Potential inhibitors for the novel coronavirus (SARS-CoV-2)

In Silico-Based Identification of Natural Inhibitors from Traditionally Used Medicinal Plants that can Inhibit Dengue Infection

Dengue fever (DF) is an endemic disease that has become a public health concern around the globe. The NS3 protease-helicase enzyme is an important target for the development of antiviral drugs against DENV (dengue virus) due to its impact on viral replication. Inhibition of the activity of the NS3 protease-helicase enzyme complex significantly inhibits the infection associated with DENV. Unfortunately, there are no scientifically approved antiviral drugs for its prevention. However, this study has been developed to find natural bioactive molecules that can block the activity of the NS3 protease-helicase enzyme complex associated with DENV infection through molecular docking, MM-GBSA (molecular mechanics-generalized born surface area), and molecular dynamics (MD) simulations. Three hundred forty-two (342) compounds selected from twenty traditional medicinal plants were retrieved and screened against the NS3 protease-helicase protein by molecular docking and MM-GBSA studies, where the top six phytochemicals have been identified based on binding affinities. The six compounds were then subjected to pharmacokinetics and toxicity analysis, and we conducted molecular dynamics simulations on three protein-ligand complexes to validate their stability. Through computational analysis, this study revealed the potential of the two selected natural bioactive inhibitors (CID-440015 and CID-7424) as novel anti-dengue agents.

Computational studies indicated the effectiveness of human metabolites against SARS-Cov-2 main protease

To fight against the devastating coronavirus disease 2019 (COVID-19), identifying robust anti-SARS-CoV-2 therapeutics from all possible directions is necessary. To contribute to this effort, we selected a human metabolites database containing waters and lipid-soluble metabolites to screen against the 3-chymotrypsin-like proteases (3CLpro) protein of SARS-CoV-2. The top 8 hits from virtual screening displayed a docking score varying between ~ - 11 and ~ - 14 kcal/mol. Molecular dynamics simulations complement the virtual screening study in conjunction with the molecular mechanics generalized Born surface area (MM/GBSA) scheme. Our analyses revealed that (HMDB0132640) has the best glide docking score, - 14.06 kcal/mol, and MM-GBSA binding free energy, - 18.08 kcal/mol. The other three lead molecules are also selected along with the top molecule through a critical inspection of their pharmacokinetic properties. HMDB0132640 displayed a better binding affinity than the other three compounds (HMDB0127868, HMDB0134119, and HMDB0125821) due to increased favorable contributions from the intermolecular electrostatic and van der Waals interactions. Further, we have investigated the ligand-induced structural dynamics of the main protease. Overall, we have identified new compounds that can serve as potential leads for developing novel antiviral drugs against SARS-CoV-2 and elucidated molecular mechanisms of their binding to the main protease. Identification of probable hits from human metabolites against SARS-CoV-2 using integrated computational approaches-Missed against MS.

In silico network pharmacology study on Glycyrrhiza glabra: Analyzing the immune-boosting phytochemical properties of Siddha medicinal plant against COVID-19

Immunosenescence is a pertinent factor in the mortality rate caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The changes in the immune system are strongly associated with age and provoke the deterioration of the individual's health. Traditional medical practices in ancient India effectively deal with COVID-19 by boosting natural immunity through medicinal plants. The anti-inflammatory and antiviral properties of Glycyrrhiza glabra are potent in fighting against COVID-19 and promote immunity boost against the severity of the infection. Athimadhura Chooranam, a polyherbal formulation containing Glycyrrhiza glabra as the main ingredient, is recommended as an antiviral Siddha herb by the Ministry of AYUSH. This paper is intended to identify the phytoconstituents of Glycyrrhiza glabra that are actively involved in preventing individuals from COVID-19 transmission. The modulated pathways, enrichment study, and drug-likeness are calculated from the target proteins of the phytoconstituents at the pharmacological activity (Pa) of more than 0.7. Liquiritigenin and Isoliquiritin, the natural compounds in Glycyrrhiza glabra, belong to the flavonoid class and exhibit ameliorative effects against COVID-19. The latter compound displays a higher protein interaction to a maximum of six, out of which HMOX1, PLAU, and PGR are top-hub genes. ADMET screening further confirms the significance of the abovementioned components containing better drug-likeness. The molecular docking and molecular dynamics method identified liquiritigenin as a possible lead molecule capable of inhibiting the activity of the major protease protein of SARS-CoV-2. The findings emphasize the importance of in silico network pharmacological assessments in delivering cost-effective, time-bound clinical drugs.

Study of MDM2 as Prognostic Biomarker in Brain-LGG Cancer and Bioactive Phytochemicals Inhibit the p53-MDM2 Pathway: A Computational Drug Development Approach

An evaluation of the expression and predictive significance of the MDM2 gene in brain lower-grade glioma (LGG) cancer was carried out using onco-informatics pipelines. Several transcriptome servers were used to measure the differential expression of the targeted MDM2 gene and search mutations and copy number variations. GENT2, Gene Expression Profiling Interactive Analysis, Onco-Lnc, and PrognoScan were used to figure out the survival rate of LGG cancer patients. The protein–protein interaction networks between MDM2 gene and its co-expressed genes were constructed by Gene-MANIA tool. Identified bioactive phytochemicals were evaluated through molecular docking using Schrödinger Suite Software, with the MDM2 (PDB ID: 1RV1) target. Protein–ligand interactions were observed with key residues of the macromolecular target. A molecular dynamics simulation of the novel bioactive compounds with the targeted protein was performed. Phytochemicals targeting MDM2 protein, such as Taxifolin and (-)-Epicatechin, have been shown with more highly stable results as compared to the control drug, and hence, concluded that phytochemicals with bioactive potential might be alternative therapeutic options for the management of LGG patients. Our once informatics-based designed pipeline has indicated that the MDM2 gene may have been a predictive biomarker for LGG cancer and selected phytochemicals possessed outstanding interaction results within the macromolecular target’s active site after utilizing in silico approaches. In vitro and in vivo experiments are recommended to confirm these outcomes.

N-acetylglucosamine-phosphatidylinositol de-N-acetylase as a novel target for probing potential inhibitor against Leishmania donovani

Leishmania donavani is the causative agent of leishmaniasis, responsible for social and economic disruption, especially in developing countries. Lack of effective drugs with few side effects have necessitated the discovery of newer therapeutic solutions for leishmaniasis. Glycophosphatidylinositol (GPI) synthesis plays a vital role in protozoan cell membranes structural formation and antigenic modification. Hence, any disruption in its biosynthesis can prove fatal to the parasitic protozoans. N-acetylglucosamine-phosphatidylinositol de-N-acetylase (NAGP-deacetylase) is an enzyme from the GPI biosynthetic pathway that catalyzes the deacetylation of N-acetylglucosaminylphosphatidylinositol to glucosaminylphosphatidylinositol, a step essential for the proper functioning of the enzyme. In the quest for novel scaffolds as anti-leishmaniasis agents, we have executed in silico virtual screening, density function theory, molecular dynamics and MM-GBSA based energy calculations with a natural product library and a diverse library set from Chembridge database. Two compounds, 14671 and 4610, were identified at the enzyme's active site and interacted with catalytic residues, Asp43, Asp44, His41, His147, His 150, Arg80 and Arg231. Both molecules exhibited stable conformation in their protein-ligand complexes with binding free energies for compound-14671 and compound-4610 of -54 ± 4 and -50 ± 4 kcal/mol, respectively. These scaffolds can be incorporated in future synthetic determinations, focusing on developing druggable inhibitor support, increasing potency, and introducing species selectivity.Communicated by Ramaswamy H. Sarma.

Exploration of potential inhibitors for SARS-CoV-2 Mpro considering its mutants via structure-based drug design, molecular docking, MD simulations, MM/PBSA, and DFT calculations

The main protease (Mpro) of SARS-COV-2 plays a vital role in the viral life cycle and pathogenicity. Due to its specific attributes, this 3-chymotrypsin like protease can be a reliable target for the drug design to combat COVID-19. Since the advent of COVID-19, Mpro has undergone many mutations. Here, the impact of 10 mutations based on their frequency and five more based on their proximity to the active site was investigated. For comparison purposes, the docking process was also performed against the Mpros of SARS-COV and MERS-COV. Four inhibitors with the highest docking score (11b, α-ketoamide 13b, Nelfinavir, and PF-07321332) were selected for the structure-based ligand design via fragment replacement, and around 2000 new compounds were thus obtained. After the screening of these new compounds, the pharmacokinetic properties of the best ones were predicted. In the last step, comparative molecular dynamics (MD) simulations, molecular mechanics Poisson-Boltzmann surface area calculations (MM/PBSA), and density functional theory calculations were performed. Among the 2000 newly designed compounds, three of them (NE1, NE2, and NE3), which were obtained by modifications of Nelfinavir, showed the highest affinity against all the Mpro targets. Together, NE1 compound is the best candidate for follow-up Mpro inhibition and drug development studies.

An In-Silico Identification of Potential Flavonoids against Kidney Fibrosis Targeting TGFβR-1

Fibrosis is a hallmark of progressive kidney diseases. The overexpression of profibrotic cytokine, namely transforming growth factor β (TGF-β) due to excessive inflammation and tissue damage, induces kidney fibrosis. The inhibition of TGF-β signaling is markedly limited in experimental disease models. Targeting TGF-β signaling, therefore, offers a prospective strategy for the management of kidney fibrosis. Presently, the marketed drugs have numerous side effects, but plant-derived compounds are relatively safer and more cost-effective. In this study, TGFβR-1 was targeted to identify the lead compounds among flavonoids using various computational approaches, such as ADME/T (absorption, distribution, metabolism, and excretion/toxicity) analysis, molecular docking, and molecular dynamics simulation. ADME/T screening identified a total of 31 flavonoids with drug-like properties of 31 compounds, a total of 5 compounds showed a higher binding affinity to TGFβR-1, with Epicatechin, Fisetin, and Luteolin ranking at the top three (-13.58, -13.17, and -10.50 kcal/mol, respectively), which are comparable to the control drug linagliptin (-9.074 kcal/mol). The compounds also exhibited outstanding protein-ligand interactions. The molecular dynamic simulations revealed a stable interaction of these compounds with the binding site of TGFβR-1. These findings indicate that flavonoids, particularly Epicatechin, Fisetin, and Luteolin, may compete with the ligand-binding site of TGFβR-1, suggesting that these compounds can be further evaluated for the development of potential therapeutics against kidney fibrosis. Further, in-vitro and in-vivo studies are recommended to support the current findings.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Systematic optimization of host-directed therapeutic targets and preclinical validation of repositioned antiviral drugs

Inhibition of host protein functions using established drugs produces a promising antiviral effect with excellent safety profiles, decreased incidence of resistant variants and favorable balance of costs and risks. Genomic methods have produced a large number of robust host factors, providing candidates for identification of antiviral drug targets. However, there is a lack of global perspectives and systematic prioritization of known virus-targeted host proteins (VTHPs) and drug targets. There is also a need for host-directed repositioned antivirals. Here, we integrated 6140 VTHPs and grouped viral infection modes from a new perspective of enriched pathways of VTHPs. Clarifying the superiority of nonessential membrane and hub VTHPs as potential ideal targets for repositioned antivirals, we proposed 543 candidate VTHPs. We then presented a large-scale drug-virus network (DVN) based on matching these VTHPs and drug targets. We predicted possible indications for 703 approved drugs against 35 viruses and explored their potential as broad-spectrum antivirals. In vitro and in vivo tests validated the efficacy of bosutinib, maraviroc and dextromethorphan against human herpesvirus 1 (HHV-1), hepatitis B virus (HBV) and influenza A virus (IAV). Their drug synergy with clinically used antivirals was evaluated and confirmed. The results proved that low-dose dextromethorphan is better than high-dose in both single and combined treatments. This study provides a comprehensive landscape and optimization strategy for druggable VTHPs, constructing an innovative and potent pipeline to discover novel antiviral host proteins and repositioned drugs, which may facilitate their delivery to clinical application in translational medicine to combat fatal and spreading viral infections.

Molecular Docking as a Potential Approach in Repurposing Drugs Against COVID-19: a Systematic Review and Novel Pharmacophore Models

Purpose of Review

This article provides a review of the recent literature related to the FDA-approved drugs that had been repurposed as potential drug candidates against COVID-19. Moreover, we performed a quality pharmacophore study for frequently studied targets, namely, the main protease, RNA-dependent RNA polymerase, and spike protein.

Recent Findings

Ever since the COVID-19 pandemic, the whole spectrum of scientific community is still unable to invent an absolute therapeutic agent for COVID-19. Considering such a fact, drug repurposing strategies seem a truly viable approach to develop novel therapeutic interventions.

Summery

Drug repurposing explores previously approved drugs of known safety and pharmacokinetics profile for possible new effects, reducing the cost, time, and predicting prospective side effects and drug interactions. COVID-19 virulent machinery appeared similar to other viruses, making antiviral agents widely repurposed in pursuit for curative candidates. Our main protease pharmacophoric study revealed multiple features and could be a probable starting point for upcoming research.

Evaluation of in vitro and in silico anti-inflammatory potential of some selected medicinal plants of Bangladesh against cyclooxygenase-II enzyme

ETHNOPHARMACOLOGICAL RELEVANCE

Medicinal plants are sources of chemical treasures that can be used in treatment of different diseases, including inflammatory disorders. Traditionally, Heritiera littoralis, Ceriops decandra, Ligustrum sinense, and Polyscias scutellaria are used to treat pain, hepatitis, breast inflammation. The present research was designed to explore phytochemicals from the ethanol extracts of H. littoralis, C. decandra, L. sinense, and P. scutellaria to discern the possible pharmacophore (s) in the treatment of inflammatory disorders.

MATERIAL AND METHODS

The chemical compounds of experimental plants were identified through GC-MS analysis. Furthermore, in-vitro anti-inflammatory activity was assessed in human erythrocytes and an in-silico study was appraised against COX-2.

RESULTS

The experimental extracts totally revealed 77 compounds in GC-MS analysis and all the extracts showed anti-inflammatory activity in in-vitro assays. The most favorable phytochemicals as anti-inflammatory agents were selected via ADMET profiling and molecular docking with specific protein of the COX-2 enzyme. Molecular dynamics simulation (MDS) confirmed the stability of the selected natural compound at the binding site of the protein. Three phytochemicals exhibited the better competitive result than the conventional anti-inflammatory drug naproxen in molecular docking and MDS studies.

CONCLUSION

Both experimental and computational studies have scientifically revealed the folklore uses of the experimental medicinal plants in inflammatory disorders. Overall, N-(2-hydroxycyclohexyl)-4-methylbenzenesulfonamide (PubChem CID: 575170); Benzeneethanamine, 2-fluoro-. beta., 3, 4-trihydroxy-N-isopropyl (PubChem CID: 547892); and 3,5-di-tert-butylphenol (PubChem CID: 70825) could be the potential leads for COX-2 inhibitor for further evaluation of drug-likeliness.

Can Artemisia herba-alba Be Useful for Managing COVID-19 and Comorbidities?

The focus of this roadmap is to evaluate the possible efficacy of Artemisia herba-alba Asso. (Asteraceae) for the treatment of COVID-19 and some of its symptoms and several comorbidities using a combination of in silico (molecular docking) studies, reported ethnic uses, and pharmacological activity studies of this plant. In this exploratory study, we show that various phytochemicals from Artemisia herba-alba can be useful against COVID-19 (in silico studies) and for its associated comorbidities. COVID-19 is a new disease, so reports of any therapeutic treatments against it (traditional or conventional) are scanty. On the other hand, we demonstrate, using Artemisia herba-alba as an example, that through a proper search and identification of medicinal plant(s) and their phytochemicals identification using secondary data (published reports) on the plant's ethnic uses, phytochemical constituents, and pharmacological activities against COVID-19 comorbidities and symptoms coupled with the use of primary data obtained from in silico (molecular docking and molecular dynamics) studies on the binding of the selected plant's phytochemicals (such as: rutin, 4,5-di-O-caffeoylquinic acid, and schaftoside) with various vital components of SARS-CoV-2, it may be possible to rapidly identify plants that are suitable for further research regarding therapeutic use against COVID-19 and its associated symptoms and comorbidities.

Synergistic Effects of Natural Compounds Toward Inhibition of SARS-CoV-2 3CL Protease

The biggest challenge in medical management and control of the COVID-19 pandemic is the nonavailability of the treatment molecules. While vaccines and other biotherapeutic products for managing COVID-19 have reached the market, a small-molecule cure is yet to be developed. This is relevant because the cost of production, storage, and ease of distribution of a small-molecule drug are significantly more favorable than those of biologics. In this paper, we present a multicompound approach, where two drug molecules are administered concurrently to offer an effective therapy for COVID-19. The co-action of the two compounds, each derived from natural origins, has been demonstrated against the 3CL protease, already recognized as a potential drug target for inhibiting SARS-CoV-2. The pair of compounds pursued in this study are flavonoid and naphthalene scaffold. Individually, they offer ∼30 to 35% inhibition at 10 μM. Comprehensive docking and molecular dynamics simulations elucidate that these compounds exhibit excellent binding in the process, which however quickly deteriorates, and the ligand is separated from the binding site. This suggests that while the ligands initially bind with the protease, they are unable to maintain it for an extended period. However, the simulation showed that a simultaneous docked complex of both the compounds together with the protein boosts the stronger binding for a sufficient time. The enzyme assay exhibited 97 and 85% inhibition activity when both compounds were used together at 100 and 50 μM, respectively. Later, a multiconcentration assay was used to determine the coinhibitory activity, and it was observed that the compounds have ∼20 to 30% inhibition activity even at lower concentrations of 0.5 and 1 μM. Surface plasmon resonance was used to measure the binding of the compounds, and when used together, the compounds had a 10-fold greater binding affinity. Thus, the results demonstrate a synergistic mechanism between the two compounds that enhances the inhibition activity against SARS-CoV-2 3CL protease.

A survey on computational methods in discovering protein inhibitors of SARS-CoV-2

The outbreak of acute respiratory disease in 2019, namely Coronavirus Disease-2019 (COVID-19), has become an unprecedented healthcare crisis. To mitigate the pandemic, there are a lot of collective and multidisciplinary efforts in facilitating the rapid discovery of protein inhibitors or drugs against COVID-19. Although many computational methods to predict protein inhibitors have been developed [ 1– 5], few systematic reviews on these methods have been published. Here, we provide a comprehensive overview of the existing methods to discover potential inhibitors of COVID-19 virus, so-called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). First, we briefly categorize and describe computational approaches by the basic algorithms involved in. Then we review the related biological datasets used in such predictions. Furthermore, we emphatically discuss current knowledge on SARS-CoV-2 inhibitors with the latest findings and development of computational methods in uncovering protein inhibitors against COVID-19.

Interactive Mechanism of Potential Inhibitors with Glycosyl for SARS-CoV-2 by Molecular Dynamics Simulation

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a type of Ribonucleic Acid (RNA) coronavirus and it has infected and killed many people around the world. It is reported that the receptor binding domain of the spike protein (S_RBD) of the SARS-CoV-2 virus is responsible for attachment to human angiotensin converting enzyme II (ACE2). Many researchers are attempting to search potential inhibitors for fighting SARS-CoV-2 infection using theoretical or experimental methods. In terms of experimental and theoretical research, Cefuroxime, Erythromycin, Lincomycin and Ofloxacin are the potential inhibitors of SARS-CoV-2. However, the interactive mechanism of the protein SARS-CoV-2 and the inhibitors are still elusive. Here, we investigated the interactions between S_RBD and the inhibitors using molecular dynamics (MD) simulations. Interestingly, we found that there are two binding sites of S_RBD for the four small molecules. In addition, our analysis also illustrated that hydrophobic and π-π stacking interactions play crucial roles in the interactions between S_RBD and the small molecules. In our work, we also found that small molecules with glycosyl group have more effect on the conformation of S_RBD than other inhibitors, and they are also potential inhibitors for the genetic variants of SARS-CoV-2. This study provides in silico-derived mechanistic insights into the interactions of S_RBD and inhibitors, which may provide new clues for fighting SARS-CoV-2 infection.

Molecular docking and dynamics study to explore phytochemical ligand molecules against the main protease of SARS-CoV-2 from extensive phytochemical datasets

BACKGROUND

The high transmission and pathogenicity of SARS-CoV-2 has led to a pandemic that has halted the world's economy and health. The newly evolved strains and scarcity of vaccines has worsened the situation. The main protease (M^pro) of SARS-CoV-2 can act as a potential target due to its role in viral replication and conservation level.

METHODS

In this study, we have enlisted more than 1100 phytochemicals from Asian plants based on deep literature mining. The compounds library was screened against the M^pro of SARS-CoV-2.

RESULTS

The selected three ligands, Flemichin, Delta-Oleanolic acid, and Emodin 1-O-beta-D-glucoside had a binding energy of -8.9, -8.9, -8.7 KJ/mol respectively. The compounds bind to the active groove of the main protease at; Cys145, Glu166, His41, Met49, Pro168, Met165, Gln189. The multiple descriptors from the simulation study; root mean square deviation, root mean square fluctuation, radius of gyration, hydrogen bond, solvent accessible surface area confirms the stable nature of the protein-ligand complexes. Furthermore, post-md analysis confirms the rigidness in the docked poses over the simulation trajectories.

CONCLUSIONS

Our combinatorial drug design approaches may help researchers to identify suitable drug candidates against SARS-CoV-2.

Pharmacoinformatics and molecular dynamics simulation-based phytochemical screening of neem plant (Azadiractha indica) against human cancer by targeting MCM7 protein

Minichromosome maintenance complex component 7 (MCM7) belongs to the minichromosome maintenance family that is important for the initiation of eukaryotic DNA replication. Overexpression of the MCM7 protein is relative to cellular proliferation and responsible for aggressive malignancy in various cancers. Mechanistically, inhibition of MCM7 significantly reduces the cellular proliferation associated with cancer. To date, no effective small molecular candidate has been identified that can block the progression of cancer induced by the MCM7 protein. Therefore, the study has been designed to identify small molecular-like natural drug candidates against aggressive malignancy associated with various cancers by targeting MCM7 protein. To identify potential compounds against the targeted protein a comprehensive in silico drug design including molecular docking, ADME (Absorption, Distribution, Metabolism and Excretion), toxicity, and molecular dynamics (MD) simulation approaches has been applied. Seventy phytochemicals isolated from the neem tree (Azadiractha indica) were retrieved and screened against MCM7 protein by using the molecular docking simulation method, where the top four compounds have been chosen for further evaluation based on their binding affinities. Analysis of ADME and toxicity properties reveals the efficacy and safety of the selected four compounds. To validate the stability of the protein-ligand complex structure MD simulations approach has also been performed to the protein-ligand complex structure, which confirmed the stability of the selected three compounds including CAS ID:105377-74-0, CID:12308716 and CID:10505484 to the binding site of the protein. In the study, a comprehensive data screening process has performed based on the docking, ADMET properties, and MD simulation approaches, which found a good value of the selected four compounds against the targeted MCM7 protein and indicates as a promising and effective human anticancer agent.

COVID-19: Characteristics and Therapeutics

Novel coronavirus (COVID-19 or 2019-nCoV or SARS-CoV-2), which suddenly emerged in December 2019 is still haunting the entire human race and has affected not only the healthcare system but also the global socioeconomic balances. COVID-19 was quickly designated as a global pandemic by the World Health Organization as there have been about 98.0 million confirmed cases and about 2.0 million confirmed deaths, as of January 2021. Although, our understanding of COVID-19 has significantly increased since its outbreak, and multiple treatment approaches and pharmacological interventions have been tested or are currently under development to mitigate its risk-factors. Recently, some vaccine candidates showed around 95% clinical efficacy, and now receiving emergency use approvals in different countries. US FDA recently approved BNT162 and mRNA-1273 vaccines developed by Pfizer/BioNTech and Moderna Inc. for emergency use and vaccination in the USA. In this review, we present a succinct overview of the SARS-CoV-2 virus structure, molecular mechanisms of infection, COVID-19 epidemiology, diagnosis, and clinical manifestations. We also systematize different treatment strategies and clinical trials initiated after the pandemic outbreak, based on viral infection and replication mechanisms. Additionally, we reviewed the novel pharmacological intervention approaches and vaccine development strategies against COVID-19. We speculate that the current pandemic emergency will trigger detailed studies of coronaviruses, their mechanism of infection, development of systematic drug repurposing approaches, and novel drug discoveries for current and future pandemic outbreaks.