Potential COVID-19 papain-like protease PLpro inhibitors: repurposing FDA-approved drugs

Evolution of drug resistance against antiviral agents that target cellular factors

Antiviral drugs have classically been developed by directly disrupting the functions of viral proteins. However, this strategy has been largely unsuccessful due to the rapid generation of viral escape mutants. It has been well established that as compared to the virus-centric approach, the strategy of developing antiviral drugs by targeting host-dependency factors (HDFs) minimizes drug resistance. However, recent reports have indicated that drug resistance against some of the host-targeting antiviral agents can in fact occur under some circumstances. Long-term selection pressure of a host-targeting antiviral agent may induce the virus to use an alternate cellular factor or alters its affinity towards the target that confers resistance. Alternatively, virus may synchronize its life cycle with the patterns of drug therapy. In addition, virus may subvert host's immune system to perpetuate under the limiting conditions of the targeted cellular factor. This review describes novel potential mechanisms that may account for the acquiring resistance against agents that target HDFs.

Integrated virtual screening and molecular dynamics simulation approaches revealed potential natural inhibitors for DNMT1 as therapeutic solution for triple negative breast cancer

Triple negative breast cancers (TNBC) are clinically heterogeneous but mostly aggressive malignancies devoid of expression of the estrogen, progesterone, and HER2 (ERBB2 or NEU) receptors. It accounts for 15-20% of all cases. Altered epigenetic regulation including DNA hypermethylation by DNA methyltransferase 1 (DNMT1) has been implicated as one of the causes of TNBC tumorigenesis. The antitumor effect of DNMT1 has also been explored in TNBC that currently lacks targeted therapies. However, the actual treatment for TNBC is yet to be discovered. This study is attributed to the identification of novel drug targets against TNBC. A comprehensive docking and simulation analysis was performed to optimize promising new compounds by estimating their binding affinity to the target protein. Molecular dynamics simulation of 500 ns well complemented the binding affinity of the compound and revealed strong stability of predicted compounds at the docked site. Calculation of binding free energies using MMPBSA and MMGBSA validated the strong binding affinity between compound and binding pockets of DNMT1. In a nutshell, our study uncovered that Beta-Mangostin, Gancaonin Z, 5-hydroxysophoranone, Sophoraflavanone L, and Dorsmanin H showed maximum binding affinity with the active sites of DNMT1. Furthermore, all of these compounds depict maximum drug-like properties. Therefore, the proposed compounds can be a potential candidate for patients with TNBC, but, experimental validation is needed to ensure their safety.Communicated by Ramaswamy H. Sarma.

DrugRep-HeSiaGraph: when heterogenous siamese neural network meets knowledge graphs for drug repurposing

BACKGROUND

Drug repurposing is an approach that holds promise for identifying new therapeutic uses for existing drugs. Recently, knowledge graphs have emerged as significant tools for addressing the challenges of drug repurposing. However, there are still major issues with constructing and embedding knowledge graphs.

RESULTS

This study proposes a two-step method called DrugRep-HeSiaGraph to address these challenges. The method integrates the drug-disease knowledge graph with the application of a heterogeneous siamese neural network. In the first step, a drug-disease knowledge graph named DDKG-V1 is constructed by defining new relationship types, and then numerical vector representations for the nodes are created using the distributional learning method. In the second step, a heterogeneous siamese neural network called HeSiaNet is applied to enrich the embedding of drugs and diseases by bringing them closer in a new unified latent space. Then, it predicts potential drug candidates for diseases. DrugRep-HeSiaGraph achieves impressive performance metrics, including an AUC-ROC of 91.16%, an AUC-PR of 90.32%, an accuracy of 84.63%, a BS of 0.119, and an MCC of 69.31%.

CONCLUSION

We demonstrate the effectiveness of the proposed method in identifying potential drugs for COVID-19 as a case study. In addition, this study shows the role of dipeptidyl peptidase 4 (DPP-4) as a potential receptor for SARS-CoV-2 and the effectiveness of DPP-4 inhibitors in facing COVID-19. This highlights the practical application of the model in addressing real-world challenges in the field of drug repurposing. The code and data for DrugRep-HeSiaGraph are publicly available at https://github.com/CBRC-lab/DrugRep-HeSiaGraph .

Structure-based virtual screening of natural compounds as inhibitors of HCV using molecular docking and molecular dynamics simulation studies

The hepatitis C virus (HCV), which causes hepatitis C, is a viral infection that damages the liver and causes inflammation in the liver. New potentially effective antiviral drugs are required for its treatment owing to various issues associated with the existing medications, including moderate to severe adverse effects, higher costs, and the emergence of drug-resistant strains. The objective of the current study was to utilize computational techniques to assess the anti-HCV efficacy of certain phytochemicals against tetraspanin (CD81) and claudin 1 (CLDN1) entry proteins. A 200-nanosecond molecular dynamics (MD) simulation was employed to examine the stability of the lead-protein complexes. Free binding energy and molecular docking calculations were conducted utilizing MM/GBSA method, and the selectivity of hit compounds for CD81 and CLDN1 was determined. Five significant CD81 and CLDN1 inhibitors were identified: Petasiphenone, Silibinin, Tanshinone IIA, Taxifolin, and Topaquinone. The MM/GBSA analysis of the compounds revealed high free binding energies. All the identified compounds were stable within the CD81 and CLDN1 binding pockets. This study indicated the promising inhibitory potential of the identified compounds against CD81 and CLDN1 receptors and might develop into potential viral entry inhibitors. However, to validate the chemotherapeutic capabilities of the discovered leads extensive preclinical research is required.Communicated by Ramaswamy H. Sarma.

Integrated molecular modeling and dynamics approaches revealed potential natural inhibitors of NF-κB transcription factor as breast cancer therapeutics

Breast cancer is a silent killer malady among women and a serious economic burden in health care management. A case of breast cancer is diagnosed among women every 19 s, and every 74 s, a woman dies of breast cancer somewhere in the world. Despite the pop-up of progressive research, advanced treatment approaches, and preventive measures, breast cancer remains amplifying ailment. The nuclear factor kappa B (NF-κB) is a key transcription factor that links inflammation with cancer and is demonstrated as being involved in the tumorigenesis of breast cancer. The NF-κB transcription factor family in mammals consists of five proteins; c-Rel, RelA(p65), RelB, NF-κB1(p50), and NF-κB2(p52). The antitumor effect of NF-κB has also been explored in breast cancer, however, the actual treatment for breast cancer is yet to be discovered. This study is attributed to the identification of novel drug targets against breast cancer by targeting c-Rel, RelA(p65), RelB, NF-κB1(p50), and NF-κB2(p52) proteins. To identify the putative active compounds, a structure-based 3D pharmacophore model to the protein active site cavity was generated followed by virtual screening, molecular docking, and molecular dynamics (MD) simulation. Initially, a library of 45000 compounds were docked against the target protein and five compounds namely Z56811101, Z653426226, Z1097341967, Z92743432, and Z464101066 were selected for further analysis. The relative binding affinity of Z56811101, Z653426226, Z1097341967, Z92743432, and Z464101066 with NF-κB1 (p50), NF-κB2 (p52), RelA (p65), RelB, and c-Rel proteins were -6.8, -8, -7.0, -6.9, and -7.2 kcal/mol, respectively which remained stable throughout the simulations of 200 ns. Furthermore, all of these compounds depict maximum drug-like properties. Therefore, the proposed compounds can be a potential candidate for patients with breast cancer, but, experimental validation is needed to ensure their safety.Communicated by Ramaswamy H. Sarma.

COVID-19 signalome: Potential therapeutic interventions

The COVID-19 pandemic has triggered intensive research and development of drugs and vaccines against SARS-CoV-2 during the last two years. The major success was especially observed with development of vaccines based on viral vectors, nucleic acids and whole viral particles, which have received emergent authorization leading to global mass vaccinations. Although the vaccine programs have made a big impact on COVID-19 spread and severity, emerging novel variants have raised serious concerns about vaccine efficacy. Due to the urgent demand, drug development had originally to rely on repurposing of antiviral drugs developed against other infectious diseases. For both drug and vaccine development the focus has been mainly on SARS-CoV-2 surface proteins and host cell receptors involved in viral attachment and entry. In this review, we expand the spectrum of SARS-CoV-2 targets by investigating the COVID-19 signalome. In addition to the SARS-CoV-2 Spike protein, the envelope, membrane, and nucleoprotein targets have been subjected to research. Moreover, viral proteases have presented the possibility to develop different strategies for the inhibition of SARS-CoV-2 replication and spread. Several signaling pathways involving the renin-angiotensin system, angiotensin-converting enzymes, immune pathways, hypoxia, and calcium signaling have provided attractive alternative targets for more efficient drug development.

In Silico Identification of Inhibitory Compounds for SARS-Cov-2 Papain-Like Protease

Virtual screening with high-performance computers is a powerful and cost-effective technique in drug discovery. A chemical database is searched to find candidate compounds firmly bound to a target protein, judging from the binding poses and/or binding scores. The severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infectious disease has spread worldwide for the last three years, causing severe slumps in economic and social activities. SARS-Cov-2 has two viral proteases: 3-chymotrypsin-like (3CL) and papain-like (PL) protease. While approved drugs have already been released for the 3CL protease, no approved agent is available for PL protease. In this work, we carried out in silico screening for the PL protease inhibitors, combining docking simulation and molecular mechanics calculation. Docking simulations were applied to 8,820 molecules in a chemical database of approved and investigational compounds. Based on the binding poses generated by the docking simulations, molecular mechanics calculations were performed to optimize the binding structures and to obtain the binding scores. Based on the binding scores, 57 compounds were selected for in vitro assay of the inhibitory activity. Five inhibitory compounds were identified from the in vitro measurement. The predicted binding structures of the identified five compounds were examined, and the significant interaction between the individual compound and the protease catalytic site was clarified. This work demonstrates that computational virtual screening by combining docking simulation with molecular mechanics calculation is effective for searching candidate compounds in drug discovery.

In silico screening of phytopolyphenolics for the identification of bioactive compounds as novel protease inhibitors effective against SARS-CoV-2

Due to the unavailability specific drugs or vaccines (FDA approved) that can cure COVID-19, the development of potent antiviral drug candidates/therapeutic molecules against COVID-19 is urgently required. This study was aimed at in silico screening and study of polyphenolic phytochemical compounds in a rational way by virtual screening, molecular docking and molecular dynamics studies against SARS-CoV-2 main protease (Mpro) and papain-like protease (PLpro) enzymes. The objective of the study was to identify plant-derived polyphenolic compounds and/or flavonoid molecules as possible antiviral agents with protease inhibitory potential against SARS-CoV-2. In this study, we report plant-derived polyphenolic compounds (including flavonoids) as novel protease inhibitors against SARS-CoV-2. From virtual docking and molecular docking study, 31 polyphenolic compounds were identified as active antiviral molecules possessing well-defined binding affinity with acceptable ADMET, toxicity and lead-like or drug-like properties. Six polyphenolic compounds, namely, enterodiol, taxifolin, eriodictyol, leucopelargonidin, morin and myricetin were found to exhibit remarkable binding affinities against the proteases with taxifolin and morin exhibiting the highest binding affinity toward Mpro and PLpro respectively. Molecular dynamics simulation studies of these compounds in complex with the proteases showed that the binding of the compounds is characterized by structural perturbations of the proteases suggesting their antiviral activities. These compounds can therefore be investigated further by in vivo and in vitro techniques to assess their potential efficacy against SARS-CoV-2 and thus serve as the starting point for the development of potent antiviral agents against the deadly COVID-19.

Identification of molecular mechanisms underlying the therapeutic effects of Celosia Cristata on immunoglobulin nephropathy

Immunoglobulin A (IgA) nephropathy also known as Berger's disease, is a silent monster and perhaps the most prevalent glomerulonephritis that often accounts for end-stage kidney failure, thereby signifying a growing public health problem worldwide. The limited amount of available data and a broad spectrum of dysregulated physiological processes of IgAN make it a challenging task and a disproportionate economic load on the community health sector. Celosia cristata is an Amaranthaceous plant with attractive colorful inflorescences that are used in various regions of earth for the treatment of numerous ailments. A list of studies evidences the therapeutic efficacy of C. cristata against complicated disorders, but the precise molecular mechanism is yet to be discovered. This study is attributed to the identification of bioactive compounds, pathways, and target genes for the better treatment of IgAN. In the current analysis, compound-target genes-pathway networks were explored which uncovered that isorhamnetin, stigmasterol, luteolin, amaranthin, and β-sitosterol may serve as a magic bullet against IgAN by influencing the targets genes involved in the disease pathogenesis. Later, the expression of hub genes was then further analyzed using a microarray dataset (GSE93798). Through expression analysis, it is worth noting that FOS, JUN, and EGFR were considerably upregulated, and at the same moment, AKT1 was considerably downregulated in IgAN patients. Lastly, docking analysis further strengthened the current findings by validating the effective activity of the active ingredients against putative target genes. In summary, we propose that five key compounds including, isorhamnetin, stigmasterol, luteolin, amaranthin, and β-sitosterol, aid in the regulation of JUN, FOS, AKT1, and EGFR, which may serve as a promising and enthralling therapeutic option for IgAN. The overall integration of network pharmacology with molecular docking unveiled the multi-target pharmacological mechanisms of C. cristata against IgAN. This study provides convincing evidence that C. cristata might partially alleviate the IgAN and ultimately lays a foundation for further experimental research on the anti-IgAN activity of C. cristata.

A Review of In Silico Research, SARS-CoV-2, and Neurodegeneration: Focus on Papain-Like Protease

Since the appearance of SARS-CoV-2 and the COVID-19 pandemic, the search for new approaches to treat this disease took place in the scientific community. The in silico approach has gained importance at this moment, once the methodologies used in this kind of study allow for the identification of specific protein-ligand interactions, which may serve as a filter step for molecules that can act as specific inhibitors. In addition, it is a low-cost and high-speed technology. Molecular docking has been widely used to find potential viral protein inhibitors for structural and non-structural proteins of the SARS-CoV-2, aiming to block the infection and the virus multiplication. The papain-like protease (PLpro) participates in the proteolytic processing of SARS-CoV-2 and composes one of the main targets studied for pharmacological intervention by in silico methodologies. Based on that, we performed a systematic review about PLpro inhibitors from the perspective of in silico research, including possible therapeutic molecules in relation to this viral protein. The neurological problems triggered by COVID-19 were also briefly discussed, especially relative to the similarities of neuroinflammation present in Alzheimer's disease. In this context, we focused on two molecules, curcumin and glycyrrhizinic acid, given their PLpro inhibitory actions and neuroprotective properties and potential therapeutic effects on COVID-19.

Novel Drug Design for Treatment of COVID-19: A Systematic Review of Preclinical Studies

Background

Since the beginning of the novel coronavirus (SARS-CoV-2) disease outbreak, there has been an increasing interest in discovering potential therapeutic agents for this disease. In this regard, we conducted a systematic review through an overview of drug development (in silico, in vitro, and in vivo) for treating COVID-19.

Methods

A systematic search was carried out in major databases including PubMed, Web of Science, Scopus, EMBASE, and Google Scholar from December 2019 to March 2021. A combination of the following terms was used: coronavirus, COVID-19, SARS-CoV-2, drug design, drug development, In silico, In vitro, and In vivo. A narrative synthesis was performed as a qualitative method for the data synthesis of each outcome measure.

Results

A total of 2168 articles were identified through searching databases. Finally, 315 studies (266 in silico, 34 in vitro, and 15 in vivo) were included. In studies with in silico approach, 98 article study repurposed drug and 91 studies evaluated herbal medicine on COVID-19. Among 260 drugs repurposed by the computational method, the best results were observed with saquinavir (n = 9), ritonavir (n = 8), and lopinavir (n = 6). Main protease (n = 154) following spike glycoprotein (n = 62) and other nonstructural protein of virus (n = 45) was among the most studied targets. Doxycycline, chlorpromazine, azithromycin, heparin, bepridil, and glycyrrhizic acid showed both in silico and in vitro inhibitory effects against SARS-CoV-2.

Conclusion

The preclinical studies of novel drug design for COVID-19 focused on main protease and spike glycoprotein as targets for antiviral development. From evaluated structures, saquinavir, ritonavir, eucalyptus, Tinospora cordifolia, aloe, green tea, curcumin, pyrazole, and triazole derivatives in in silico studies and doxycycline, chlorpromazine, and heparin from in vitro and human monoclonal antibodies from in vivo studies showed promised results regarding efficacy. It seems that due to the nature of COVID-19 disease, finding some drugs with multitarget antiviral actions and anti-inflammatory potential is valuable and some herbal medicines have this potential.

Discovery of Rift Valley fever virus natural pan-inhibitors by targeting its multiple key proteins through computational approaches

The Rift Valley fever virus (RVFV) is a zoonotic arbovirus and pathogenic to both humans and animals. Currently, no proven effective RVFV drugs or licensed vaccine are available for human or animal use. Hence, there is an urgent need to develop effective treatment options to control this viral infection. RVFV glycoprotein N (GN), glycoprotein C (GC), and nucleocapsid (N) proteins are attractive antiviral drug targets due to their critical roles in RVFV replication. In present study, an integrated docking-based virtual screening of more than 6000 phytochemicals with known antiviral activities against these conserved RVFV proteins was conducted. The top five hit compounds, calyxin C, calyxin D, calyxin J, gericudranins A, and blepharocalyxin C displayed optimal binding against all three target proteins. Moreover, multiple parameters from the molecular dynamics (MD) simulations and MM/GBSA analysis confirmed the stability of protein-ligand complexes and revealed that these compounds may act as potential pan-inhibitors of RVFV replication. Our computational analyses may contribute toward the development of promising effective drugs against RVFV infection.

Structural Elucidation of Rift Valley Fever Virus L Protein towards the Discovery of Its Potential Inhibitors

Rift valley fever virus (RVFV) is the causative agent of a viral zoonosis that causes a significant clinical burden in domestic and wild ruminants. Major outbreaks of the virus occur in livestock, and contaminated animal products or arthropod vectors can transmit the virus to humans. The viral RNA-dependent RNA polymerase (RdRp; L protein) of the RVFV is responsible for viral replication and is thus an appealing drug target because no effective and specific vaccine against this virus is available. The current study reported the structural elucidation of the RVFV-L protein by in-depth homology modeling since no crystal structure is available yet. The inhibitory binding modes of known potent L protein inhibitors were analyzed. Based on the results, further molecular docking-based virtual screening of Selleckchem Nucleoside Analogue Library (156 compounds) was performed to find potential new inhibitors against the RVFV L protein. ADME (Absorption, Distribution, Metabolism, and Excretion) and toxicity analysis of these compounds was also performed. Besides, the binding mechanism and stability of identified compounds were confirmed by a 50 ns molecular dynamic (MD) simulation followed by MM/PBSA binding free energy calculations. Homology modeling determined a stable multi-domain structure of L protein. An analysis of known L protein inhibitors, including Monensin, Mycophenolic acid, and Ribavirin, provide insights into the binding mechanism and reveals key residues of the L protein binding pocket. The screening results revealed that the top three compounds, A-317491, Khasianine, and VER155008, exhibited a high affinity at the L protein binding pocket. ADME analysis revealed good pharmacodynamics and pharmacokinetic profiles of these compounds. Furthermore, MD simulation and binding free energy analysis endorsed the binding stability of potential compounds with L protein. In a nutshell, the present study determined potential compounds that may aid in the rational design of novel inhibitors of the RVFV L protein as anti-RVFV drugs.

The effect of various compounds on the COVID mechanisms, from chemical to molecular aspects

The novel coronavirus that caused COVID-19 pandemic is SARS-CoV-2. Although various vaccines are currently being used to prevent the disease's severe consequences, there is still a need for medications for those who become infected. The SARS-CoV-2 has a variety of proteins that have been studied extensively since the virus's advent. In this review article, we looked at chemical to molecular aspects of the various structures studied that have pharmaceutical activity and attempted to find a link between drug activity and compound structure. For example, designing of the compounds which bind to the allosteric site and modify hydrogen bonds or the salt bridges can disrupt SARS-CoV2 RBD–ACE2 complex. It seems that quaternary ammonium moiety and quinolin-1-ium structure could act as a negative allosteric modulator to reduce the tendency between spike-ACE2. Pharmaceutical structures with amino heads and hydrophobic tails can block envelope protein to prevent making mature SARS-CoV-2. Also, structures based on naphthalene pharmacophores or isosteres can form a strong bond with the PLpro and form a π-π and the Mpro's active site can be occupied by octapeptide compounds or linear compounds with a similar fitting ability to octapeptide compounds. And for protein RdRp, it is critical to consider pH and pKa so that pKa regulation of compounds to comply with patients is very effective, thus, the presence of tetrazole, phenylpyrazole groups, and analogs of pyrophosphate in the designed drugs increase the likelihood of the RdRp active site inhibition. Finally, it can be deduced that designing hybrid drug molecules along with considering the aforementioned characteristics would be a suitable approach for developing medicines in order to accurate targeting and complete inhibition this virus.

Repurposing of phytomedicine-derived bioactive compounds with promising anti-SARS-CoV-2 potential: Molecular docking, MD simulation and drug-likeness/ADMET studies

In view of the potential of traditional plant-based remedies (or phytomedicines) in the management of COVID-19, the present investigation was aimed at finding novel anti-SARS-CoV-2 molecules by in silico screening of bioactive phytochemicals (database) using computational methods and drug repurposing approach. A total of 160 compounds belonging to various phytochemical classes (flavonoids, limonoids, saponins, triterpenoids, steroids etc.) were selected (as initial hits) and screened against three specific therapeutic targets (Mpro/3CLpro, PLpro and RdRp) of SARS-CoV-2 by docking, molecular dynamics simulation and drug-likeness/ADMET studies. From our studies, six phytochemicals were identified as notable ant-SARS-CoV-2 agents (best hit molecules) with promising inhibitory effects effective against protease (Mpro and PLpro) and polymerase (RdRp) enzymes. These compounds are namely, ginsenoside Rg2, saikosaponin A, somniferine, betulinic acid, soyasapogenol C and azadirachtin A. On the basis of binding modes and dynamics studies of protein-ligand intercations, ginsenoside Rg2, saikosaponin A, somniferine were found to be the most potent (in silico) inhibitors potentially active against Mpro, PLpro and RdRp, respectively. The present investigation can be directed towards further experimental studies in order to confirm the anti-SARS-CoV-2 efficacy along with toxicities of identified phytomolecules.

Recent advances in developing small-molecule inhibitors against SARS-CoV-2

The COVID-19 pandemic caused by the novel SARS-CoV-2 virus has caused havoc across the entire world. Even though several COVID-19 vaccines are currently in distribution worldwide, with others in the pipeline, treatment modalities lag behind. Accordingly, researchers have been working hard to understand the nature of the virus, its mutant strains, and the pathogenesis of the disease in order to uncover possible drug targets and effective therapeutic agents. As the research continues, we now know the genome structure, epidemiological and clinical features, and pathogenic mechanism of SARS-CoV-2. Here, we summarized the potential therapeutic targets involved in the life cycle of the virus. On the basis of these targets, small-molecule prophylactic and therapeutic agents have been or are being developed for prevention and treatment of SARS-CoV-2 infection.

Potential Inhibitors Targeting Papain-Like Protease of SARS-CoV-2: Two Birds With One Stone

Severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2), the pathogen of the Coronavirus disease-19 (COVID-19), is still devastating the world causing significant chaos to the international community and posing a significant threat to global health. Since the first outbreak in late 2019, several lines of intervention have been developed to prevent the spread of this virus. Nowadays, some vaccines have been approved and extensively administered. However, the fact that SARS-CoV-2 rapidly mutates makes the efficacy and safety of this approach constantly under debate. Therefore, antivirals are still needed to combat the infection of SARS-CoV-2. Papain-like protease (PLpro) of SARS-CoV-2 supports viral reproduction and suppresses the innate immune response of the host, which makes PLpro an attractive pharmaceutical target. Inhibition of PLpro could not only prevent viral replication but also restore the antiviral immunity of the host, resulting in the speedy recovery of the patient. In this review, we describe structural and functional features on PLpro of SARS-CoV-2 and the latest development in searching for PLpro inhibitors. Currently available inhibitors targeting PLpro as well as their structural basis are also summarized.

DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design

Since the outbreak of SARS-CoV-2, numerous compounds against COVID-19 have been derived by computer-aided drug design (CADD) studies. They are valuable resources for the development of COVID-19 therapeutics. In this work, we reviewed these studies and analyzed 779 compounds against 16 target proteins from 181 CADD publications. We performed unified docking simulations and neck-to-neck comparison with the solved co-crystal structures. We computed their chemical features and classified these compounds, aiming to provide insights for subsequent drug design. Through detailed analyses, we recommended a batch of compounds that are worth further study. Moreover, we organized all the abundant data and constructed a freely available database, DrugDevCovid19, to facilitate the development of COVID-19 therapeutics.

Strategies for drug repurposing against coronavirus targets

Repurposing regulatory agency approved drugs and investigational compounds with known safety profiles can significantly fast track the drug development timeline over de novo drug discovery, with lower investment requirements and improved attrition rate. These advantages are vital in any epidemic or pandemic situation, where hospital beds are occupied by patients for whom there is no known treatment. Here we examine drug repurposing in the context of human coronaviruses, SARS-CoV, MERS-CoV, and, in particular, SARS-CoV-2, the virus currently causing a continued widespread pandemic with substantial impacts on public health and economy. The key druggable targets explored were those involved in viral entry, viral replication, and viral-induced ARDS, as well as viral proteases, with a focus on the strategy by which the drugs were repurposed.

Network analytics for drug repurposing in COVID-19

To better understand the potential of drug repurposing in COVID-19, we analyzed control strategies over essential host factors for SARS-CoV-2 infection. We constructed comprehensive directed protein–protein interaction (PPI) networks integrating the top-ranked host factors, the drug target proteins and directed PPI data. We analyzed the networks to identify drug targets and combinations thereof that offer efficient control over the host factors. We validated our findings against clinical studies data and bioinformatics studies. Our method offers a new insight into the molecular details of the disease and into potentially new therapy targets for it. Our approach for drug repurposing is significant beyond COVID-19 and may be applied also to other diseases.

Advances in the computational landscape for repurposed drugs against COVID-19

The COVID-19 pandemic has caused millions of deaths and massive societal distress worldwide. Therapeutic solutions are urgently needed, but de novo drug development remains a lengthy process. One promising alternative is computational drug repurposing, which enables the prioritization of existing compounds through fast in silico analyses. Recent efforts based on molecular docking, machine learning, and network analysis have produced actionable predictions. Some predicted drugs, targeting viral proteins and pathological host pathways are undergoing clinical trials. Here, we review this work, highlight drugs with high predicted efficacy and classify their mechanisms of action. We discuss the strengths and limitations of the published methodologies and outline possible future directions. Finally, we curate a list of COVID-19 data portals and other repositories that could be used to accelerate future research.

Drug repurposing against SARS-CoV-1, SARS-CoV-2 and MERS-CoV

Since the beginning of the COVID-19 pandemic, large in silico screening studies and numerous in vitro studies have assessed the antiviral activity of various drugs on SARS-CoV-2. In the context of health emergency, drug repurposing represents the most relevant strategy because of the reduced time for approval by international medicines agencies, the low cost of development and the well-known toxicity profile of such drugs. Herein, we aim to review drugs with in vitro antiviral activity against SARS-CoV-2, combined with molecular docking data and results from preliminary clinical studies. Finally, when considering all these previous findings, as well as the possibility of oral administration, 11 molecules consisting of nelfinavir, favipiravir, azithromycin, clofoctol, clofazimine, ivermectin, nitazoxanide, amodiaquine, heparin, chloroquine and hydroxychloroquine, show an interesting antiviral activity that could be exploited as possible drug candidates for COVID-19 treatment.

Investigating Fungi-Derived Bioactive Molecules as Inhibitor of the SARS Coronavirus Papain Like Protease: Computational Based Study

Due to the rapid growth of the COVID-19 pandemic and its outcomes, developing a remedy to fight the predicament is critical. So far, it has infected more than 214,468,601 million people and caused the death of 4,470,969 million people according to the August 27, 2021, World Health Organization's (WHO) report. Several studies have been published on both computational and wet-lab approaches to develop antivirals for COVID-19, although there has been no success yet. However, the wet-lab approach is laborious, expensive, and time-consuming, and computational techniques have screened the activity of bioactive compounds from different sources with less effort and cost. For this investigation, we screened the binding affinity of fungi-derived bioactive molecules toward the SARS coronavirus papain-like protease (PLpro) by using computational approaches. Studies showed that protease inhibitors can be very effective in controlling virus-induced infections. Additionally, fungi represent a vast source of bioactive molecules, which could be potentially used for antiviral therapy. Fifty fungi-derived bioactive compounds were investigated concerning SARS-CoV-2 PLpro by using Auto Dock 4.2.1, Gromacs 2018. 2, ADMET, Swiss-ADME, FAF-Drugs 4.023, pKCSM, and UCLA-DOE server. From the list of the screened bioactive compounds, Dihydroaltersolanol C, Anthraquinone, Nigbeauvin A, and Catechin were selected with the Auto-Dock results of -8.68, -7.52, -10.46, and -10.58 Kcal/mol, respectively, based on their binding affinity compared to the reference drug. We presented the drug likeliness, toxicity, carcinogenicity, and mutagenicity of all compounds using ADMET analysis. They interacted with the amino acid residues, Gly163, Trp106, Ser111, Asp164, and Cys270, through hydrogen bonds. The root-mean-square deviation (RMSD), root-mean-square fluctuations (RMSF), solvent-accessible surface area (SASA), and radius of gyration (Rg) values revealed a stable interaction. From the overall analyses, we can conclude that Dihydroaltersolanol C, Anthraquinone, Nigbeauvin A, and Catechin are classified as promising candidates for PLpro, thus potentially useful in developing a medicine for COVID-19.

Using informative features in machine learning based method for COVID-19 drug repurposing

Coronavirus disease 2019 (COVID-19) is caused by a novel virus named Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). This virus induced a large number of deaths and millions of confirmed cases worldwide, creating a serious danger to public health. However, there are no specific therapies or drugs available for COVID-19 treatment. While new drug discovery is a long process, repurposing available drugs for COVID-19 can help recognize treatments with known clinical profiles. Computational drug repurposing methods can reduce the cost, time, and risk of drug toxicity. In this work, we build a graph as a COVID-19 related biological network. This network is related to virus targets or their associated biological processes. We select essential proteins in the constructed biological network that lead to a major disruption in the network. Our method from these essential proteins chooses 93 proteins related to COVID-19 pathology. Then, we propose multiple informative features based on drug-target and protein-protein interaction information. Through these informative features, we find five appropriate clusters of drugs that contain some candidates as potential COVID-19 treatments. To evaluate our results, we provide statistical and clinical evidence for our candidate drugs. From our proposed candidate drugs, 80% of them were studied in other studies and clinical trials.

Identification of Potential Inhibitors against Epstein-Barr Virus Nuclear Antigen 1 (EBNA1): An Insight from Docking and Molecular Dynamic Simulations

Epstein-Barr virus (EBV), a known tumorigenic virus, is associated with various neuropathies, including multiple sclerosis (MS). However, there is no anti-EBV FDA-approved drug available in the market. Our study targeted EBV protein EBV nuclear antigen 1 (EBNA1), crucial in virus replication and expressed in all the stages of viral latencies. This dimeric protein binds to an 18 bp palindromic DNA sequence and initiates the process of viral replication. We chose phytochemicals and FDA-approved MS drugs based on literature survey followed by their evaluation efficacies as anti-EBNA1 molecules. Molecular docking revealed FDA drugs ozanimod, siponimod, teriflunomide, and phytochemicals; emodin; protoapigenone; and EGCG bound to EBNA1 with high affinities. ADMET and Lipinski's rule analysis of the phytochemicals predicted favorable druggability. We supported our assessments of pocket druggability with molecular dynamics simulations and binding affinity predictions by the molecular mechanics generalized Born surface area (MM/GBSA) method. Our results establish a stable binding for siponimod and ozanimod with EBNA1 mainly via van der Waals interactions. We identified hot spot residues like I481', K477', L582', and K586' in the binding of ligands. In particular, K477' at the amino terminal of EBNA1 is known to establish interaction with two bases at the major groove of the DNA. Siponimod bound to EBNA1 engaging K477', thus plausibly making it unavailable for DNA interaction. Computational alanine scanning further supported the significant roles of K477', I481', and K586' in the binding of ligands with EBNA1. Conclusively, the compounds showed promising results to be used against EBNA1.

Science's Response to CoVID-19

CoVID-19 is a multi-symptomatic disease which has made a global impact due to its ability to spread rapidly, and its relatively high mortality rate. Beyond the heroic efforts to develop vaccines, which we do not discuss herein, the response of scientists and clinicians to this complex problem has reflected the need to detect CoVID-19 rapidly, to diagnose patients likely to show adverse symptoms, and to treat severe and critical CoVID-19. Here we aim to encapsulate these varied and sometimes conflicting approaches and the resulting data in terms of chemistry and biology. In the process we highlight emerging concepts, and potential future applications that may arise out of this immense effort.

Predicted antiviral drugs Darunavir, Amprenavir, Rimantadine and Saquinavir can potentially bind to neutralize SARS-CoV-2 conserved proteins

BACKGROUND

Novel Coronavirus disease 2019 or COVID-19 has become a threat to human society due to fast spreading and increasing mortality. It uses vertebrate hosts and presently deploys humans. Life cycle and pathogenicity of SARS-CoV-2 have already been deciphered and possible drug target trials are on the way.

RESULTS

The present study was aimed to analyze Non-Structural Proteins that include conserved enzymes of SARS-CoV-2 like papain-like protease, main protease, Replicase, RNA-dependent RNA polymerase, methyltransferase, helicase, exoribonuclease and endoribonucleaseas targets to all known drugs. A bioinformatic based web server Drug ReposeER predicted several drug binding motifs in these analyzed proteins. Results revealed that anti-viral drugs Darunavir,Amprenavir, Rimantadine and Saquinavir were the most potent to have 3D-drug binding motifs that were closely associated with the active sites of the SARS-CoV-2 enzymes .

CONCLUSIONS

 Repurposing of the antiviral drugs Darunavir, Amprenavir, Rimantadine and Saquinavir to treat COVID-19 patients could be useful that can potentially prevent human mortality.

The impact of curcumin derived polyphenols on the structure and flexibility COVID-19 main protease binding pocket: a molecular dynamics simulation study

The newly occurred SARS-CoV-2 caused a leading pandemic of coronavirus disease (COVID-19). Up to now it has infected more than one hundred sixty million and killed more than three million people according to 14 May 2021 World Health Organization report. So far, different types of studies have been conducted to develop an anti-viral drug for COVID-19 with no success yet. As part of this, silico were studied to discover and introduce COVID-19 antiviral drugs and results showed that protease inhibitors could be very effective in controlling. This study aims to investigate the binding affinity of three curcumin derived polyphenols against COVID-19 the main protease (Mpro), binding pocket, and identification of important residues for interaction. In this study, molecular modeling, auto-dock coupled with molecular dynamics simulations were performed to analyze the conformational, and stability of COVID-19 binding pocket with diferuloylmethane, demethoxycurcumin, and bisdemethoxycurcumin. All three compounds have shown binding affinity −39, −89 and −169.7, respectively. Demethoxycurcumin and bisdemethoxycurcumin showed an optimum binding affinity with target molecule and these could be one of potential ligands for COVID-19 therapy. And also, COVID-19 main protease binding pocket binds with the interface region by one hydrogen bond. Moreover, the MD simulation parameters indicated that demethoxycurcumin and bisdemethoxycurcumin were stable during the simulation run. These findings can be used as a baseline to develop therapeutics with curcumin derived polyphenols against COVID-19.

Current understanding on molecular drug targets and emerging treatment strategy for novel coronavirus-19

SARS-CoV-2 is an enveloped positive-sense RNA virus, contain crown-like spikes on its surface, exceptional of large RNA genome, and a special replication machinery. Common symptoms of SARS-CoV-2 include cough, common cold, fever, sore throat, and a variety of severe acute respiratory disease (SARD) such as pneumonia. SARS-CoV-2 infects epithelial cells, T-cells, macrophages, and dendritic cells and also influences the production and implantation of pro-inflammatory cytokines and chemokines. Repurposing of various drugs during this emergency condition can reduce the rate of mortality as well as time and cost. Two druggable protein and enzyme targets have been selected in this review article due to their crucial role in the viral life cycle. The eukaryotic translation initiation factor (eIF4A), cyclophilin, nucleocapsid protein, spike protein, Angiotensin-converting enzyme 2 (ACE2), 3-chymotrypsin-like cysteine protease (3CLpro), and RNA-dependent RNA polymerase (RdRp) play significant role in early and late phase of SARS-CoV-2 replication and translation. This review paper is based on the rationale of inhibiting of various SARS-CoV-2 proteins and enzymes as novel therapeutic approaches for the management and treatment of patients with SARS-CoV-2 infection. We also discussed the structural and functional relationship of different proteins and enzymes to develop therapeutic approaches for novel coronavirus SARS-CoV-2.

Interactions between SARS coronavirus 2 papain-like protease and immune system: A potential drug target for the treatment of COVID-19

Coronaviruses (CoVs) are a large family of respiratory viruses which can cause mild to moderate upper respiratory tract infections. Recently, new coronavirus named as Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has been identified which is a major threat to public health. Innate immune responses play a vital role in a host's defence against viruses. Interestingly, CoVs have evolved elaborate strategies to evade the complex system of sensors and signalling molecules to suppress host immunity. SARS‐CoV‐2 papain‐like protease (PLpro), as an important coronavirus enzyme, regulates viral spread and innate immune responses. SCoV‐2 PLpro is multifunctional enzyme with deubiquitinating (DUB) and deISGylating activity. The PLpro can interact with key regulators in signalling pathways such as STING, NF‐κB, cytokine production, MAPK and TGF‐β and hijack those to block the immune responses. Therefore, the PLpro can be as an important target for the treatment of COVID‐19. Until now, several drugs or compounds have been identified that can inhibit PLpro activity. Here we discuss about the dysregulation effects of PLpro on immune system and drugs that have potential inhibitors for SCoV‐2 PLpro.

Virtual high throughput screening: Potential inhibitors for SARS-CoV-2 PLPRO and 3CLPRO proteases

The pandemic, COVID-19, has spread worldwide and affected millions of people. There is an urgent need, therefore, to find a proper treatment for the novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the causative agent. This paper focuses on identifying inhibitors that target SARS-CoV-2 proteases, PL^PRO and 3CL^PRO, which control the duplication and manages the life cycle of SARS-CoV-2. We have carried out detailed in silico Virtual high-throughput screening using Food and Drug Administration (FDA) approved drugs from the Zinc database, COVID-19 clinical trial compounds from Pubchem database, Natural compounds from Natural Product Activity and Species Source (NPASS) database and Maybridge database against PL^PRO and 3CL^PRO proteases. After thoroughly analyzing the screening results, we found five compounds, Bemcentinib, Pacritinib, Ergotamine, MFCD00832476, and MFCD02180753 inhibit PL^PRO and six compounds, Bemcentinib, Clofazimine, Abivertinib, Dasabuvir, MFCD00832476, Leuconicine F inhibit the 3CL^PRO. These compounds are stable within the protease proteins’ active sites at 20ns MD simulation. The stability is revealed by hydrogen bond formations, hydrophobic interactions, and salt bridge interactions. Our study results also reveal that the selected five compounds against PL^PRO and the six compounds against 3CL^PRO bind to their active sites with good binding free energy. These compounds that inhibit the activity of PL^PRO and 3CL^PRO may, therefore, be used for treating COVID-19 infection.

Targeting multiple conformations of SARS-CoV2 Papain-Like Protease for drug repositioning: An in-silico study

Papain-Like Protease (PLpro) is a key protein for SARS-CoV-2 viral replication which is the cause of the emerging COVID-19 pandemic. Targeting PLpro can suppress viral replication and provide treatment options for COVID-19. Due to the dynamic nature of its binding site loop, PLpro multiple conformations were generated through a long-range 1 micro-second molecular dynamics (MD) simulation. Clustering the MD trajectory enabled us to extract representative structures for the conformational space generated. Adding to the MD representative structures, X-ray structures were involved in an ensemble docking approach to screen the FDA approved drugs for a drug repositioning endeavor. Guided by our recent benchmarking study of SARS-CoV-2 PLpro, FRED docking software was selected for such a virtual screening task. The results highlighted potential consensus binders to many of the MD clusters as well as the newly introduced X-ray structure of PLpro complexed with a small molecule. For instance, three drugs Benserazide, Dobutamine and Masoprocol showed a superior consensus enrichment against the PLpro conformations. Further MD simulations for these drugs complexed with PLpro suggested the superior stability and binding of dobutamine and masoprocol inside the binding site compared to Benserazide. Generally, this approach can facilitate identifying drugs for repositioning via targeting multiple conformations of a crucial target for the rapidly emerging COVID-19 pandemic.

Knowing and combating the enemy: a brief review on SARS-CoV-2 and computational approaches applied to the discovery of drug candidates

Since the emergence of the new severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) at the end of December 2019 in China, and with the urge of the coronavirus disease 2019 (COVID-19) pandemic, there have been huge efforts of many research teams and governmental institutions worldwide to mitigate the current scenario. Reaching more than 1,377,000 deaths in the world and still with a growing number of infections, SARS-CoV-2 remains a critical issue for global health and economic systems, with an urgency for available therapeutic options. In this scenario, as drug repurposing and discovery remains a challenge, computer-aided drug design (CADD) approaches, including machine learning (ML) techniques, can be useful tools to the design and discovery of novel potential antiviral inhibitors against SARS-CoV-2. In this work, we describe and review the current knowledge on this virus and the pandemic, the latest strategies and computational approaches applied to search for treatment options, as well as the challenges to overcome COVID-19.

Novel coronavirus disease-2019 (COVID-19) in people with rheumatic disease: Epidemiology and outcomes

There is concern that people with rheumatic disease, often treated with immunosuppressive or immunomodulatory medication, may be at an increased risk of poor outcomes of novel coronavirus disease-2019 (COVID-19). However, hyperinflammation is a major cause of morbidity and mortality in COVID-19 and treatment with glucocorticoids has been shown to improve outcomes in patients with severe COVID-19. Therefore, uncertainty exists about continuing or withholding immune therapies with the risk of infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This review covers the current knowledge with respect to the risk of infection and outcomes and risk factors for poor outcomes in patients with rheumatic disease. We also discuss data from other immune-mediated diseases and its relevance to patients with rheumatic disease. In addition, we cover the limitations of the research efforts to date and how the current knowledge translates into practice guidance. Finally, we discuss our vision of the future research agenda.

Potent, Novel SARS-CoV-2 PLpro Inhibitors Block Viral Replication in Monkey and Human Cell Cultures

Antiviral agents blocking SARS-CoV-2 viral replication are desperately needed to complement vaccination to end the COVID-19 pandemic. Viral replication and assembly are entirely dependent on two viral cysteine proteases: 3C-like protease (3CLpro) and the papain-like protease (PLpro). PLpro also has deubiquitinase (DUB) activity, removing ubiquitin (Ub) and Ub-like modifications from host proteins, disrupting the host immune response. 3CLpro is inhibited by many known cysteine protease inhibitors, whereas PLpro is a relatively unusual cysteine protease, being resistant to blockade by such inhibitors. A high-throughput screen of biased and unbiased libraries gave a low hit rate, identifying only CPI-169 and the positive control, GRL0617, as inhibitors with good potency (IC50 < 10 lower case Greek μM). Analogues of both inhibitors were designed to develop structure-activity relationships; however, without a co-crystal structure of the CPI-169 series, we focused on GRL0617 as a starting point for structure-based drug design, obtaining several co-crystal structures to guide optimization. A series of novel 2-phenylthiophene-based non-covalent SARS-CoV-2 PLpro inhibitors were obtained, culminating in low nanomolar potency. The high potency and slow inhibitor off-rate were rationalized by newly identified ligand interactions with a 'BL2 groove' that is distal from the active site cysteine. Trapping of the conformationally flexible BL2 loop by these inhibitors blocks binding of viral and host protein substrates; however, until now it has not been demonstrated that this mechanism can induce potent and efficacious antiviral activity. In this study, we report that novel PLpro inhibitors have excellent antiviral efficacy and potency against infectious SARS-CoV-2 replication in cell cultures. Together, our data provide structural insights into the design of potent PLpro inhibitors and the first validation that non-covalent inhibitors of SARS-CoV-2 PLpro can block infection of human cells with low micromolar potency.

Computational Determination of Potential Multiprotein Targeting Natural Compounds for Rational Drug Design Against SARS-COV-2

SARS-CoV-2 caused the current COVID-19 pandemic and there is an urgent need to explore effective therapeutics that can inhibit enzymes that are imperative in virus reproduction. To this end, we computationally investigated the MPD3 phytochemical database along with the pool of reported natural antiviral compounds with potential to be used as anti-SARS-CoV-2. The docking results demonstrated glycyrrhizin followed by azadirachtanin, mycophenolic acid, kushenol-w and 6-azauridine, as potential candidates. Glycyrrhizin depicted very stable binding mode to the active pocket of the Mpro (binding energy, -8.7 kcal/mol), PLpro (binding energy, -7.9 kcal/mol), and Nucleocapsid (binding energy, -7.9 kcal/mol) enzymes. This compound showed binding with several key residues that are critical to natural substrate binding and functionality to all the receptors. To test docking prediction, the compound with each receptor was subjected to molecular dynamics simulation to characterize the molecule stability and decipher its possible mechanism of binding. Each complex concludes that the receptor dynamics are stable (Mpro (mean RMSD, 0.93 Å), PLpro (mean RMSD, 0.96 Å), and Nucleocapsid (mean RMSD, 3.48 Å)). Moreover, binding free energy analyses such as MMGB/PBSA and WaterSwap were run over selected trajectory snapshots to affirm intermolecular affinity in the complexes. Glycyrrhizin was rescored to form strong affinity complexes with the virus enzymes: Mpro (MMGBSA, -24.42 kcal/mol and MMPBSA, -10.80 kcal/mol), PLpro (MMGBSA, -48.69 kcal/mol and MMPBSA, -38.17 kcal/mol) and Nucleocapsid (MMGBSA, -30.05 kcal/mol and MMPBSA, -25.95 kcal/mol), were dominated mainly by vigorous van der Waals energy. Further affirmation was achieved by WaterSwap absolute binding free energy that concluded all the complexes in good equilibrium and stability (Mpro (mean, -22.44 kcal/mol), PLpro (mean, -25.46 kcal/mol), and Nucleocapsid (mean, -23.30 kcal/mol)). These promising findings substantially advance our understanding of how natural compounds could be shaped to counter SARS-CoV-2 infection.

Computational molecular docking and virtual screening revealed promising SARS-CoV-2 drugs

The pandemic of novel coronavirus disease 2019 (COVID-19) has rampaged the world, with more than 58.4 million confirmed cases and over 1.38 million deaths across the world by 23 November 2020. There is an urgent need to identify effective drugs and vaccines to fight against the virus. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) belongs to the family of coronaviruses consisting of four structural and 16 non-structural proteins (NSP). Three non-structural proteins, main protease (Mpro), papain-like protease (PLpro), and RNA-dependent RNA polymerase (RdRp), are believed to have a crucial role in replication of the virus. We applied computational ligand-receptor binding modeling and performed comprehensive virtual screening on FDA-approved drugs against these three SARS-CoV-2 proteins using AutoDock Vina, Glide, and rDock. Our computational studies identified six novel ligands as potential inhibitors against SARS-CoV-2, including antiemetics rolapitant and ondansetron for Mpro; labetalol and levomefolic acid for PLpro; and leucal and antifungal natamycin for RdRp. Molecular dynamics simulation confirmed the stability of the ligand-protein complexes. The results of our analysis with some other suggested drugs indicated that chloroquine and hydroxychloroquine had high binding energy (low inhibitory effect) with all three proteins-Mpro, PLpro, and RdRp. In summary, our computational molecular docking approach and virtual screening identified some promising candidate SARS-CoV-2 inhibitors that may be considered for further clinical studies.

Drug repurposing: new strategies for addressing COVID-19 outbreak

Introduction: COVID-19 outbreak has infected 34.20 million people with 1019 thousand deaths in more than 125 countries till 30 September 2020. Due to the unavailability of vaccine or targeted novel drug therapy against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), screening of existential medical treatments facilitates identification of promising drugs for the treatment and management of COVID-19.Areas covered: The review article highlights repurposing of antiviral, antimalarial, antineoplastic, antidiabetic, analgesic, and immunomodulatory drugs. Furthermore, clinical trials, in-vitro studies, benefits, adverse effects, toxicities, mechanisms of action, and regulatory status of drugs are covered in this article.Expert opinion: Lack of conclusive results from randomized clinical trials indicates absence of specific drugs for treatment of COVID-19. Unavailability of complete data regarding safety, efficacy, and adverse reactions of drugs restricts the recommendation of clinical advice on dose and duration of the drug therapy. Remdesivir and favipiravir show promising outcomes but more clinical evidence is required for use in large populations. Experimental and repurposed drug therapies targeting spike and envelope proteins, Mpro, 3CL_pro and PL_pro enzymes, and RdRp and TMPRSS2 genes show capability to produce effective anti-SARS-CoV-2 action. Development of vaccine against SARS-CoV-2 will offer long-term solution to terminate spread of this global pandemic.