Morbidity and fatality rates have skyrocketed because of the coronavirus disease 2019 (COVID-19) epidemic, making it a worldwide health emergency. New treatment medicines are desperately needed to combat this illness. As of the most current information available, which was on 26 April 2023, there have been a total of 764,474,387 confirmed cases documented around the globe, which has directly resulted in 6,915,286 fatalities (i.e., https://covid19.who.int/). It wasn’t until December 2019 that scientists confirmed the existence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or coronavirus (CoV) illness, also known as COVID-19. CoVs are in the family Coronaviridae. They have a genome that is an enclosed, single-stranded, positive-sense RNA that ranges in length from 26 to 32 kilobases [1]. Humans are only known to be infected by alpha and beta CoVs, which fall into two of the four genera: alpha and beta [1, 2]. There is a 76.5% degree of similarity between the genomic sequences of SARS-CoV-2 and SARS-CoV. The RNA genome of the SARS-CoV-2 virus, which belongs to the family Coronaviridae and is positive-sense and single-stranded, is encased in a membrane envelope inside the virus. The Middle East respiratory syndrome coronavirus (MERS-CoV) and SARS-CoV viruses are members of the genus beta CoV, of which SARS-CoV-2 is a member. There are at least four structural proteins in SARS-CoV-2: the spike protein (S-protein), the envelope protein, the membrane protein, and the nucleocapsid protein [3]. The virus causes minor or no symptoms to death and is characterized by fever, dry cough, and fatigue [4].

The novel CoV (2019-nCoV) was initially named after its discoverer [5]. Angiotensin-converting enzyme two (ACE2) is the receptor for SARS-CoV-2 entry into epithelial cells lining the lower respiratory tract in recent studies [6–8]. Structural analysis and pharmacological experiments have shown that the spike of SARS-CoV2 interacts with human ACE2 receptors [9]. SARS-CoV-2 S1 S-protein interacts with ACE2 via its receptor binding domain (RBD), which then triggers membrane fusion mediated by the S2 domain and the incorporation of viral RNA into host cells. SARS-CoV-2 RBD binds to ACE2 through hydrogen bonds and salt bridges, resulting in a stable interaction with a dissociation constant [dissociation constant (Kd), in nano molar (nM)] [10].

CoV infection often results in a respiratory illness that is either mild or moderate in severity, and the majority of infected individuals recover entirely without requiring any medical treatment. COVID-19 infection, on the other hand, may cause severe respiratory distress in persons who already have preexisting diseases such as diabetes, respiratory disorders, cardiovascular difficulties, cancer, and so on, which require urgent treatment [11]. Due to their immunosuppression, cancer patients are more susceptible to these infections than others. According to research [12], people with cancer had roughly two times the risk of contracting COVID-19 compared to the general population. According to the findings of a research project that was carried out in Italy, it was discovered that among the 355 fatalities that COVID-19 caused, 20% of patients had aggressive cancer [13].

It is essential to identify highly conserved proteins across multiple CoVs as targets for antiviral therapy against SARS-CoV-2; since there is a significant possibility that CoVs may change to produce a new infectious virus. Many CoVs target enzymes involved in replication, such as RNA-dependent RNA polymerase (RdRp) and protease [6, 4]. Drugs that inhibit conserved proteases, such as main protease (Mpro) and papain-like protease (PLpro), can hinder viral replication and proliferation by interfering with the processing of essential viral polypeptides after they have been translated. This fact reduces the likelihood that mutations will lead to treatment resistance [14–16]. The CoV polyprotein encodes two proteases, a PLpro and a 3-C-like protease (Mpro). Non-structural proteins (Nsps) translated into cells are processed and secreted by combining two proteases (PLpro). SARS and MERS-CoV drug development targets included PLpro and Mpro proteases [17–20]. There is no cure for COVID-19; however, several therapeutic avenues are being investigated, and multiple clinical trials are underway [21–24].

There has been a great deal of research within herbal medicine in regard to anti-CoV agents since the outbreak of SARS. Among the most attractive targets are receptor and protein inhibitors. A number of compounds, including alkaloids (like tryptanthrin), flavonoids (like herbacetin), steroids (such as glycyrrhizic), tannins (such as pedunculagin), quinones (such as emodin), and stilbenes (such as curcumin), inhibit SARS-CoV-2 replication and transcription, and may therefore be of value in early virus cycles [25]. Many research groups were forced to seek out new synthetic molecules that would be effective against SARS-CoV-2 due to the COVID-19 pandemic. By expressing the 3-chymotrypsin-like protease (3CLpro) protein, the virus is capable of proteolyzing nonfunctional viral proteins into functional ones. A novel series of fused 1,2,3-triazole derivatives has been shown to inhibit 3CLpro protein [25]. Several synthetic drugs have shown the ability to inhibit CoV infection in vitro. During viral entry, MDL28170, trypsin, and leupeptin inhibit the activity of endosomal proteases [26], preventing the spread of infection. In the study, ribavirin, penciclovir, favipiravir, nafamostat, nitazoxanide, remdesivir, and chloroquine were found to be the most effective drugs against SARS-CoV-2. Hydroxychloroquine has been tested for its effectiveness in blocking virus infection in a number of clinical trials [27]. COVID-19 therapeutic strategies could, however, be improved through antibodies. Many patents are currently being examined to determine whether antibodies against COVID-19 can improve therapeutic outcomes [25]. Plasma from patients who have been cured can be used to treat patients with COVID-19. A clinical vaccine trial uses antigens of SARS-CoV-2 to direct the immune system against these antigens and lower COVID-19 complications. There have only been some vaccine trials that have reached the third stage of clinical development [25].

The urgent need to address COVID-19 is not met by the lengthy de novo medication development procedure [28]. Finding new medications based on the repurposing strategy is the most pressing option for combating COVID-19 [3]. These results led to the use of X-ray crystallography and structural analyses of the SARS-CoV-2 RdRp to develop novel antiviral drug designs and drug repurposing techniques [29, 30]. Attempts to find novel treatment agents for COVID-19 via drug repurposing hold much promise. As part of therapeutic repurposing, current medications are tested for their potential to block the viral protease that catalyzes the cleavage of the viral S-protein. This strategy has the benefit of being able to move quickly since a significant number of the medications have previously undergone clinical testing and are, as a result, recognized to be safe for use in people.

As such, a thorough virtual screening (VS) investigation was conducted using a library of Food and Drug Administration (FDA)-approved medications to identify compounds capable of binding to the three primary molecular targets of SARS-CoV-2 [Protein Data Bank (PDB)] [31, 32]. Because of its utility in the quest for novel therapies for COVID-19, VS has become a standard computational tool in drug development. Using computational approaches, VS evaluates a pool of therapeutic options. This strategy is fast and effective, allowing for the rapid screening of many molecules. A routinely used flowchart for the VS process is shown in Figure 1.

When looking for novel treatment drugs to treat COVID-19, adopting VS may be pretty beneficial due to its numerous benefits. The use of VS allows for the screening of vast numbers of compounds quickly and effectively. Moreover, VS may be used to find compounds structurally related to existing medications. The potential benefits of this method include the speed with which promising medication candidates may be found. The use of a trustworthy computational technique to reliably anticipate binding free energies (BFE) is crucial for the success of any VS attempt [33]. VS has a poor success rate and predicts primarily false positives. The authors successfully designed a system for VS that considerably cuts the number of false positives by combining two types of filtering: pre-docking filtering, which is based on form similarity, and post-docking filtering, which is based on interaction similarity [16]. VS of current drugs is often used as a first step in repurposing them to treat emerging disorders like COVID-19; this is then followed by experimental validation. However, the actual hit rate is generally relatively low when using standard computer methodologies [33]. Moreover, various epidemiological and systems biology-based researchers have been in this field [34–36].

This article will explore how VS may be used to find prospective medication candidates for COVID-19. VS concepts will be discussed initially. After that, we’ll explain how we plan to utilize VS to identify potential novel COVID-19 treatments.

Antiviral cytotoxic T (CD8+ T) lymphocytes cell responses are triggered by SARS-CoV-2 and then directed towards tumor cells based on their cancer-specific epitopes. The potential therapeutic advantages of repurposing antiviral CD8+ T cells against malignancy are enormous. In anticancer immunotherapy, CD8+ anti-tumour T cells are generated in response to auto-immunogenic epitopes strongly present in tumor antigens. It is possible to show synthetic viral epitopes on the surface of cancer cells to reprogram CD8+ T lymphocytes, which would typically target and destroy viruses, to target and destroy tumors instead. For effective cancer immunotherapy, CD8+ T cells are crucial. It’s possible to redirect CD8+ T lymphocytes toward tumors by displaying synthetic viral epitopes on the surface of cancer cells [37].

Interferons significantly impact various immune responses, including antiviral responses, adaptive immunological responses, and fungal and viral immune responses. A little window of opportunity exists for treating COVID-19 with anti-interleukin-based drugs; some patients may have different problems. For the treatment of severe ARDS brought on by COVID-19, the experimental data point to the potential benefit of tocilizumab and selinexor. The immunological response to COVID-19 in humans may be modulated by the monoclonal antibody C-C chemokine receptor type five (CCR5; immune and non-immune). Anti-interleukin-6 (IL-6) monoclonal antibodies may mitigate COVID-19’s inflammatory storm. JAK inhibitors, leronlimab, and Bacillus Calmette–Guérin (BCG) are a few of the medications that researchers are testing to treat COVID-19. Lenalidomide, a drug often used in treating multiple myeloma, is also being investigated for its potential use in treating COVID-19 in elderly patients with mild to moderate symptoms [38].

Recent studies, including docking and simulation methods, employed the replication delay protein (RdRp) from SARS-CoV-2. The CASTp 3.0 program used computational geometry techniques to identify the active site of SARS-CoV-2-RdRp- associated nucleotidyl transferase domain (NiRAN). Sixteen medications were validated by AutoDock docking to the Computed Atlas of Surface Topography of Proteins (CASTp) predicted active site of the viral domain. Molecular mechanics with generalised born and surface area (MM-GBSA) solvation was applied to the compounds that had the most incredible docking findings. Using a default configuration of molecular dynamics (MD) software (i.e., Desmond), the authors simulated the stability of the SARS-CoV-2-RdRp-NiRAN domain-ligand complex [39].

To dock 27 drugs commonly used to treat lung cancer, Pingali et al. [40] opted for LigPrep. Molecular docking and calculations of binding affinity were used to locate the appropriate ligand for the proteins that were being targeted. Ten ligands with a docking score of 4.0 were selected for additional screening and evaluation against the RdRP. The MD simulation was conducted in Groningen MAchine for Chemical Simulation (GROMACS) 2018.2 using the charmm36-mar2019.ff force field and all-atom optimized potentials for liquid simulations (OPLS-AA) for protein. The number of Hydrogen Bond interactions, Radius of Gyration, and root mean square deviation of the structural order were calculated using GROMACS software in a MD study.

A Lamivudine docking investigation was performed utilizing the recently released cryo-EM structure of SARS-CoV-2-RdRp. Lamivudine may prevent cytidine triphosphate (CTP) from catalyzing SARS-CoV-2-RdRp RNA Polymerase by inhibiting chain termination. Neither monkey nor human malignant cells showed any inhibition of SARS-CoV-2 replication when treated with Lamivudine; however, it may help treat or prevent COVID-19.

On the other hand, antiretroviral nucleoside/nucleotide analogs (ANNAs) were made to stop viruses like Ebola and human immunodeficiency virus (HIV) from making RdRp. Still, it has been found that they can be used against a different group of viruses. Lamivudine has been given to HIV/hepatitis C virus (HCV) patients for over 25 years. Even though it has been used a lot, it hasn’t been linked to too many severe side effects, which makes it a safe drug that can be used alone or with other antivirals. Since viruses cause certain human malignancies, the concept that ANNAs may treat cancer is not new. Remdesivir is another pro-drug that attaches to the Severe Acute Respiratory Syndrome (SARS) virus. However, it does so with a lower affinity than lamivudine [41].

Hyaluronic acid (HA)-based nanoparticles are uptaken more readily with doxorubicin (DOX) in radiation therapy, drug resistance is overcome, and side effects are reduced [42]. Furthermore, smart HA-based delivery systems are capable of developing new drugs as well as responding to internal and external stimuli. In addition to DOX and other antitumor compounds, several types of gene therapies based on RNA or DNA can enhance their effectiveness. HA-based delivery systems are effective in delivering drugs or genes with DOX [42].

In addition to controlling proliferation and migration rates, exosomes modulate the tumor microenvironment and are widely recognized as key players in cancer progression and therapy. The use of exosomes as carriers of genetic tools and antitumor agents is an important component of controlling the progression of cancer [43].

P-glycoproteins (P-gp) are to blame for DOX resistance since they transport the medication. The presence of dox resistance may be determined by investigating the molecular pathways that control P-gp. These pathways include nuclear factor erythroid 2-related factor 2 (Nrf2), hypoxia-inducible factor 1-alpha (HIF-1a), microRNAs (miRNAs), and long noncoding RNAs (LncRNAs). Since DOX’s anticancer action is improved when adenosine triphosphate (ATP) is low, it seems sense that P-gp activity is hindered when ATP levels drop. The delivery of DOX together with anticancer drugs and genes that enhance DOX’s cytotoxicity may be accomplished by the use of nanoarchitectures like liposomes, micelles, polymeric nanoparticles, and solid lipid nanocarriers. And again as mentioned before, the HA can be beneficial to the surfaces of nanocarriers for improving the overall performance considering the long run [44].

According to the most recent and cutting-edge approaches in cancer immunotherapy, antiviral CD8+ T cell immunity may be able to be used in cancer immunotherapies against various types of cancer. Infections or vaccines with SARS-CoV-2 cause this immunity [37].

Medical professionals and scientists have struggled to develop effective therapies for the deadly COVID-19 epidemic because of the massive loss of life it has caused. The repurposing of existing medications may fulfill the unmet need. The treatment of COVID-19 may be able to use many different anticancer medications in some capacity. The proliferative effects of these medicines are the primary focus of their development. Cytotoxic drugs and immune modulators can potentially suppress cancer patients’ humoral and cellular immunological responses, which may result in developing secondary infections and other problems. Patients hospitalized with COVID-19 should pay attention to titrating the medications to avoid over-suppression and further difficulties [38].

Patients with gastric cancer (GC) who are infected with COVID-19 can take one of the potential medications. There is a high binding affinity between these medicines and the Nsp12/RdRp region of SARS-CoV-2. After using docking to find drugs that would have a good chance of binding to the RdRp-NiRAN domain of SARS-CoV-2, four potent drugs with high binding affinities to the virus were selected. Due to the lack of a standard therapeutic option, medication repurposing is now viable for COVID-19 patients with GC. Patients with GC infected with SARS-CoV-2 may take advantage of these medications [39].

On the other hand, Pingali et al. [40] tested 27 medicines for treating small cell lung cancer (SCLC) for their ability to inhibit COVID-19’s RdRP protein and utilize the pharmaceuticals to treat both SCLC and COVID-19. For the RdRP complex, paclitaxel, gefitinib, and dacomitinib are projected to be suitable ligands [40].

Patients undergoing radiation or chemotherapy may benefit from Lamivudine since it reduces the risk of their Hepatitis virus becoming active again during treatment. Hepatocellular carcinoma (HCC) might be avoided in the first place if Lamivudine and similar ANNAs were effective in preventing chronic HBV and cirrhosis. Lamivudine, originally developed as a cancer treatment, may also be evaluated for its potential as a treatment for SARS-CoV-2 and COVID-19. Additional in vitro and in vivo testing of this chemical is required to determine whether or if it is effective against SARS-CoV-2 RdRp, either alone or in combination. Future theoretical and experimental research may benefit from the insights provided by this study. If these studies are successful, patients with cancer and COVID-19 will hopefully benefit from an improvement in their quality of life and their prognoses [41].

The SARS-CoV-2 S-protein was virtually screened for inhibitors using drug-likeness screening, molecular docking, and pharmacokinetic features evaluation. Researchers used molecular docking to zero in on the amino acid residues in ATV, PRZ, and binding sites responsible for the protein’s interaction with the spike. The WT-ATV and DLT-PRZ complexes were the most structurally stable over the simulation duration. In other words, the two medications were approved by the FDA after being shown to treat COVID-19 effectively. By shedding light on the underlying molecular mechanisms of inhibition, this work will significantly contribute to creating new SARS-CoV-2 inhibitors [45].

To stop SARS-CoV-2 from infecting human cells, technique of de Oliveira et al. [46] included looking at the virus’s S-protein before it connected with the human ACE2 receptors. Using binding affinities below –8.1 kcal/mol, they found anti-SARS activity in 14 herbal isolates and ten medicines. MD simulations show that the ligands for Lig8522, Lig8970, and Lig6843 were contained inside the RBD region for the simulations [46].

Medication repositioning was used in study of Tsuji [47] to locate potential medications that may be applied to treating SARS-CoV-2. These possible treatments might be subjected to further testing to evaluate whether or not they have anti-SARS-CoV-2 capabilities. The findings of these studies could be used to develop more specific anti-SARS-CoV-2 drugs [47].

The 3CLpro is a prospective therapeutic target for SARS-CoV-2 because of its central role in the viral replication cycle. In the current investigation, structure-based methods were used to repurpose anti-HIV pharmaceuticals and explore TCMs databases for compounds that may inhibit 3CLpro [48].

The residues of 3CLpro’s active site to those of databases of traditional Chinese medications, a structure-based method were compared by Arun et al. [49]. It is essential to conduct clinical trials of saquinavir and TCM5280805, two suspected inhibitors of 3CLpro, for the treatment of SARS-COV-2 [49].

It was revealed via computational and statistical techniques that Simeprevir, Ergotamine, Bromocriptine, and Tadalafil had the maximum binding affinity to the significant protease of SARS-CoV-2. Bromocriptine was also shown to have this affinity. There are many non-covalent interactions between these drugs and the residues in Mpro’s binding site [50].

Several existing medications, including rutin, boceprevir, epirubicin, nelfinavir, and bortezomib, show promise as inhibitors of SARS-CoV-2. These medicines are structurally similar to N3 and X77, two ligands cocrystallized with SARS-CoV-2 Mpro, and have identical binding patterns. This research found five promising COVID-19 treatments that extend the previously announced SARS-CoV-2 Mpro inhibitors [2].

D3Targets-2019-nCoV is a website the authors built for target prediction and VS using data on protein structures and ligands. The findings demonstrated that DL-based models are far better at finding COVID-19 hits than other approaches [51].

The sole current option for treating SARS-CoV-2 is the creation of pan-viral medicines based on highly conserved portions of existing medications. There were 129 medications evaluated for their potential usefulness in this research. There is evidence that the antiviral drugs beclabuvir, nilotinib, tirilazad, trametinib, and glecaprevir can stop the spread of COVID-19. To fully assess the efficacy of these putative inhibitors, however, more in vivo testing is required [75].

Compared with discovering new pharmaceuticals from scratch, the method of repurposing existing drugs for new therapeutic uses is more efficient in terms of the amount of time and the amount of money it saves, respectively. In some instances, the potential for acute toxicity from repurposed medications may be too great to justify the use of the drug in question as an antiviral, especially if the benefit is as yet unclear. As a result, an accurate evaluation of the probable candidates’ toxicity levels is required. In silico screening of FDA-approved drugs against SARS-CoV-2 proteins may help speed up clinical trials for drugs with a known safety profile [52].

A VS for commercially available drugs using the 3CLpro molecular model and provided 16 potential options for further study was conducted by Chen et al. [53]. Edipasvir and velpatasvir, two antiviral medications, stand out as promising treatments for the new CoV because of their low risk of causing the common but debilitating side effects—fatigue and headache. Epclusa (velpatasvir/sofosbuvir) and Harvoni (ledipasvir/sofosbuvir) are two combination drugs that have shown great promise as therapies for hepatitis C because of their ability to inhibit two separate viral enzymes [53].

According to the results of molecular docking assays, GR hydrochloride and GNF-5 predominantly link with hotspot 353, while RS504393, TNP, and Eptifibatide acetate engage with hotspot 31 via both polar and hydrophobic interactions. KT185’s affinity for hotspot 31’s S-RBD residue was predicted to block SARS-S-RBD. CoV-2’s. Some FDA-approved medications that were discovered through VS of compound libraries show promise as potential inhibitors of RNA viruses. These medications are thought to work by blocking viral entry or replication or reducing inflammation. The SARS-CoV virus evades the body’s defenses by binding to chemokine receptors. The inflammation caused by viral infection in cells and tissues may also be mitigated by these molecules [54].

Bedaquiline, glibenclamide, and miconazole, three medicines (two oral and one buccal), were shown to be effective Mpro inhibitors against COVID-19. These medications treat fungal infections, multi-drug resistant TB, and type 2 diabetes [76].

As part of the other authors’ efforts to streamline the drug development process, they have established two standardized procedures for repositioning studies that skip the time-consuming yet crucial pharmacokinetics assessment stage. Validation findings for these processes have been very positive, resulting in the selection of seven prospective medications that show encouraging signs of being effective against the CoV [55].

A combined structure-based VS technique may uncover possible irreversible Mpro inhibitors, which can be employed in creating antiviral medicines and potentially vaccinations using bioinformatics tools (FDA-approved drugs including vaborbactam, cimetidine, ixazomib, scopolamine, bicalutamide, and riociguat). Their study illustrates a combined cheminformatics process for identifying medications that can target diverse proteins of viruses [56].

Using drug repositioning, the authors of this research identified prospective anti-SARS-CoV-2 medication candidates and made predictions about therapies produced for the treatment of COVID-19. Results showed promise for the identification technique in rapidly repurposing medicines to manage COVID-19 [57].

In the pharmaceutical sector, production-linked incentive (PLI) research is crucial. Due to asymmetries in how these physicochemical characteristics are represented in the training dataset, the current techniques for predicting PLI suffer from lengthy compute times and biases. SSnet performs better on human and C. elegans datasets than other well-known ML algorithms. Additionally, it is much quicker than conventional VS methods. Accurate predictions of all three types of ligand binding sites (active, allosteric, and cryptic) are made using SSnet, which may be used with the classic VS/docking approach as a pre-screen to filter ligands. It is also easy for people of all levels of computer knowledge to use. Using their secondary structures as a common denominator, they proposed a latent space for proteins that may be utilized to make bioactivity comparisons [77].

Drugs already in use, such as ibrutinib and zanubrutinib, may be repurposed to help patients with COVID-19. They prevent viral polyproteins from being assembled, replicated, and post-translationally processed, all of which are a part of the inflammatory cytokine storm mediated by BTK [58].

To construct medications rationally, it is necessary to consider the high degree of flexibility present in the active site of the SARS-primary CoV-2 protease (potent active sites are shown in Figure 3). Using three different Mpro conformers, Jiménez-approach Alberto was able to isolate nine molecules that might potentially be repurposed as a treatment for COVID-19 [59].

This research has led to the identification of several therapeutic strategies that offer promise for combating the SARS-CoV-2 pandemic. Oxytetracycline, naringin, kanamycin, cefpiramide, salvianolic acid b, teniposide, etoposide, and DOX were the hits that showed the most promise in the fight against cancer. After that, the researchers screened the chemical space using a pharmacophore search, and they found a variety of novel scaffolds. Some examples of these new scaffolds are the fluoroquinolone ZINC001570001158 and the sulfonamide ZINC000016429284. In addition, the findings of the research point to the possibility that antibiotics that are commercially available right now, most notably oxytetracycline, may have a substantial impact on the ability of SARS-CoV-2 to create 3CLpro [60].

The supercomputer MOGON also provided some ideas for potential inhibitors of the SARS-CoV-2 virus. The therapeutic potential for SARS-CoV-2 includes several medicines that are currently on the market for illnesses caused by encapsulated ssRNA viruses, such as cancer, HCV, and other diseases [61].

The RBD of SARS-CoV-2 S-protein and human ACE targets current medications that have been identified via computational studies of drug repurposing (ACE2). An MD simulation of RBD produced an ensemble of structures. In the VS process, three significant conformers were found and analyzed [62].

Researchers ran an in silico high throughput screening on 5,491 compounds from multiple databases to find SARS-CoV-2 proteases PLpro and 3CLpro inhibitors that might treat COVID-19. Ergotamine and abivertinib are good drug development candidates for COVID-19 treatment [63].

Numerous physiologically active structural analogs from DrugBank, including the antiviral medicines indinavir, sofosbuvir, cidofovir, and darunavir, have shown promise in fighting SARS-CoV-2 infection [64].

Medication repurposing using VS was used to track down CD147 inhibitors, ACE2 inhibitors, and RdRp inhibitors for this study. Based on the data, the best g-values were found for the combinations of ledipasvir and ACE2, estradiol benzoate and CD147, and vancomycin and RdRp. Significant viral receptor inhibition can stop COVID-19 infection. Possible choices for more study included paritaprevir and vancomycin [30].

A chemical library of several thousand human-licensed medicines using MM-assisted SBVS was searched by Teralı et al. [65] to uncover drugs that might interact with human ACE2 and prevent SARS-identification CoV-2’s. All or part of the eight found medications have proven in vitro and ex vivo effectiveness against COVID-19. Hence, they should be brought into the clinics as monotherapy or in conjunction with other treatments [65].

Fenoterol and riboflavin ligands on grid 1 (site S1), Cangrelor on grid 2 (site 2), and Vidarabine on grid 4 (sites 1 + 2) all exhibited intense contact with the RBD area. These potential inhibitors of S1:ACE2 need to be investigated in vitro to determine whether or not they are effective [10].

The Mpro of the recently identified COVID-19 was compared to the Mpro of SARS and MERS CoV, which were two former CoV pandemics. These comparisons were made using molecular modeling techniques. COVID-19 Mpro has a stronger genetic relationship to SARS Mpro than vice versa. In a VS competition against COVID-19 Mpro, it was shown that curcumin had the lowest level of effectiveness when compared to a panel of antivirals, vitamins, anti-microbial, and other systemically acting drugs (known Mpro inhibitors). Alternative applications are suggested for vitamin B12, nicotinamide, and the nucleoside reverse transcriptase inhibitors ribavirin and telbivudine [20].

As an alternative therapy method for COVID-19, Hage-Melim suggests new possible Mpro inhibitors of the SARS-CoV-2 virus in this study. These compounds’ ADME/Tox characteristics were superior to those of the medicines being evaluated against COVID-19, and they maintained a network of favorable intermolecular interactions with the novel CoV. For the future therapy of patients with this SARS, the authors recommend their most promising chemical in addition to Apixaban [66].

Another study effectively used a mix of molecular docking-based computational screening and in vitro testing of repurposed medicines to identify compounds that inhibit SAR-CoV-2 3CLpro. The level of 3CLpro inhibition shown by lapatinib was the greatest of any drug. Van der Waals interactions primarily drove the binding of lapatinib to 3CLpro. Some of the drug’s stability comes from hydrogen bonds formed with the N142 and E166 residues. To create effective SAR-CoV-2 3CLpro inhibitors, it is best to use both in silico screening and experimental research [67].

Due to its importance in viral replication, the SARS-CoV-2 Mpro might be a therapeutic target. The perfect candidate would be substantial enough to fill the pocket. They employed a hybrid strategy using VS and molecular docking methods to search through a collection of natural chemicals and structural mimics identified or synthesized by the Mazzini team. To enter the protein binding pocket and access the catalytic dyad, the most promising candidates have shown impressive abilities as potential scaffolding for creating superior inhibitors. CPT, Leopolis acid, and lamellarin D derivatives are desirable options. To develop effective SAR-CoV-2 3CLpro inhibitors, it is best to use both in silico screening and experimental research [68].

The predictive capacities of the provided docking approaches were assessed using a database of 500 compounds previously established as potent inhibitors of the SARS-CoV 3CLpro enzyme. For each docking simulation, the authors generated numerous poses for each ligand and considered all potential isomers/states for molecules that may exist in more than one configuration. Consensus models were built after calculating the resultant binding and isomeric space. The top-ranked compounds include a range of heterogeneous molecules, many of which have recently been shown to inhibit SARS-CoV-2 3CLpro. The findings encourage the repetition of comparable docking techniques by simultaneously considering both monomers of various representative resolved structures. Despite the significant conservation shared by SARS-CoV 3CLpro and genuine inhibitors, current prediction models benefit from using known inhibitors. Post-docking instruments utilized to dock SARS-CoV-2 3CLpro successfully had significantly varying roles, but they all helped get the job done [69].

Using the FEP-ABFE prediction method, Li et al. [33] could isolate 16 potent inhibitors of SARS-CoV-2 Mpro from currently available drugs. The efficiency of 14 of these inhibitors was confirmed. Clinical studies are underway for DIP, the most potent inhibitor presently known. Newer drugs that reduce SARS-CoV-2 Mpro include candesartan cilexetil, hydroxychloroquine, and chloroquine. In the future, these drugs might be used as templates for creating treatment options with increased effectiveness against SARS-CoV-2 Mpro. With a stunning 60% hit rate, FEP-ABFE prediction-based VS has shown to be very effective [33].

Jang found three promising SARS-CoV-2-inhibiting drug combinations at therapeutic dosages. Tipifarnib and Omipalisib, Tipifarnib and Remdesivir, and Omipalisib and Remdesivir, respectively, are the medication combinations in question. Based on promising results from SARS-CoV-2 inhibition testing in cells, the authors advise moving on with preclinical and clinical trials using omipalisib and three-drug combinations [16].

Medications with untapped therapeutic potential may be found via computational analyses—patients at an increased risk for contracting COVID-19 due to cardiovascular diseases. The data may be used to choose medications for in vitro and in vivo investigations, with Saquinavir and Beclabuvir being the best new protease inhibitor options for COVID-19 treatment [70].

Many promising lead compounds were identified by using the SARS-CoV-2-RBD crystal structure with a VS of clinically approved drugs. Furthermore, the binding free energy of the SARS-CoV-2-RBD complex was lowest for the Diammonium Glycyrrhizinate complex [71].

For the treatment of SARS-CoV-2, three antiviral medicines were selected from the currently available drug library. Three diagnostic compounds were identified by screening an authorized drug library that showed promise in interacting with the Mpro protein; structural alterations to these three candidates might lead to valuable molecules. Twenty compounds were found to interact with the viral Mpro protein by a rigorous VS of the Asinex BioDesign library [72].

Compounds found in Cluster Two were tested for hits against 3CLpro, and two were re-docked with four distinct PDB structures of 3CLpro for further analysis [73].

An exhaustive theoretical investigation was carried out by us, in which the authors used the approaches of RBVS, docking, MD simulations, and MM-PBSA computations. In addition to Remdesivir, our seven possible hits revealed the ability to bind to three of the most critical SARS-CoV2 targets efficiently. Remdesivir, elbasvir, and ritonavir are the most promising medications for this purpose, as shown by our findings [31].

SARS-2’-O-MTase CoV-2’s Nsp16, which causes COVID-19, structurally and functionally was examined by Jiang et al. [74]. Inhibitors of 2’-O-MTase have been found in 17 different drugs, several of which are currently in clinical use. Further experimental and/or clinical testing of hesperidin, rimegepant, gs-9667, and sonedenoson, among other potential possibilities for treating COVID-19, is warranted [74]. Finally, the extracted chemicals from several studies are listed in Figure 4.

Taking all information mentioned above together into consideration, the target of evaluation for a ligand capable of inhibiting a receptor specifically for various types of SARS-CoV2 viral proteins was only determined by calculations of energy binding affinity values using either molecular docking scores (e.g., AutoDock Vina, iDock, AutoDock, DockThor, and Glide) or MD simulation denoted by G (e.g., MM-PBSA and MM-GBSA methodologies). However, no experimental values were reported on confirmation of the calculated values.

Due to hardware limitations or a lack of target proteins, previously unavailable approaches are now widely available in the in-silico docking field [78]. Researchers are increasingly interested in this topic because of the PDB’s large collection of macromolecules and its fast-advancing hardware components. As pharmaceutical companies increasingly use high-throughput screening (HTS) for discovering new, innovative drug substances, a more economical alternative is needed. The in silico equivalent of HTS, VS, allows you to test a large number of compounds in a short amount of time. Even though some programs are capable of generating poses similar to those found in crystal structures, protein-ligand docking has several limitations. In most docking methods, proteins are considered rigid for practical reasons, while ligands and proteins are treated as flexible [79, 80]. Further, unlike what we might expect, the structure of ligands can greatly influence docking scores and pose scores [81]. The docked poses can therefore be drastically affected by even minor changes in ligand input conformation [81]. The scoring functions of docking programs have a major limitation, as they do not always provide accurate predictions of ligand affinity to substrates [82, 83]. Furthermore, molecular docking has the disadvantage that water molecules do not enter binding sites, so the ligand’s interaction with the target can be inaccurate. Docking programs may be made more effective by combining them with other techniques. It is possible to estimate ligand-binding affinities with just a moderate amount of computational work using a variety of well-established approaches, such as standard MD or binding free energy estimates like MM-GBSA and MM-PBSA [84].

It is also acknowledged that commercially targeted or focused libraries have evolved well beyond COVID-19, a topic that is beyond the scope of this paper. To aid in the preliminary VS stages enabled by these libraries, commercial and other suppliers of focused and targeted libraries are required. When using targeted libraries, readers should be cautious about compound selection, which is key to success in drug discovery efforts.

Little research has been done to determine the exact nature of the connections between COVID-19 and cancer. Studies are being conducted to determine whether or not cancer patients would have more severe COVID-19 symptoms and whether or not the likelihood of developing COVID-19 will rise as a result of cancer therapies. There is some indication that specific cancer therapies may be beneficial against the COVID-19 virus. Despite this, there is mounting evidence that pharmacological repurposing and VS might play significant roles in the battle against COVID-19. VS and the repurposing of existing cancer drugs might be helpful in searching for COVID-19 therapies. The SARS-CoV-2 virus has several distinctive characteristics that set it apart from other viruses and make it an intriguing target for medication repurposing and VS. The first is that the structure of the viral S-protein is quite similar to the structure of other well-known human viruses, such as the virus that causes the common cold. Based on this, antiviral medications now in use against other human viruses may also be effective against SARS-CoV-2. When an existing medicine is repurposed, it is used for a different purpose than it was initially intended. This strategy may be pursued for both approved medications and those tested in humans but found to be ineffective for other uses. The computer method known as VS may be used to evaluate many compounds to determine which ones have the most significant potential to form bonds.