host cell via ACE2 receptors [19]. The expression of several genes, such as AHCYL2, ZNF385B, etc., appears to have a strong correlation with the expression of ACE2 and TMPRSS2 protein receptors in human healthy and normal lung cells [20].
However, repurposing drugs could prove to be beneficial tactics for finding COVID-19 treatment, including cost-effectiveness, elimination of some clinical trial steps, faster on-field availability, combining the drugs with other possible drugs, and the invention of information about the mechanisms of the existing drug. Researchers were able to develop the possible COVID-19 medications using information from previous CoVs therapies, genetic sequences, and protein modeling studies. Antimalarials, antivirals, antibiotics, and corticosteroids are among the most often studied medications, and they have been repurposed based on their ability to neutralize viruses, reduce lung inflammation, or alleviate other illness symptoms. Chloroquine (CQ), hydroxychloroquine (HCQ), and azithromycin (AZM) are the most often utilized antiviral drugs against COVID-19, since they have already demonstrated reasonable antiviral efficacy against SARS-CoV, MERS-CoV, and SARS-CoV-2. Anti-HIV medications lopinavir/ritonavir (LPV/RTV) are being studied for COVID-19 since they were successful in previous CoV epidemics. Furthermore, the anti-Ebola medicine remdesivir (RDV) was evaluated for COVID-19 and garnered further attention.
Similarly, favipiravir (FPV), ribavirin (RBV), umifenovir (UFV), and oseltamivir (OTV) have broad-spectrum antiviral activities and clinically tested against COVID-19. The effective uses of HCQ, RDV, LPV/RTV, or LPV/RTV in combination with Interferon (IFN) β-1a against COVID-19 [21], all these drugs had little or no effect on overall mortality, initiation of ventilation, and duration of hospital stay in hospitalized patients. So far, to treat severe and critical COVID-19, only corticosteroids have proven effective [21]. Other drugs, such as Angiotensin-Converting-Enzyme inhibitors (ACEi), have also been used to treat COVID-19. However, no clear correlation was reported between mortality rate and ACEi drugs in hypertension patients with COVID-19 [22]. Due to the possibility of secondary infection in these patients, antibiotics have been used as various protocols [23].
Umifenovir (UFV) may interact with SARS-CoV-2 surface glycoproteins and lipids and obstruct the interaction with the entry receptor ACE-2. Antibodies against SARS-CoV-2 may prevent the virus from entering the body and causing illness. Chloroquine (CQ), hydroxychloroquine (HCQ), and azithromycin (AZM) can raise endosomal pH, making viral entrance and RNA release more difficult. CQ, HCQ, and AZM all have immunomodulatory properties. RDV, FPV, and RBV are nucleoside inhibitors that impede RNA replication and reduce RNA-dependent RNA polymerase activity. Fraternization of LPV with viral protease may change proteolysis. OTV may interact with components involved in exocytosis, preventing the virus from leaving the cell. Antibodies against cytokine receptors and corticosteroids have been shown to have anti-inflammatory properties in the face of excessive immune responses. Drugs such as CQ are wide-spectrum inhibitors of viral cell entry, and RDV is a wide-spectrum RNA polymerase inhibitor. SARS-CoV-2 infection concurrently triggers the host immune system and an inflammatory cascade response (cytokine storm). These are being targeted in the treatment of COVID-19 patients [23].
So far, no fully effective drug has been discovered against this virus. The antiviral drugs, usually nucleoside analogs or intracellular proteases, block the virus by preventing its entry into the cell or by interfering with its replication inside the cell. Protease inhibitors target certain proteases, whereas fusion inhibitors block the fusion phase of viral entrance. Transcription inhibitors impede viral replication by inhibiting RNA-dependent RNA polymerase during the reverse transcription process. Nucleoside reverse transcriptases are some of the transcriptase inhibitors. M2 channel protein is a target for certain antivirals. In this chapter, we have provided information about repurposed drugs that are used against COVID-19, the mechanism of activity, therapeutic regimens, pharmacokinetics, and drug-drug interactions [7, 8].
The rationale major biochemical events and components in the replication cycle of coronavirus are considered as targets for currently developed drugs. These include the spike protein, proteolytic enzymes, and RNA-dependent RNA polymerase [24]. SARS-CoV-2 is transmitted mainly via respiratory droplets. The virus enters the host cells through two pathways, either via endosomes or plasma membrane fusion. In both mechanisms, the viral S protein mediates attachment to the membrane of the host cell and engages ACE2 as the entry receptor [25]. A host protease termed transmembrane serine protease 2 (TMPRSS2) activates the connection between S protein and ACE-2 [26]. S protein is used by the virus to destroy antibodies and make it simpler for it to attach to host receptors [27]. Beta-coronaviruses generally employ hemagglutinin-esterase (HE) to bind to sialic acid on the glycoprotein surface, despite the fact that the fusion machinery of SARS-CoV-2 remains unknown [28]. Fusion inhibitors might be used to prevent these fusion stages.
The envelope is peeled off when fusion is complete, and the SARS-CoV-2 genome, together with its nucleocapsid, penetrates the cytoplasm of the host cell. Its genome comprises the open reading frames 1a and 1b (ORF1a and ORF1b) genes, which create two polyproteins (pp) named pp1a and pp1b, which aid in the viral translation process by hijacking host ribosomes [29]. Main protease (Mpro) and papain-like protease (Ppro) break these polyproteins to create multiple non-structural proteins [30]. Aside from Mpro and Ppro, SARS-CoV-2 has 3C-like cysteine protease (3CLPro), which has a 96% resemblance to SARS-CoV. These proteases are essential for viral replication and transcription, and protease inhibitors inhibiting these proteases are potential antivirals for SARS-CoV-2. The promising clinical outcomes for COVID-19 patients should be obtained by using alpha-interferon, chloroquine phosphate, arabinol, remdesivir, lopinavir/ritonavir, and anti-inflammatory drugs [31, 32, 33, 34]. Moreover, clinical trials with these drugs should be performed on COVID-19 patients to prove their efficacy and safety as proposed for tocilizumab (Figure 1) [35].
Schematic diagram of the life cycle of SARS-CoV-2.
Highest sequence similarity (~96%) was observed for the bat Coronavirus. So, it has been speculated that COVID-19 was transmitted from bats to humans. The intermediary animal host could be a pangolin or dog. COVID-19 illness is spread via intimate contact with an infected individual, as well as minute respiratory droplets emitted during coughing, sneezing, or talking [36]. Small droplets of saliva or sputum emitted from the mouth might carry large amounts of viruses that can linger in the air for lengthy periods of time and function as infection carriers. Even when a person is not in direct physical touch with the infected individual, inhaling these minute droplets causes viral infection to move from the sick to the healthy. The virus enters the human body via the eyes, nose, and mouth and spreads by encountering the virus on infected surfaces and then touching these bodily areas [37]. Environmental factors such as temperature and humidity influence viral propagation across infected surfaces [38]. The binding of homotrimer spike protein (S) on the virus’s surface to ACE2 on the host’s cell membrane facilitates SARS-CoV-2 entry into host cells [16]. The host cell receptor’s credit is a critical predictor of the virus’s tissue tropism and pathogenicity. The life cycle of SARS-CoV-2 is similar to the SARS-CoV and MERS-CoV [39]. Different strategies have been adopted to fight COVID-19.
COVID-19 diagnosis is a crucial step in tracking the virus and understanding its spread. This aids in the prevention of transmission as well as adequate patient care. COVID-19 is diagnosed in the first instance by observing signs and symptoms such as first loss of smell or taste or both, cough, mild to high fever, myalgia or weariness, and so on [40]. In addition, some people experience gastrointestinal problems such as vomiting, diarrhea, and nausea [41]. However, variations in the development of symptoms ranging from asymptomatic to severe instances, such as septic shock, metabolic acidosis, coagulation malfunction, and acute respiratory pneumonia-like syndrome, have been recorded often [17]. These indications and symptoms should only be used as a starting point for additional testing, not as a diagnostic tool. The recognition of symptoms in clinical conditions is the most important factor in diagnosis. Swabs are used to obtain pathological samples from the upper and lower respiratory areas (throat, oropharyngeal, nasopharyngeal, broncho-alveolar fluid, and sputum). The virus is still absent in the blood and urine of infected people, hence they are not regarded valid clinical specimens. The interlink between the temporal surge of viral load and its bio-distribution in different tissues of the body has a critical implication on the accuracy of various tests for diagnosis, according to reports of inconsistency in RTPCR test results for CoV-SARS-2 in various tissues [42] and temporal variation of test results from the same tissues [43]. SARS-spike CoV-2’s surface glycoprotein binds to the ACE2 receptor and then enters the host cell. Viral particles release their DNA after entering the host cell, which is then translated into protein, and additional viral particles are created, which are then released to infect the next cells. Many assays (molecular and immunological assays) or tools have been used for the diagnosis of COVID-19 and many more are currently in development.
SARS-Cov-2 infections currently have no vaccinations or antiviral therapies available [44]. Because developing safe and stable vaccines takes time and the pandemic is still going on, it’s critical to test and discover current medications that are already effective against SARS and MERS to determine whether they can be effectively applied to SARSCov-2. Various preclinical studies on other CoVs genetically very close to SARS-Cov-2 suggested that promising clinical outcomes for COVID-19 patients should be obtained by using several drugs including alpha-interferon, chloroquine phosphate, arabinol, remdesivir, lopinavir/ritonavir, and anti-inflammatory drugs. In a large-scale drug screening, nelfinavir has potent antiviral activity against SARS-Cov-2 [45]. Besides, praziquantel, pitavastatin, and perampanel might be effective against SARS-CoV-2. The outbreak of COVID-19 infection is related to the unavailability of specific drugs to combat this viral infection. Despite the challenges related to COVID-19 therapy, there are still several approaches being undertaken that show significant outcomes [5]. Discuss the positive impacts of some of the clinically used drugs for the COVID-19. Some drugs are in clinical trials, and some have shown significant promise in COVID-19 patients [46]. To find the solutions for COVID-19, great efforts have been made and are continued to develop vaccines, small-molecule drugs, or monoclonal antibodies that can prevent the infection [47]. In addition to drugs under clinical trials, some vaccines are expected to play a significant role in controlling the COVID-19 pandemic (Figure 2).
Common inhibitory action of antiviral drugs.
In 2009, Gilead Sciences, Inc. (USA) developed an antiviral drug called Remdesivir (RDV) to treat hepatitis B [48]. It did not indicate a desirable act against hepatitis. However, it is effective against other viruses, such as the Nipah virus, hepatitis C, and Marburg [49]. RDV is a broad-spectrum antiviral nucleoside analog, and now it is used as a treatment option for COVID-19 [50]. It is the class of polymerase inhibitors and showed activity against different RNA viruses, including SARS-CoV, MERS-CoV, Lassa fever virus, Junin virus, respiratory syncytial virus, Nipah virus, Hendra viruses, filoviruses, and Ebola viruses. RDV is a prodrug of its parent adenosine triphosphate analog, (2R,3R,4S,5R)-2-(4-aminopyrrolo(2,1-f)(1,2,4)triazin-7-yl)-3,4-dihydroxy-5-(hydroxymethyl)oxolane-2-carbonitrile (GS-441524), and has similarity to the adenine nucleic acid structurally. Both of these drugs are metabolized into the active component as nucleoside triphosphate (GS-443902) after ingestion and show antiviral activity against SARS-CoV [51]. RDV targets the viral genome replication process by acting as an RdRp inhibitor [52], RDV was used to block the RNA-dependent RNA polymerase of SARS-CoV-2. On metabolization of RDV into active nucleoside triphosphate (NTP), which competes with ATP for incorporation into nascent RNA strands, premature RNA synthesis occurs, resulting in RNA strand termination and cessation of growth [51]. RDV when tested through in vitro studies using the Vero E6 cells showed an EC50 value of 1.76 μM that showed its activity against SARS-CoV-2 [53]. Intravenous remdesivir treatment showed significant improvement for COVID-19. RDV and chloroquine are highly effective in the control of SARS-CoV-2 infection. In severe COVID-19 treated with RDV, improvements in the clinical finding were observed in 68% of patients [54]. However, in October 2020, the WHO removed it from the list of effective drugs in the treatment procedure of COVID-19 patients because it failed in the first trials for the treatment of COVID-19 [42]. There are still controversies regarding the results, no benefit in COVID-19 treatment using RDV; whereas, the company claims it as a promising drug for the same. After penetrating the cell, RDV as a prodrug (GS-5734) and like Favipiravir, binds to the triphosphate group under esterase, kinase, and phosphatase enzymatic reactions. These enzymes modify the structure of RDV and convert it to the active form, RDV-triphosphate (RDV-TP or GS-441524) [55]. After virus entry into the cell cytoplasm, this prodrug gets activated and loses its ability to diffuse to the intercellular space [53]. However, the primary mechanism of action of RDV against SARS-CoV-2 is unclear, and more research is necessary to understand it [56]. In an in vitro study, the combination of RDV and chloroquine (antimalarial drug) effectively inhibited SARS-CoV-2 growth in Vero E6 cells [19]. RDV is used to treat COVID-19 cases.
The combined use of RDV and IFN-β created a higher antiviral activity compared with the lopinavir/ritonavir-IFN-β combination against the MERS-CoV virus. Additionally, RDV could be better pulmonary function, cause fall lung viral loads and severe lung pathology in mice; on the contrary, lopinavir/ritonavir-IFN-β could not [57]. In two clinical studies, the use of RDV has been carried out against severe or mild respiratory infections caused by COVID-19. Recently, RDV for emergency use to treat COVID-19, including five antiviral drugs, ribavirin, RDV, sofosbuvir, galidesivir, and tenofovir, was conducted against SARS-CoV-2 RNA-dependent RNA polymerase (RdRp); these drugs showed promising results against COVID-19. Prominent adverse reactions were an acute respiratory failure, decreased glomerular filtration rate, lymphocytopenia, pyrexia, hyperglycemia, increased anemia, increased creatine, and liver transaminases. RDV given in combination with baricitinib (Janus kinase inhibitor used to hinder intracellular signaling of cytokines) was effective compared with RDV alone in terms of reducing recovery time additionally speeding improvement. RDV’s parent nucleotide GS-441524 is superior and less toxic than its prodrug form and has shown efficacy [58].
Favipiravir (Avigan or T705) is a synthetic antiviral agent that was first marketed as an anti-influenza drug in Japan. It is a derivative of pyrazine carboxamide (6-fluoro-3-hydroxy-2-pyrazine carboxamide) [59]. Due to its similarity to the purine (guanine) nucleotide, it is a type of RNA-dependent RNA-polymerase (RdRp) inhibitor. RdRp uses Favipiravir-RTP in the synthesis of mRNA strands, which can consequently stop viral protein synthesis via suppressing the translation process. Activated Favipiravir-RTP could suppress the SARS-CoV-2 RdRp enzyme and inhibit viral mRNA elongation and protein synthesis [60]. Favipiravir acts against RNA viruses by working on viral genetic copying to prevent its reproduction. A phase 3 clinical trial was involved for the treatment of COVID-19 disease using Favipiravir. For the first day, take 1800 mg twice a day, then 600 mg three times a day from the second day onward for a total of 14 days. Normalization of pyrexia, respiratory rate, and cough alleviation for at least 72 h are the key objectives [61]. The precursor of this drug known as T1105 has anti-influenza effects [62]. Drug excretion is through renal elimination and is mainly impacted by aldehyde oxidase and xanthine oxidase [62]. Favipiravir is a prodrug that is phosphorylated upon its entry into the cell and converted to an active antiviral form, favipiravir ibufuranosyl-5′-triphosphate (T-705-RTP). Favipiravir was first prescribed in Wuhan, to treat patients with SARS-CoV-2 infection. In June 2020, it was approved for mild-to-moderate COVID-19 cases in India. Favipiravir has been consumed to cure distinct viral diseases. Favipiravir was effective against some RNA viruses, such as yellow fever virus, Lisa virus, West Nile virus, Bunyavirus, arenavirus, flavivirus, filoviruses, and Ebola virus [63]. The exact mechanism of action is not clear against SARS-CoV-2. Favipiravir is considered a potential drug for COVID-19 and is currently used for COVID-19 treatment in Japan and Indonesia. Besides, its anti-influenza virus action, it stops the replication of RNA viruses such as flavi-, alpha-, filo-, bunya-, arena-, noroviruses [64]. Favipiravir showed a more powerful antiviral activity than lopinavir/ritonavir. Adverse reactions are not observed in a favipiravir therapy group. Compared with the lopinavir/ritonavir group, it had considerably fewer adverse effects. In a Japanese study, FPV was also shown to control inflammatory mediators and pneumonia progression in COVID-19 patients [65]. Severe or critical COVID-19 patients showed improvements after treating with FPV and FPV also led to improved lung histology [66].
Lopinavir is an antiviral drug belonging to the family of protease inhibitors. It is commonly used to treat Acquired Immunodeficiency Syndrome (AIDS) and prevent HIV from spreading inside the body. Lopinavir/ritonavir (LPV/RTV) is used in combination with other antiretroviral drugs for the treatment of HIV-1 infection. In the coronavirus pandemic, when no definitive drug was proposed to treat patients, it was used in combination with Ritonavir. This LPV/RTV is branded as Kaletra. Lopinavir has a relatively short half-life in the blood and is affected by the cytochrome p450 enzyme, while Ritonavir is a protease inhibitor and reduces the Lopinavir metabolism by suppressing the function of cytochrome p450. The half-life of Lopinavir is improved, and its circulation period is increased. LPV/RTV acts as a protease inhibitor drug and inhibits the action of 3-CLpro, a chymotrypsin-like protease enzyme, that plays a vital role in the processing and interferes with the process of viral replication and its release from host cells [67, 68, 69]. LPV/RTV use is related to diverse side effects, mainly in the gastrointestinal tract. Diarrhea, impaired hepatic cell function, and pancreatitis are some of these crucial side effects.
The use of lopinavir as an emergency drug in China increased the eosinophil count among COVID-19 patients [70]. In an in silico study, LPV/RTV used as HIV protease inhibitors inhibited the main protease (MPro) of SARS-CoV-2 [71]. The LPV/RTV is being used as an emergency treatment for COVID-19 patients in some countries [72]. LPV/RTV alone or in combination with interferon (INF)-β, an inflammation regulator, has been listed by WHO as options for “solidarity” clinical trial for COVID-19. COVID-19 might benefit from LPV/RTV since it reduces viral load and improves clinical symptoms. Lung damage was also significantly reduced when LPV/RTV and umifenovir were used together [73]. A research found that while LPV/RTV therapy was associated with a better result, it did not significantly speed up the clinical progression of severe COVID-19 infection. Although the efficacy of lopinavir for COVID-19 has yet to be determined, LPV/RTV has been employed in the treatment of COVID-19 patients [57]. Now, LPV/RTV and IFN-β1b are in phase 2 for the MERS therapy. Despite the positive findings, in a recent study performed on patients with SARS-CoV-2 infection, the LPV/RTV did not provide clinical improvement compared with standard care processes [72]. Findings of LPV/RTV clinical efficacy remain limited and primarily anecdotal cases. LPV/RTV in the therapy of COVID-19 is needed as current results contradict. LPV/RTV can ameliorate the outcome of MERS-CoV infection [74]. Moreover, LPV/RTV is assumed as a therapeutic option for COVID-19 pneumonia [72]. Thus, more well-designed clinical studies are necessary to identify their efficacy as therapeutic agents for COVID-19.
Novaferon has potential as an antiviral drug against COVID-19. It is a synthesized protein consisting of 167 amino acids, designed on the technical basis of DNA shuffling technology. The antiviral effects of novaferon are shown alone and in combination with lopinavir/ritonavir (LPV/RTV) for COVID-19 treatment. Novaferon inhibited the viral replication in infected cells (EC50 = 1.02 ng/ml) and protected healthy cells from SARS-CoV-2 infection (EC50 = 0.1 ng/ml). Both novaferon and novaferon plus LPV/RTV groups had significantly higher SARS-CoV-2 clearance rates on day 6 than the LPV/RTV group [8].
Ribavirin (Virazole) is an antiviral drug belonging to the nucleoside analogues, (1-beta-d-ribofuranosyl-1,2,4-triazole-3-carboxamide). It is a synthetic nucleoside analog with a guanosine-like structure. Ribavirin disrupts viral DNA and RNA replication, thereby inhibiting virus proliferation in the cell. Although Ribavirin’s primary mechanism of action is suppressing the virus replication, and can also interfere with viral RNA capping, which depends on the presence of natural guanosine in the RNA structure. The natural guanosine in the viral RNA structure prevents the breakdown of RNA strands. Ribavirin reduces the guanosine synthesis in the cell by inhibiting the activity of the inosine monophosphate dehydrogenase enzyme, which negatively impacts virus replication [75]. Although Virazole does not entirely inhibit viral RNA synthesis, the synthesis of the viral genetic material is severely impaired. It results in significant and persistent mutations in viral RNA, which reduce the viability of the virus in host cells [76]. Besides, the presence of Ribavirin in the patient’s body can reduce viral immune evasion and boost immune maintenance [77]. It is the first broad-spectrum antiviral drug against DNA and RNA viruses [75]. It is used clinically to treat HIV and hepatitis C virus (HCV) patients.
Ribavirin, which has been studied for its antiviral effectiveness against SARS-CoV-2, is used to inhibit viral RNA production and viral mRNA capping with a broad range of antiviral activity. It’s a prodrug that, when metabolized, looks like purine RNA nucleotide, which prevents viral multiplication by interfering with RNA metabolism. It was discovered in a comparison study of SARS-CoV-2 patients treated with lopinavir/ritonavir (LPV/RTV) and ribavirin combination treatment [77]. Ribavirin is one of the medications used to treat COVID-19 in conjunction with either IFN alpha or LPV/RTV [46]. Using ribavirin in combination with sofosbuvir and remdesivir, docking and modeling studies revealed that ribavirin is a viable candidate medication for COVID-19 therapy [78]. Ribavirin and sofosbuvir are currently part of the therapeutic regimen to treat COVID-19 in some countries.
Ribavirin inhibits the function of inosine monophosphate dehydrogenase, which affects the formation of guanosine triphosphate (GTP), preventing RNA and DNA viral replication. During the SARS outbreak in Hong Kong, ribavirin was utilized. With or without steroids, it was occasionally chosen. The combination of ribavirin and interferon-β, which appears to inhibit SARS-CoV replication, has shown significant efficacy in the inhibition of SARS-CoV [79]. The ribavirin triple antiviral treatment was safe and superior compared with lopinavir-ritonavir combined therapy.
The drug showed antiviral efficacy against canine distemper virus, hepatitis C virus, Enterovirus, Chikungunya virus, and Semliki Forest virus, orthopoxvirus, influenza virus, flavi- and paramyxoviruses [80]. A study observed reduced replication of the MERS-CoV in rhesus macaques upon treatment with IFN-α2b and RBV [81]. RBV in combination with LPV/RTV was used in SARS-CoV and MERS-CoV trials [82]. In the case of SARS-CoV-2 infection, an in vitro study showed the EC50 of RBV as 109.50 uM [31]. A study included RBV along with LPV/RTV and IFN-α in the treatment of hospitalized COVID-19 patients. When compared with those that only received LPV-RTV, the triple treatment was found to be effective in reducing illness symptoms and viral shedding. The RBV dosage was 400 mg bid for 14 days, paired with 400 mg/100 mg of LPV/RTV + IFN-β. A research examined the effectiveness of antivirals sofosbuvir/daclatasvir and RBV in the treatment of COVID-19 patients. COVID-19 patients treated with RBV had a greater death rate (33%) than those treated with sofosbuvir/daclatasvir. A cohort study comparing RBV vs. supportive therapy stated that RBV did not help in reducing the mortality rate in COVID-19 patients [83].
It is an antiviral widely used to treat the influenza virus. Arbidol can prevent SARS-CoV-2 infection
Darunavir, an anti-HIV drug, is recommended for COVID-19 treatment in Italy. It is used in a combined regimen along with cytochrome P-450 inhibitors such as ritonavir or cobicistat and confirmed their replication inhibitory effect against SARS-CoV-2. A clinical trial assessed the effectiveness of darunavir combination with other antivirals and hydroxychloroquine for COVID-19 patients. A combination of darunavir and cobicistat is also being tested [93]. PREZCOBIX®, a fixed-dose combination of darunavir and cobicistat, is also used to treat COVID-19. COVID-19 infection was recently discovered in HIV-positive individuals who were already taking darunavir, raising questions about the effectiveness of this HIV protease inhibitor. The darunavir might not be effective in preventing SARS-CoV-2 infection at the dosage of 800 mg [94]. Darunavir is a second generation of HIV-1 protease inhibitors used to prevent SARS-CoV-2 infection in vitro [17] by inhibiting viral replication at 300 μM, and this inhibition efficiency was 280-fold compared with the untreated groups. Darunavir boosted with ritonavir or cobicistat is used in HIV/AIDS treatment. The efficacy of darunavir or ritonavir is enhanced by cytochrome p450 (CYP3A) inhibition [95]. Cell experiments with darunavir showed that the drug inhibited viral replication of COVID-19 in vitro. The lopinavir/ritonavir used in the treatment of HIV/AIDS has more efficacy and tolerability than darunavir, its use in COVID-19 is limited.
Oseltamivir (Tamiflu) is an antiviral agent that is used for patients with influenza A and B. It is a protease inhibitor, which specifically inhibits the neuraminidase enzyme in the influenza virus. This enzyme has a key role in the binding of the influenza virus to the cell membrane and spread throughout the body. Therefore, Oseltamivir, by targeting neuraminidase, prevents the spread of the influenza virus and its progression inside the body [96]. This drug was used in the treatment of COVID-19 infection, which showed an appropriate effect on patients [41]. Oseltamivir has been applied in concomitant regimens with other drugs such as Hydroxychloroquine or Favipiravirs [97]. In addition to treating influenza A and B patients, this drug may also be used in severe cases. For the treatment of flu patients, Tamiflu is prescribed in a 75 mg dosage twice a day and once a day as prophylaxis. The main side effects of this drug can be nausea and headache [98]. Neuraminidase inhibitors seem beneficial for COVID-19 patients and can reduce their ventilator requirements [99]. The precise mechanism of action of Oseltamivir against COVID-19 infection is still unclear. Oseltamivir is a synthetic derivative prodrug of ethyl ester [100]. It acts as a neuraminidase inhibitor against the influenza virus and is also effective for various avian influenza virus strains [101]. An in vitro oseltamivir study on H5N1 influenza showed that the IC50 was 0.1–4.9 nM [102]. In vivo study involving H5N1 infection required a longer course and higher dosage of Oseltamivir. The COVID-19 originated in China during flu season, and hence earlier, many patients received oseltamivir treatment until the causative agent SARSCoV-2 was discovered. Some current clinical trials have used oseltamivir in combination with other major therapeutic drugs [31, 41].
Sofosbuvir is an antiviral drug and RdRp inhibitor that exerts its effect by suppressing RdRp enzyme activity. A combination of Sofosbuvir with Ledipasvir is used for treating patients with genotype 1 of HCV67. Because of the similarity in the transcription and replication mechanism of the SARS-CoV-2 with HCV in host cells, physicians speculate that this drug may help treat COVID-19 patients [103]. This drug disrupts the activity of RdRp by acting like free nucleotides that are essential for viral mRNA synthesis [104]. Sofosbuvir is a potential option for COVID-19 treatment [105], and extensive clinical studies should be performed to verify the effectiveness of this drug.
Danoprevir, an HCV N53 protease inhibitor, is authorized in China for the treatment of noncirrhotic genotype 1b chronic hepatitis C in combination with other medications. In China, only two clinical studies of danoprevir coupled with ritonavir in the treatment of SARS-CoV-2 infection were completed [8].
In a computer simulation, atazanavir bonded more firmly to the active site of SARS-CoV-2 MPro than lopinavir, and atazanavir suppressed SARS-CoV-2 replication in a test tube. A prior trial on HIV-positive individuals found that combining atazanavir with ritonavir enhanced glucose uptake and lipid parameters while also lowering fasting glucose levels more efficiently than lopinavir-ritonavir. The atazanavir might be an alternative for lopinavir when combined with ritonavir for COVID-19 treatment. This antiviral drug is an option for COVID-19 treatment [8].
SARS-CoV-2 penetrates host cells by receptor-mediated endocytosis, just as other viruses. AP2-related protein kinase 1 controls the process of endocytosis (AAK1). As a result, disrupting AAK1 will prevent not just viral entrance but also intracellular viral assembly. Baricitinib is a Janus kinase (JAK) inhibitor that has a high affinity for AAK1 and can inhibit it. SARS-CoV-2 infection can be treated with baricitinib, which inhibits both viral entry and the inflammatory response [106]. JAK inhibitors such as ruxolitinib and fedratinib, which are linked to baricitinib, decreased clathrin-mediated endocytosis at higher dosages, suggesting that they may not be effective at acceptable concentrations in lowering viral infectivity. Neutropenia, lymphocytopenia, and viral reactivation have all been linked to the use of baricitinib for therapeutic purposes. Because individuals infected with SARSCoV-2 had a lower absolute lymphocyte count, baricitinib may increase the risk of co-infection [107].
Blocking virus-host fusion is a promising target for the novel antiviral agents that inhibit the Abl kinase pathway [41]. In a study, imatinib, an Abl kinase inhibitor, was observed to block the replication of SARS and MERS viruses by blocking viral fusion in 2016 [108]. COVID-19 utilized the SARS-coronavirus receptor ACE2 as well as the cellular protease TMPRSS2 to get access to target cells; therefore, TMPRSS2, transmembrane serine protease 2, inhibiting medicines such imatinib might be evaluated as COVID-19 disease treatment alternatives [37].
Another possible medicine that targets the fusion stage in viruses is camostat mesylate, a serine protease inhibitor. SARS-CoV-2 enters target host cells via ACE-2 receptors and/or TMPRSS2 receptors, with camostat mesylate acting as a TMPRSS2 inhibitor. It inhibits the virus’s cellular entrance by downregulating the production of the SARS-CoV-2 spike (S) protein, which prevents surface fusion. SARS-CoV infection in human bronchial epithelial cells was inhibited by camostat mesylate [109]. In vitro testing revealed that camostat mesylate and E-64d (a cysteine protease inhibitor) effectively blocked SARS-CoV-2 TMPRSS2 binding. Clinical studies are now underway to compare the efficacy of hydroxychloroquine and camostat mesylate vs. hydroxychloroquine alone. Another serine protease inhibitor, nafamostat mesylate, was shown to be 15 times more effective in preventing the SARS-CoV-2 virus from infecting host cells. As a result, nafamostat mesylate can be regarded a preferable option to camostat mesylate due to its more robust antiviral activity and acceptable safety profile [37]. Disseminated intravascular coagulation is also treated with nafamostat mesylate (DIC). It will aid in the management of DIC, as seen by increased fibrinolysis in COVID-19 patients [110].
In an in vitro research utilizing Vero E6 cells, nitazoxanide and its active component, tizoxanide, showed promise against MERS CoV and SARS CoV-2, with EC50 values of 0.92 and 2.12 μM, respectively [111]. In addition to coronaviruses, it exhibited action against norovirus, rotavirus, parainfluenza, respiratory syncytial virus, and influenza virus. This antiviral efficacy is due to the fact that the action mechanism is based on interfering with the virus’s host-regulated reproduction pathways rather than the virus’s particular pathways [112]. Nitazoxanide stimulates innate antiviral systems through amplification of cytoplasmic RNA sensing and type 1 IFN pathways. Nitazoxanide increases the expression of certain host systems that interfere with viral infection, allowing viruses to evade the host’s cellular defenses [113]. The nitazoxanide used against influenza viruses blocks the maturation of viral hemagglutinin at the post-translational stage [112]. Even if the findings aren’t promising, this medicine is used to treat some acute respiratory infections such as influenza. Although the in vitro activity of nitazoxanide against SARS-CoV-2 is promising, additional research is needed to understand its function in the management of COVID-19 (Figure 3).
Chemical structure of antiviral drugs.
Other various antiviral agents have been utilized to determine their impacts against SARS-CoV-2. Galidesivir is a nucleoside analog and a protease inhibitor [114]. This drug mechanism on COVID-19 is hypothesized to be similar to other antivirals, although its exact action mechanism is unknown. Another antiviral agent for COVID-19 is Tenofovir, which is known as an anti-influenza drug. It is an antiretroviral agent that targets DNA polymerase and inhibits virus replication [115, 116]. The action mechanism of this substance against COVID-19 requires further studies.
A fusion inhibitor is a group of antivirals that inhibit the fusion process during viral entry into the host cells. Some drugs are available with umifenovir and camostat mesylate representing antiviral activity against SARS-CoV-2 [117].
Some protease inhibitors such as lopinavir, darunavir, and atazanavir are used against COVID-19 [118]. In a computational study, drugs such as carfilzomib, valrubicin, eravacycline, lopinavir, and elbasvir inhibited the main protease in SARS-CoV-2. Further studies are required to confirm the efficacy of these drugs. Saquinavir and other protease inhibitors such as indinavir, amprenavir, and nelfinavir might also show the same effects against COVID-19 like protease inhibitors, due to resemblance between the structures. In a computer simulation, saquinavir and indinavir were found to suppress 3CLPro activity in SARS-CoV-2 [119]. In vitro inhibition of SARS-CoV-2 was shown to be inhibited by saquinavir, indinavir, amprenavir, and nelfinavir, with nelfinavir demonstrating the greatest suppression when compared with the others. In Singapore, saquinavir has been used to treat COVID-19 patients. Two other medications, raltegravir and paritaprevir, were shown to have the ability to block 3CLPro activity in SARS-CoV-2 in a computational investigation (Tables 1 and 2) [120].
Class | Drugs | Application | Emergency use for COVID-19 |
---|---|---|---|
Fusion inhibitor | Umifenovir (Arbidol) | Influenza | Singapore, China |
Protease Inhibitor | Lopinavir | HIV | USA, Japan, Singapore, Italy, China, IPC (Lopinavir-Ritonavir fix dose) |
Darunavir | HIV-1 | Italy (Darunavir-Ritonavir fix dose) | |
Atazanavir | HIV-1 | Singapore | |
Saquinavir | HIV-1 | Singapore | |
Nucleoside reverse transcriptase inhibitor | Emtricitabine | HIV-1 | Singapore (Emtricitabine-Tenofovir fix dose) |
Azvudine | HIV-1 | Singapore | |
Nucleotide reverse transcriptase inhibitor | Remdesivir | Ebola | WHO, IPC, USA, Singapore, Italy |
Favipiravir | (Avigan) Influenza | Singapore, Japan, Indonesia | |
Ribavirin | HCV | Singapore, IPC | |
Sofosbuvir | HCV | Singapore | |
Neuraminidase inhibitor (Virus release inhibitor) | Oseltamivir (Tamiflu) | Influenza A & B | IPC, Singapore, Indonesia |
Current use of existing antiviral drugs for COVID-19 [56].
International Pulmonologists’ Consensus includes the USA, India, Iran, China, Italy, Great Britain, EUA, Colombia, Egypt, Singapore, Romania, Ireland, Malaysia, Saudi Arabia, Sudan, Greece, and Bolivia.
Group | Drugs | Mechanism of action |
---|---|---|
Viral RNA polymerase inhibitors | Remdesivir (GS-5734) | RdRp inhibitor, prodrug, the analog of adenosine nucleotide |
Favipiravir | RdRp inhibitor, prodrug, the analog of guanosine nucleotide | |
Viral protein synthesis inhibitors | Ritonavir/Lopinavir | Inhibitor of protease |
Inhibitors of viral entry | Hydroxychloroquine Chloroquine | Increase in endosomal pH needed for the virus/cell fusion. Interfere with cellular receptor glycosylation of SARS CoV (ACE-2) |
Immunomodulators | Nitazoxanide | Interfere with host regulated pathways of virus replication, amplification of type 1 IFN pathways, and cytoplasmic RNA sensing |
Ivermectin | Inhibition of importin 1 heterodimer to inhibit the nuclear import of host and viral proteins |
Mechanism of action of antiviral drugs used for the treatment of COVID-19.
Another technique for combating SARS-CoV-2 infection is to inhibit RdRp and impede viral replication by targeting the reverse transcription process. Nucleoside reverse transcriptase inhibitors (NRTIs), nucleotide reverse transcriptase inhibitors (NtRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs), and nucleoside reverse transcriptase translocation inhibitors are a few examples of possible inhibitors (NRTTIs).
Other NtRTIs with comparable structural properties to remdesivir or ribavirin, such as adefovir, tenofovir alafenamide, tenofovir disoproxil, abacavir, ganciclovir, and didanosine, exhibit antiviral effectiveness against SARS-CoV-2. NRTIs (lamivudine, stavudine, zidovudine, emtricitabine, zalcitabine, and azvudine) and NNRTIs (efavirenz, nevirapine, delavirdine, and rilpivirine) may also have antiviral activity against SARS-CoV-2 [56].
Oseltamivir is a neuraminidase inhibitor used in preventing influenza Neuraminidase inhibitor drugs such as oseltamivir, zanamivir, and peramivir are antiviral drugs that inhibit the viral neuraminidase enzyme and are recommended for influenza and to block the release of viral particles out of host cells. Neuraminidase inhibitors are also used as empirical treatment in MERS-CoV infection [121, 122]. However, a combination of oseltamivir with ganciclovir and lopinavir/ritonavir is used to treat COVID-19 patients [40]. A computational study also supported synergistic effects of oseltamivir-lopinavir-ritonavir combination against SARS-CoV-2 [123]. Oseltamivir is used with ceftriaxone and terbutaline to treat COVID-19 [124]. A study showed that the CT scan of the lungs of a COVID-19 patient showed significant improvement after a three-day course of oseltamivir [19]. Oseltamivir has been used either with or without antibiotics and corticosteroids against COVID-19. In a clinical trial, oseltamivir is tested with chloroquine and favipiravir [93, 125].
Nowadays, the rising SARS-CoV-2 turned into a global threat. COVID-19 targets lung cells by connecting to ACE2 protein. This protein is largely produced in some tissues such as the bile duct, liver, gastrointestinal organs, esophagus, testis, and kidney as well as lung tissue. Thus, COVID-19 may damage these organs and tissues. With the global threatening caused by COVID-19, efficient therapy against COVID-19 is quickly necessary. Nevertheless, the development of new drugs for this disease is still a huge problem for people in the world, and we have none formally approved drugs against COVID-19 now. It is very crucial to cut off the extending of this virus owing to epidemic avoidance and checking techniques. We need to develop novel drugs and to find new therapy methods to prevent this outbreak and to treat COVID-19. The extent of the current pandemic, along with other factors, such as the lack of time to develop novel and effective agents against COVID-19, the high mortality rate, possible mutations in its genetic material and severe economic shocks to societies highlight the value of testing antiviral drugs present in our drug arsenal. Some drugs that have already started with repositioning may be effective against COVId-19 as well. It is essential to address the drug-drug interaction of the drugs in COVID-19 patients with comorbidities. We hope that the continuing studies may provide solutions for the prevention and therapy against the COVID-19.
Despite the fact that specific antiviral medications for COVID-19 have yet to be identified or authorized by the FDA, the usage of some currently existing antiviral agents that target various phases in COVID-19’s life cycle might be an alternate therapeutic strategy for combating the pandemic. Fusion inhibitors, protease inhibitors, and transcription inhibitors are just a few of the interesting antiviral medication classes to investigate. Apart from antiviral medicines, various interesting techniques to treating COVID-19 are being employed, such as convalescent plasma, which has been found to reduce viral load and patient morbidity. The effects of interferon (IFN)-α/β and IL-6R inhibitor1 have also been encouraging [126, 127, 128]. The introduction of several new technologies is likely to yield good benefits. The safety of patients should be prioritized while evaluating new SARS-CoV-2 vaccinations. Nanotechnology offers an effective new route for diagnostics and treatment techniques. The more distinctive nanoparticles operate as excellent antiviral medication delivery vehicles, increasing the procedure’s effectiveness. Finding appropriate diagnostic and therapeutic strategies for the fast and efficient care of severe COVID-19 patients is urgently needed [129, 130]. Different research on different CoV-induced diseases shows that using α-interferon, chloroquine phosphate, arabinol, remdesivir, lopinavir/ritonavir, and anti-inflammatory medications might result in encouraging clinical results for SARS-Cov-2 patients. Tocilizumab should be used as a therapy approach for severe COVID-19 pneumonia to achieve favorable results. Furthermore, further clinical studies with appropriate medications should be conducted on SARS-CoV-2 patients to demonstrate effectiveness and safety.
We are thankful to the Laboratory Medicine Department, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, 21955, Saudi Arabia, and Glocal School of Pharmacy, Glocal University, Mirzapur Pole, 247121, Saharanpur, Uttar Pradesh, India for providing necessary facilities.
The authors declare no conflicts of interest.
3CLpro | 3-chymotrypsin-like protease |
AAK1 | AP2-associated protein kinase 1 |
ACE2 | angiotensin-converting enzyme 2 |
ACEi | angiotensin-converting-enzyme inhibitors |
ADR | acute respiratory distress syndrome |
AIDS | acquired immunodeficiency syndrome |
Cm | maximum concentration |
CMV | cytomegalovirus |
COVID-19 | coronavirus disease 2019 |
DCGI | drug controller general of India |
DR | drug repurposing |
E | envelope protein |
ER | endoplasmic reticulum |
ERGIC | endoplasmic reticulum-Golgi apparatus compartment |
EVD | Ebola virus disease |
HA | hemagglutinin envelope glycoprotein |
HAV | hepatitis A virus |
HCMV | human cytomegalovirus |
HCV | hepatitis-C virus |
HE | hemagglutinin esterase |
HSV | herpes simplex virus |
ICU | intensive care unit |
INF-β | interferon |
Kb | kilo base pairs |
M | membrane protein |
MERS | Middle-East Respiratory Syndrome |
Mpro | main protease |
N | nucleocapsid |
NNRTI | non-nucleoside reverse-transcriptase inhibitors |
NRTTI | nucleoside reverse transcriptase translocation inhibitors |
NtRTI | nucleotide reverse-transcriptase inhibitor |
PLPro | Papain-like protease |
qRT-PCR | quantitative real-time polymerase chain reaction |
R0 | reproductive number |
RdRp | RNA-dependent RNA polymerase |
RNA | ribonucleic acid |
RVFV | Rift Valley fever virus |
S(P) | Spike protein |
S | glycoprotein spike |
SARS | severe acute respiratory syndrome |
SARS-CoV-2 | Severe acute respiratory syndrome coronavirus 2 |
SPs | spike proteins |
TMPRSS2 | transmembrane serine protease 2 |
US FDA | United States Food and Drug Administration |
WHO | World Health Organization |
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\\n\\nWe have adopted the Protocol to increase the number of readers of our publications. All our Works are more widely accessible, with resulting benefits for scholars, researchers, students, libraries, universities and other academic institutions. Through this method of exposing metadata, IntechOpen enables citation indexes, scientific search engines, scholarly databases, and scientific literature collections to gather metadata from our repository and make our publications available to a broader academic audience.
\\n\\nAs a Registered Data Provider, metadata for published Books and Chapters are available via our interface at the base URL: http://mts.intechopen.com/oai/index.php
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\\n\\nBASE - Bielefeld Academic Search Engine
\\n\\nOne of the world's most powerful search engines, used primarily for academic Open Access web resources.
\\n\\n\\n\\nA search engine for online catalogues of publications from all over the world.
\\n"}]'},components:[{type:"htmlEditorComponent",content:'The OAI-PMH (Open Archives Initiative Protocol for Metadata Harvesting) is used to govern the collection of metadata descriptions and enables other archives to access our database. The Protocol has been developed by the Open Archives Initiative, based on ensuring interoperability standards in order to ease and promote broader and more efficient dissemination of information within the scientific community.
\n\nWe have adopted the Protocol to increase the number of readers of our publications. All our Works are more widely accessible, with resulting benefits for scholars, researchers, students, libraries, universities and other academic institutions. Through this method of exposing metadata, IntechOpen enables citation indexes, scientific search engines, scholarly databases, and scientific literature collections to gather metadata from our repository and make our publications available to a broader academic audience.
\n\nAs a Registered Data Provider, metadata for published Books and Chapters are available via our interface at the base URL: http://mts.intechopen.com/oai/index.php
\n\nREQUESTS
\n\nYou can find out more about the Protocol by visiting the Open Archives website. For additional questions please contact us at ai@intechopen.com.
\n\nDATABASES
\n\nDatabases, repositories and search engines that provide services based on metadata harvested using the OAI metadata harvesting protocol include:
\n\nBASE - Bielefeld Academic Search Engine
\n\nOne of the world's most powerful search engines, used primarily for academic Open Access web resources.
\n\n\n\nA search engine for online catalogues of publications from all over the world.
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Ovarian cancers are heterogenous cancers where each subtype possesses a varied morphology and biologic behavior. Accumulating evidence has identified each of these subtypes characterized with specific pathways activated in each along with specific gene alterations. For example, high-grade serous ovarian cancer is characterized by universal TP53 mutation, mucinous ovarian cancer with KRAS mutation and clear cell or endometrioid ovarian cancers with ARID1A mutations. With the current focus of molecular-targeted therapies for cancer, such druggable markers serve as excellent targets for precision therapy and combination therapy. This chapter, provides an overview of the critical molecular pathways activated in the ovarian cancer subtypes with its druggable targets studied in ovarian cancer. We also highlight the implications of miRNAs in chemoresistance and sensitivity in the regulation of ovarian cancer.",book:{id:"10342",slug:"ovarian-cancer-updates-in-tumour-biology-and-therapeutics",title:"Ovarian Cancer",fullTitle:"Ovarian Cancer - Updates in Tumour Biology and Therapeutics"},signatures:"Febina Ravindran and Bibha Choudhary",authors:[{id:"334121",title:"Prof.",name:"Bibha",middleName:null,surname:"Choudhary",slug:"bibha-choudhary",fullName:"Bibha Choudhary"},{id:"335007",title:"Dr.",name:"Febina",middleName:null,surname:"Ravindran",slug:"febina-ravindran",fullName:"Febina Ravindran"}]},{id:"42501",title:"Implication of Clear Cell and Mucinous Histology",slug:"implication-of-clear-cell-and-mucinous-histology",totalDownloads:2362,totalCrossrefCites:0,totalDimensionsCites:0,abstract:null,book:{id:"3449",slug:"ovarian-cancer-a-clinical-and-translational-update",title:"Ovarian Cancer",fullTitle:"Ovarian Cancer - A Clinical and Translational Update"},signatures:"Jun Naniwa, Hiroaki Itamochi and Junzo Kigawa",authors:[{id:"158925",title:"Prof.",name:"Junzo",middleName:null,surname:"Kigawa",slug:"junzo-kigawa",fullName:"Junzo Kigawa"}]},{id:"74781",title:"The Anti-Cancer Effects of Anti-Parasite Drug Ivermectin in Ovarian Cancer",slug:"the-anti-cancer-effects-of-anti-parasite-drug-ivermectin-in-ovarian-cancer",totalDownloads:900,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Ivermectin is an old, common, and classic anti-parasite drug, which has been found to have a broad-spectrum anti-cancer effect on multiple human cancers. This chapter will focus on the anti-cancer effects of ivermectin on ovarian cancer. First, ivermectin was found to suppress cell proliferation and growth, block cell cycle progression, and promote cell apoptosis in ovarian cancer. Second, drug pathway network, qRT-PCR, and immunoaffinity blot analyses found that ivermectin acts through molecular networks to target the key molecules in energy metabolism pathways, including PFKP in glycolysis, IDH2 and IDH3B in Kreb’s cycle, ND2, ND5, CYTB, and UQCRH in oxidative phosphorylation, and MCT1 and MCT4 in lactate shuttle, to inhibit ovarian cancer growth. Third, the integrative analysis of TCGA transcriptomics and mitochondrial proteomics in ovarian cancer revealed that 16 survival-related lncRNAs were mediated by ivermectin, SILAC quantitative proteomics analysis revealed that ivermectin extensively inhibited the expressions of RNA-binding protein EIF4A3 and 116 EIF4A3-interacted genes including those key molecules in energy metabolism pathways, and also those lncRNAs regulated EIF4A3-mRNA axes. Thus, ivermectin mediated lncRNA-EIF4A3-mRNA axes in ovarian cancer to exert its anticancer capability. Further, lasso regression identified the prognostic model of ivermectin-related three-lncRNA signature (ZNRF3-AS1, SOS1-IT1, and LINC00565), which is significantly associated with overall survival and clinicopathologic characteristics in ovarian cancer patients. These ivermectin-related molecular pattern alterations benefit for prognostic assessment and personalized drug therapy toward 3P medicine practice in ovarian cancer.",book:{id:"10342",slug:"ovarian-cancer-updates-in-tumour-biology-and-therapeutics",title:"Ovarian Cancer",fullTitle:"Ovarian Cancer - Updates in Tumour Biology and Therapeutics"},signatures:"Xianquan Zhan and Na Li",authors:[{id:"223233",title:"Prof.",name:"Xianquan",middleName:null,surname:"Zhan",slug:"xianquan-zhan",fullName:"Xianquan Zhan"},{id:"438269",title:"Dr.",name:"Na",middleName:null,surname:"Li",slug:"na-li",fullName:"Na Li"}]},{id:"43345",title:"Surgical Treatment of Ovarian Cancer",slug:"surgical-treatment-of-ovarian-cancer",totalDownloads:2960,totalCrossrefCites:1,totalDimensionsCites:4,abstract:null,book:{id:"3449",slug:"ovarian-cancer-a-clinical-and-translational-update",title:"Ovarian Cancer",fullTitle:"Ovarian Cancer - A Clinical and Translational Update"},signatures:"Lucas Minig, M. 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He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. 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He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. 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He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. 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Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. 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He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. 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Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. 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