Identification of FDA approved drugs against SARS-CoV-2 RNA dependent RNA polymerase (RdRp) and 3-chymotrypsin-like protease (3CLpro), drug repurposing approach

In silico drug repurposing of potential antiviral inhibitors targeting methyltransferase (2'-O-MTase) domain of Marburg virus

Marburg Virus (MARV) presents a significant threat to human health, highlighting the urgent need for effective therapeutics. The MARV genome encodes a multifunctional 'large' L protein that plays a crucial role in polymerase, capping, and methyltransferase activities. Within this protein, the 2'-O-methyltransferase (2'-O-MTase) domain is essential for viral replication and immune evasion, making it a promising therapeutic target. However, the lack of structural data on this domain limits drug discovery efforts. To address this challenge, we utilized AlphaFold2 to predict a 3D structure of the MARV 2'-O-MTase domain. Molecular docking with its natural ligand, S-adenosyl methionine (SAM), allowed us to identify key active-site residues involved in ligand binding. We then screened 62 known inhibitors against this domain and identified four promising candidates: Lifirafenib (- 9.5 kcal/mol), Dolutegravir (- 8.5 kcal/mol), BRD3969 (- 8.3 kcal/mol), and JFD00244 (- 8.2 kcal/mol). Further, we assessed the pharmacokinetic and pharmacodynamic properties of these compounds to evaluate their drug-likeness. Molecular dynamics simulations, along with MM/GBSA free energy calculations, confirmed stable interactions between the selected inhibitors and the target domain. While these findings highlight promising candidates for MARV, experimental validation through in vitro and in vivo assays is essential to assess their safety and efficacy.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-025-00355-z.

Molecular Insights into Structural Dynamics and Binding Interactions of Selected Inhibitors Targeting SARS-CoV-2 Main Protease

The SARS-CoV-2 main protease (Mpro, also known as 3CLpro) is a key target for antiviral therapy due to its critical role in viral replication and maturation. This study investigated the inhibitory effects of Bofutrelvir, Nirmatrelvir, and Selinexor on 3CLpro through molecular docking, molecular dynamics (MD) simulations, and free energy calculations. Nirmatrelvir exhibited the strongest binding affinity across docking tools (AutoDock Vina: -8.3 kcal/mol; DiffDock: -7.75 kcal/mol; DynamicBound: 7.59 to 7.89 kcal/mol), outperforming Selinexor and Bofutrelvir. Triplicate 300 ns MD simulations revealed that the Nirmatrelvir-3CLpro complex displayed high conformational stability, reduced root mean square deviation (RMSD), and a modest decrease in solvent-accessible surface area (SASA), indicating enhanced structural rigidity. Gibbs free energy analysis highlighted greater flexibility in unbound 3CLpro, stabilized by Nirmatrelvir binding, supported by stable hydrogen bonds. MolProphet prediction tools, targeting the Cys145 residue, confirmed that Nirmatrelvir exhibited the strongest binding, forming multiple hydrophobic, hydrogen, and π-stacking interactions with key residues, and had the lowest predicted IC50/EC50 (9.18 × 10-8 mol/L), indicating its superior potency. Bofutrelvir and Selinexor showed weaker interactions and higher IC50/EC50 values. MM/PBSA analysis calculated a binding free energy of -100.664 ± 0.691 kJ/mol for the Nirmatrelvir-3CLpro complex, further supporting its stability and binding potency. These results underscore Nirmatrelvir's potential as a promising therapeutic agent for SARS-CoV-2 and provide novel insights into dynamic stabilizing interactions through AI-based docking and long-term MD simulations.

Unveiling the Mechanism of Compound Ku-Shen Injection in Liver Cancer Treatment through an Ingredient-Target Network Analysis

BACKGROUND

Compound Ku-Shen Injection (CKI) is a traditional Chinese medicine preparation derived from Ku-Shen and Bai-Tu-Ling, commonly used in the adjunctive treatment of advanced cancers, including liver cancer. However, the underlying mechanisms of CKI's effectiveness in cancer treatment are not well defined.

METHODS

This study employs network pharmacology to investigate the traditional Chinese medicine (TCM) compatibility theory underlying CKI's action in treating liver cancer, with findings substantiated by molecular docking and in vitro experiments. Sixteen active components were identified from CKI, along with 193 potential targets for treating liver cancer. Key therapeutic target proteins, including EGFR and ESR1, were also identified. KEGG enrichment results showed that the neuroactive ligand-receptor interaction, cAMP signaling pathway, and serotonergic synapses make up the key pathway of CKI in the treatment of liver cancer. Molecular docking results confirmed that the key active ingredients effectively bind to the core targets. CCK-8 cytotoxic experiment results show that the CKI key components of oxymatrine and matrine can inhibit the growth of HepG2 liver cancer cell proliferation. A Western blot analysis revealed that oxymatrine suppresses the expression of EGFR, contributing to its therapeutic efficacy against liver cancer.

CONCLUSION

our study elucidated the therapeutic mechanism of CKI in treating liver cancer and unveiled the underlying principles of its TCM compatibility through its mode of action.

Boosting immunity: synergistic antiviral effects of luteolin, vitamin C, magnesium and zinc against SARS-CoV-2 3CLpro

SARS-CoV-2 was first discovered in 2019 and has disseminated throughout the globe to pandemic levels, imposing significant health and economic burdens. Although vaccines against SARS-CoV-2 have been developed, their long-term efficacy and specificity have not been determined, and antiviral drugs remain necessary. Flavonoids, which are commonly found in plants, fruits, and vegetables and are part of the human diet, have attracted considerable attention as potential therapeutic agents due to their antiviral and antimicrobial activities and effects on other biological activities, such as inflammation. The present study uses a combination of biochemical, cellular, molecular dynamics, and molecular docking experiments to provide compelling evidence that the flavonoid luteolin (2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-4H-chromen-4-one) has antiviral activity against SARS-CoV-2 3-chymotrypsin-like protease (3CLpro) that is synergistically enhanced by magnesium, zinc, and vitamin C. The IC50 of luteolin against 2 µM 3CLpro is 78 µM and decreases 10-fold to 7.6 µM in the presence of zinc, magnesium, and vitamin C. Thermodynamic stability analyses revealed that luteolin has minimal effects on the structure of 3CLpro, whereas metal ions and vitamin C significantly alter the thermodynamic stability of the protease. Interactome analysis uncovered potential host-virus interactions and functional clusters associated with luteolin activity, supporting the relevance of this flavone for combating SARS-CoV-2 infection. This comprehensive investigation sheds light on luteolin's therapeutic potential and provides insights into its mechanisms of action against SARS-CoV-2. The novel formulation of luteolin, magnesium, zinc, and vitamin C may be an effective avenue for treating COVID-19 patients.

Unlocking the puzzle: non-defining mutations in SARS-CoV-2 proteome may affect vaccine effectiveness

Introduction

SARS-CoV-2 variants are defined by specific genome-wide mutations compared to the Wuhan genome. However, non-clade-defining mutations may also impact protein structure and function, potentially leading to reduced vaccine effectiveness. Our objective is to identify mutations across the entire viral genome rather than focus on individual mutations that may be associated with vaccine failure and to examine the physicochemical properties of the resulting amino acid changes.

Materials and methods

Whole-genome consensus sequences of SARS-CoV-2 from COVID-19 patients were retrieved from the GISAID database. Analysis focused on Dataset_1 (7,154 genomes from Italy) and Dataset_2 (8,819 sequences from Spain). Bioinformatic tools identified amino acid changes resulting from codon mutations with frequencies of 10% or higher, and sequences were organized into sets based on identical amino acid combinations.

Results

Non-defining mutations in SARS-CoV-2 genomes belonging to clades 21 L (Omicron), 22B/22E (Omicron), 22F/23A (Omicron) and 21J (Delta) were associated with vaccine failure. Four sets of sequences from Dataset_1 were significantly linked to low vaccine coverage: one from clade 21L with mutations L3201F (ORF1a), A27- (S) and G30- (N); two sets shared by clades 22B and 22E with changes A27- (S), I68- (S), R346T (S) and G30- (N); and one set shared by clades 22F and 23A containing changes A27- (S), F486P (S) and G30- (N). Booster doses showed a slight improvement in protection against Omicron clades. Regarding 21J (Delta) two sets of sequences from Dataset_2 exhibited the combination of non-clade mutations P2046L (ORF1a), P2287S (ORF1a), L829I (ORF1b), T95I (S), Y145H (S), R158- (S) and Q9L (N), that was associated with vaccine failure.

Discussion

Vaccine coverage associations appear to be influenced by the mutations harbored by marketed vaccines. An analysis of the physicochemical properties of amino acid revealed that primarily hydrophobic and polar amino acid substitutions occurred. Our results suggest that non-defining mutations across the proteome of SARS-CoV-2 variants could affect the extent of protection of the COVID-19 vaccine. In addition, alteration of the physicochemical characteristics of viral amino acids could potentially disrupt protein structure or function or both.

SRX3177, a CDK4/6-PI3K-BET inhibitor, in combination with an RdRp inhibitor, Molnupiravir, or an entry inhibitor MU-UNMC-2, has potent antiviral activity against the Omicron variant of SARS-CoV-2

Despite considerable progress in developing vaccines and antivirals to combat COVID-19, the rapid mutations of the SARS-CoV-2 genome have limited the durability and efficacy of the current vaccines and therapeutic interventions. Hence, it necessitates the development of novel therapeutic approaches or repurposing existing drugs that target either viral life cycle, host factors, or both. Here, we report that SRX3177, a potent triple-activity CDK4/6-PI3K-BET inhibitor, blocks replication of the SARS-CoV-2 Omicron variant with IC50 values at sub-micromolar concentrations without any impact on the cell proliferation of Calu-3 cells at and below its IC50 concentration. When SRX3177 is combined with EIDD-1931 (active moiety of a small-molecule prodrug Molnupiravir) or MU-UNMC-2 (a SARS-CoV-2 entry inhibitor) at a fixed doses matrix, a synergistic effect was observed, leading to the significant reduction in the dose of the individual compounds to achieve similar inhibition of SARS-CoV-2 replication. Herein, we report that the combination of SRX3177/MPV or SRX3177/UM-UNMC-2 has the potential for further development as a combinational therapy against SARS-CoV-2 and in any future outbreak of beta coronavirus.

Arylamines QSAR-Based Design and Molecular Dynamics of New Phenylthiophene and Benzimidazole Derivatives with Affinity for the C111, Y268, and H73 Sites of SARS-CoV-2 PLpro Enzyme

A non-structural SARS-CoV-2 protein, PLpro, is involved in post-translational modifications in cells, allowing the evasion of antiviral immune response mechanisms. In this study, potential PLpro inhibitory drugs were designed using QSAR, molecular docking, and molecular dynamics. A combined QSAR equation with physicochemical and Free-Wilson descriptors was formulated. The r2, q2, and r2test values were 0.833, 0.770, and 0.721, respectively. From the equation, it was found that the presence of an aromatic ring and a basic nitrogen atom is crucial for obtaining good antiviral activity. Then, a series of structures for the binding sites of C111, Y268, and H73 of PLpro were created. The best compounds were found to exhibit pIC50 values of 9.124 and docking scoring values of -14 kcal/mol. The stability of the compounds in the cavities was confirmed by molecular dynamics studies. A high number of stable contacts and good interactions over time were exhibited by the aryl-thiophenes Pred14 and Pred15, making them potential antiviral candidates.

COVID-19: A novel holistic systems biology approach to predict its molecular mechanisms (in vitro) and repurpose drugs

PURPOSE

COVID-19 strangely kills some youth with no history of physical weakness, and in addition to the lungs, it may even directly harm other organs. Its complex mechanism has led to the loss of any significantly effective drug, and some patients with severe forms still die daily. Common methods for identifying disease mechanisms and drug design are often time-consuming or reductionist. Here, we use a novel holistic systems biology approach to predict its molecular mechanisms (in vitro), significant molecular relations with SARS, and repurpose drugs.

METHODS

We have utilized its relative phylogenic similarity to SARS. Using the available omics data for SARS and the fewer data for COVID-19 to decode the mechanisms and their significant relations, We applied the Cytoscape analyzer, MCODE, STRING, and DAVID tools to predict the topographically crucial molecules, clusters, protein interaction mappings, and functional analysis. We also applied a novel approach to identify the significant relations between the two infections using the Fischer exact test for MCODE clusters. We then constructed and analyzed a drug-gene network using PharmGKB and DrugBank (retrieved using the dgidb).

RESULTS

Some of the shared identified crucial molecules, BPs and pathways included Kaposi sarcoma-associated herpesvirus infection, Influenza A, and NOD-like receptor signaling pathways. Besides, our identified crucial molecules specific to host response against SARS-CoV-2 included FGA, BMP4, PRPF40A, and IFI16.

CONCLUSION

We also introduced seven new repurposed candidate drugs based on the drug-gene network analysis for the identified crucial molecules. Therefore, we suggest that our newly recommended repurposed drugs be further investigated in Vitro and in Vivo against COVID-19.

Cell-specific genome-scale metabolic modeling of SARS-CoV-2-infected lung to identify antiviral enzymes

Computational systems biology plays a key role in the discovery of suitable antiviral targets. We designed a cell-specific, constraint-based modeling technique for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected lungs. We used the gene sequence of the alpha variant of SARS-CoV-2 to build a viral biomass reaction (VBR). We also used the mass proportion of lipids between the viral biomass and its host cell to estimate the stoichiometric coefficients of viral lipids in the reaction. We then integrated the VBR, the gene expression of the alpha variant of SARS-CoV-2, and the generic human metabolic network Recon3D to reconstruct a cell-specific genome-scale metabolic model. An antiviral target discovery (AVTD) platform was introduced using this model to identify therapeutic drug targets for combating COVID-19. The AVTD platform not only identified antiviral genes for eliminating viral replication but also predicted side effects of treatments. Our computational results revealed that knocking out dihydroorotate dehydrogenase (DHODH) might reduce the synthesis rate of cytidine-5'-triphosphate and uridine-5'-triphosphate, which terminate the viral building blocks of DNA and RNA for SARS-CoV-2 replication. Our results also indicated that DHODH is a promising antiviral target that causes minor side effects, which is consistent with the results of recent reports. Moreover, we discovered that the genes that participate in the de novo biosynthesis of glycerophospholipids and ceramides become unidentifiable if the VBR does not involve the stoichiometry of lipids.

Repurposing of Rutan showed effective treatment for COVID-19 disease

Previously, from the tannic sumac plant (Rhus coriaria), we developed the Rutan 25 mg oral drug tablets with antiviral activity against influenza A and B viruses, adenoviruses, paramyxoviruses, herpes virus, and cytomegalovirus. Here, our re-purposing study demonstrated that Rutan at 25, 50, and 100 mg/kg provided a very effective and safe treatment for COVID-19 infection, simultaneously inhibiting two vital enzyme systems of the SARS-CoV-2 virus: 3C-like proteinase (3CLpro) and RNA-dependent RNA polymerase (RdRp). There was no drug accumulation in experimental animals' organs and tissues. A clinical study demonstrated a statistically significant decrease in the C-reactive protein and a reduction of the viremia period. In patients receiving Rutan 25 mg (children) and 100 mg (adults), the frequency of post-COVID-19 manifestations was significantly less than in the control groups not treated with Rutan tablets. Rutan, having antiviral activity, can provide safe treatment and prevention of COVID-19 in adults and children.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, ID NCT05862883.

Targeting the Spike: Repurposing Mithramycin and Dihydroergotamine to Block SARS-CoV-2 Infection

The urgency to find complementary therapies to current SARS-CoV-2 vaccines, whose effectiveness is preserved over time and not compromised by the emergence of new and emerging variants, has become a critical health challenge. We investigate the possibility of jamming the opening of the Receptor Binding Domain (RBD) of the spike protein of SARS-CoV-2 with small compounds. Through in silico screening, we identified two potential candidates that would lock the Receptor Binding Domain (RBD) in a closed configuration, preventing the virus from infecting the host cells. We show that two drugs already approved by the FDA, mithramycin and dihydroergotamine, can block infection using concentrations in the μM range in cell-based assays. Further STD-NMR experiments support dihydroergotamine's direct interaction with the spike protein. Overall, our results indicate that repurposing of these compounds might lead to potential clinical drug candidates for the treatment of SARS-CoV-2 infection.

Fuzzy optimization for identifying antiviral targets for treating SARS-CoV-2 infection in the heart

In this paper, a fuzzy hierarchical optimization framework is proposed for identifying potential antiviral targets for treating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the heart. The proposed framework comprises four objectives for evaluating the elimination of viral biomass growth and the minimization of side effects during treatment. In the application of the framework, Dulbecco's modified eagle medium (DMEM) and Ham's medium were used as uptake nutrients on an antiviral target discovery platform. The prediction results from the framework reveal that most of the antiviral enzymes in the aforementioned media are involved in fatty acid metabolism and amino acid metabolism. However, six enzymes involved in cholesterol biosynthesis in Ham's medium and three enzymes involved in glycolysis in DMEM are unable to eliminate the growth of the SARS-CoV-2 biomass. Three enzymes involved in glycolysis, namely BPGM, GAPDH, and ENO1, in DMEM combine with the supplemental uptake of L-cysteine to increase the cell viability grade and metabolic deviation grade. Moreover, six enzymes involved in cholesterol biosynthesis reduce and fail to reduce viral biomass growth in a culture medium if a cholesterol uptake reaction does not occur and occurs in this medium, respectively.

Therapeutic Potential of Bioactive Compounds from Edible Mushrooms to Attenuate SARS-CoV-2 Infection and Some Complications of Coronavirus Disease (COVID-19)

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a highly infectious positive RNA virus, has spread from its epicenter to other countries with increased mortality and morbidity. Its expansion has hampered humankind's social, economic, and health realms to a large extent. Globally, investigations are underway to understand the complex pathophysiology of coronavirus disease (COVID-19) induced by SARS-CoV-2. Though numerous therapeutic strategies have been introduced to combat COVID-19, none are fully proven or comprehensive, as several key issues and challenges remain unresolved. At present, natural products have gained significant momentum in treating metabolic disorders. Mushrooms have often proved to be the precursor of various therapeutic molecules or drug prototypes. The plentiful bioactive macromolecules in edible mushrooms, like polysaccharides, proteins, and other secondary metabolites (such as flavonoids, polyphenols, etc.), have been used to treat multiple diseases, including viral infections, by traditional healers and the medical fraternity. Some edible mushrooms with a high proportion of therapeutic molecules are known as medicinal mushrooms. In this review, an attempt has been made to highlight the exploration of bioactive molecules in mushrooms to combat the various pathophysiological complications of COVID-19. This review presents an in-depth and critical analysis of the current therapies against COVID-19 versus the potential of natural anti-infective, antiviral, anti-inflammatory, and antithrombotic products derived from a wide range of easily sourced mushrooms and their bioactive molecules.

Polypharmacology guided drug repositioning approach for SARS-CoV2

Drug repurposing has emerged as an important strategy and it has a great potential in identifying therapeutic applications for COVID-19. An extensive virtual screening of 4193 FDA approved drugs has been carried out against 24 proteins of SARS-CoV2 (NSP1-10 and NSP12-16, envelope, membrane, nucleoprotein, spike, ORF3a, ORF6, ORF7a, ORF8, and ORF9b). The drugs were classified into top 10 and bottom 10 drugs based on the docking scores followed by the distribution of their therapeutic indications. As a result, the top 10 drugs were found to have therapeutic indications for cancer, pain, neurological disorders, and viral and bacterial diseases. As drug resistance is one of the major challenges in antiviral drug discovery, polypharmacology and network pharmacology approaches were employed in the study to identify drugs interacting with multiple targets and drugs such as dihydroergotamine, ergotamine, bisdequalinium chloride, midostaurin, temoporfin, tirilazad, and venetoclax were identified among the multi-targeting drugs. Further, a pathway analysis of the genes related to the multi-targeting drugs was carried which provides insight into the mechanism of drugs and identifying targetable genes and biological pathways involved in SARS-CoV2.

Prospecting native and analogous peptides with anti-SARS-CoV-2 potential derived from the trypsin inhibitor purified from tamarind seeds

The study aimed to prospect in silico native and analogous peptides with anti-SARS-CoV-2 potential derived from the trypsin inhibitor purified from tamarind seeds (TTIp). From the most stable theoretical model of TTIp (TTIp 56/287), in silico cleavage was performed for the theoretical identification of native peptides and generation of analogous peptides. The anti-SARS-CoV-2 potential was investigated through molecular dynamics (MD) simulation between the peptides and binding sites of transmembrane serine protease 2 (TMPRSS2), responsible for the entry of SARS-CoV-2 into the host cell. Five native and analogous peptides were obtained and validated through chemical and physical parameters. The best interaction potential energy (IPE) occurred between TMPRSS2 and one of the native peptides obtained by cleavage with trypsin and its analogous peptide. Thus, both peptides showed many hydrophobic residues, a common physical-chemical property among the peptides that inhibit the entry of enveloped viruses, such as SARS-CoV-2, present in specific drugs to treat COVID-19.

Virtual high-throughput screening: Potential inhibitors targeting aminopeptidase N (CD13) and PIKfyve for SARS-CoV-2

Since the outbreak of the novel coronavirus nearly 3 years ago, the world's public health has been under constant threat. At the same time, people's travel and social interaction have also been greatly affected. The study focused on the potential host targets of SARS-CoV-2, CD13, and PIKfyve, which may be involved in viral infection and the viral/cell membrane fusion stage of SARS-CoV-2 in humans. In this study, electronic virtual high-throughput screening for CD13 and PIKfyve was conducted using Food and Drug Administration-approved compounds in ZINC database. The results showed that dihydroergotamine, Saquinavir, Olysio, Raltegravir, and Ecteinascidin had inhibitory effects on CD13. Dihydroergotamine, Sitagliptin, Olysio, Grazoprevir, and Saquinavir could inhibit PIKfyve. After 50 ns of molecular dynamics simulation, seven compounds showed stability at the active site of the target protein. Hydrogen bonds and van der Waals forces were formed with target proteins. At the same time, the seven compounds showed good binding free energy after binding to the target proteins, providing potential drug candidates for the treatment and prevention of SARS-CoV-2 and SARS-CoV-2 variants.

Deciphering molecular mechanisms of SARS-CoV-2 pathogenesis and drug repurposing through GRN motifs: a comprehensive systems biology study

The world has recently been plagued by a new coronavirus infection called SARS-CoV-2. This virus may lead to severe acute respiratory syndrome followed by multiple organ failure. SARS-CoV-2 has approximately 80-90% genetic similarity to SARS-CoV. Given the limited omics data available for host response to the viruses (more limited data for SARS-CoV-2), we attempted to unveil the crucial molecular mechanisms underlying the SARS-CoV-2 pathogenesis by comparing its regulatory network motifs with SARS-CoV. We also attempted to identify the non-shared crucial molecules and their functions to predict the specific mechanisms for each infection and the processes responsible for their different manifestations. Deciphering the crucial shared and non-shared mechanisms at the molecular level and signaling pathways underlying both diseases may help shed light on their pathogenesis and pave the way for other new drug repurposing against COVID-19. We constructed the GRNs for host response to SARS-CoV and SARS-CoV-2 pathogens (in vitro) and identified the significant 3-node regulatory motifs by analyzing them topologically and functionally. We attempted to identify the shared and non-shared regulatory elements and signaling pathways between their host responses. Interestingly, our findings indicated that NFKB1, JUN, STAT1, FOS, KLF4, and EGR1 were the critical shared TFs between motif-related subnetworks in both SARS and COVID-1, which are considered genes with specific functions in the immune response. Enrichment analysis revealed that the NOD-like receptor signaling, TNF signaling, and influenza A pathway were among the first significant pathways shared between SARS and COVID-19 up-regulated DEGs networks, and the term "metabolic pathways" (hsa01100) among the down-regulated DEGs networks. WEE1, PMAIP1, and TSC22D2 were identified as the top three hubs specific to SARS. However, MYPN, SPRY4, and APOL6 were the tops specific to COVID-19 in vitro. The term "Complement and coagulation cascades" pathway was identified as the first top non-shared pathway for COVID-19 and the MAPK signaling pathway for SARS. We used the identified crucial DEGs to construct a drug-gene interaction network to propose some drug candidates. Zinc chloride, Fostamatinib, Copper, Tirofiban, Tretinoin, and Levocarnitine were the six drugs with higher scores in our drug-gene network analysis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03518-x.

Exploration of the Shared Molecular Mechanisms between COVID-19 and Neurodegenerative Diseases through Bioinformatic Analysis

The COVID-19 pandemic has caused millions of deaths and remains a major public health burden worldwide. Previous studies found that a large number of COVID-19 patients and survivors developed neurological symptoms and might be at high risk of neurodegenerative diseases, such as Alzheimer's disease (AD) and Parkinson's disease (PD). We aimed to explore the shared pathways between COVID-19, AD, and PD by using bioinformatic analysis to reveal potential mechanisms, which may explain the neurological symptoms and degeneration of brain that occur in COVID-19 patients, and to provide early intervention. In this study, gene expression datasets of the frontal cortex were employed to detect common differentially expressed genes (DEGs) of COVID-19, AD, and PD. A total of 52 common DEGs were then examined using functional annotation, protein-protein interaction (PPI) construction, candidate drug identification, and regulatory network analysis. We found that the involvement of the synaptic vesicle cycle and down-regulation of synapses were shared by these three diseases, suggesting that synaptic dysfunction might contribute to the onset and progress of neurodegenerative diseases caused by COVID-19. Five hub genes and one key module were obtained from the PPI network. Moreover, 5 drugs and 42 transcription factors (TFs) were also identified on the datasets. In conclusion, the results of our study provide new insights and directions for follow-up studies of the relationship between COVID-19 and neurodegenerative diseases. The hub genes and potential drugs we identified may provide promising treatment strategies to prevent COVID-19 patients from developing these disorders.

Identification of SARS-CoV-2 main protease inhibitors from FDA-approved drugs by artificial intelligence-supported activity prediction system

Although a certain level of efficacy and safety of several vaccine products against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have been established, unmet medical needs for orally active small molecule therapeutic drugs are still very high. As a key drug target molecule, SARS-CoV-2 main protease (M^pro) is focused and large number of in-silico screenings, a part of which were supported by artificial intelligence (AI), have been conducted to identify M^pro inhibitors both through drug repurposing and drug discovery approaches. In the many drug-repurposing studies, docking simulation-based technologies have been mainly employed and contributed to the identification of several M^pro binders. On the other hand, because AI-guided INTerprotein's Engine for New Drug Design (AI-guided INTENDD), an AI-supported activity prediction system for small molecules, enables to propose the potential binders by proprietary AI scores but not docking scores, it was expected to identify novel potential M^pro binders from FDA-approved drugs. As a result, we selected 20 potential M^pro binders using AI-guided INTENDD, of which 13 drugs showed M^pro-binding signal by surface plasmon resonance (SPR) method. Six (6) compounds among the 13 positive drugs were identified for the first time by the present study. Furthermore, it was verified that vorapaxar bound to M^pro with a K_d value of 27 µM by SPR method and inhibited virus replication in SARS-CoV-2 infected cells with an EC₅₀ value of 11 µM. Communicated by Ramaswamy H. Sarma.

In silico evaluation of potential intervention against SARS-CoV-2 RNA-dependent RNA polymerase

Background

With few available effective interventions, emergence of novel mutants responding poorly to existing vaccines and ever swelling newer waves of infection, SARS-CoV-2 is posing difficult challenges to mankind. This mandates development of newer and effective therapeutics to prevent loss of life and contain the spread of this deadly virus. Nsp12 or RNA-dependent RNA polymerase (RdRp) is a suitable druggable target as it plays a central role in viral replication.

Methodology

Catalytically important conserved amino acid residues of RdRp were delineated through a comprehensive literature search and multiple sequence alignments. PDB ID 7BV2 was used to create binding pockets using SeeSAR and to generate docked poses of the FDA approved drugs on the receptor and estimating their binding affinity and other properties.

Result

In silico approach used in this study assisted in prediction of several potential RdRp inhibitors; and re-validation of the already reported ones. Five molecules namely Inosine, Ribavirin, 2-Deoxy-2-Fluoro-D-glucose, Guaifenesin, and Lamivudine were shortlisted which exhibited reasonable binding affinities, with neither torsional nor intermolecular or intramolecular clashes.

Conclusion

This study aimed to widen the prospect of interventions against the SARS-CoV-2 RdRp. Our results also re-validate already reported molecules like 2-Deoxy-D-glucose as a similar molecule 2-deoxy-2-fluoro-D-glucose is picked up in this study. Additionally, ribavirin and lamivudine, already known antivirals with polymerase inhibition activity are also picked up as the top leads. Selected potent inhibitors of RdRp hold promise to cater for any future coronavirus-outbreak subject to in vitro and in vivo validations.

In vitro and in silico evaluation of antiretrovirals against SARS-CoV-2: A drug repurposing approach

Background

Drug repurposing is a valuable strategy for rapidly developing drugs for treating COVID-19. This study aimed to evaluate the antiviral effect of six antiretrovirals against SARS-CoV-2 in vitro and in silico.

Methods

The cytotoxicity of lamivudine, emtricitabine, tenofovir, abacavir, efavirenz and raltegravir on Vero E6 was evaluated by MTT assay. The antiviral activity of each of these compounds was evaluated via a pre-post treatment strategy. The reduction in the viral titer was assessed by plaque assay. In addition, the affinities of the antiretroviral interaction with viral targets RdRp (RNA-dependent RNA polymerase), ExoN-NSP10 (exoribonuclease and its cofactor, the non-structural protein 10) complex and 3CLpro (3-chymotrypsin-like cysteine protease) were evaluated by molecular docking.

Results

Lamivudine exhibited antiviral activity against SARS-CoV-2 at 200 µM (58.3%) and 100 µM (66.7%), while emtricitabine showed anti-SARS-CoV-2 activity at 100 µM (59.6%), 50 µM (43.4%) and 25 µM (33.3%). Raltegravir inhibited SARS-CoV-2 at 25, 12.5 and 6.3 µM (43.3%, 39.9% and 38.2%, respectively). The interaction between the antiretrovirals and SARS-CoV-2 RdRp, ExoN-NSP10 and 3CLpro yielded favorable binding energies (from -4.9 kcal/mol to -7.7 kcal/mol) using bioinformatics methods.

Conclusion

Lamivudine, emtricitabine and raltegravir showed in vitro antiviral effects against the D614G strain of SARS-CoV-2. Raltegravir was the compound with the greatest in vitro antiviral potential at low concentrations, and it showed the highest binding affinities with crucial SARS-CoV-2 proteins during the viral replication cycle. However, further studies on the therapeutic utility of raltegravir in patients with COVID-19 are required.

Antiviral Mechanisms of Curcumin and Its Derivatives in Prevention and Treatment of COVID-19: A Review

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has now plagued the world for almost 3 years. Although vaccines are now available, the severity of the pandemic and the current dearth of approved effective medications have prompted the need for novel treatment approaches. Curcumin, as a food nutraceutical with anti-inflammatory and antioxidant effects, is now under consideration for the prevention and treatment of COVID-19. Curcumin has been demonstrated to retard the entrance of SARS-CoV-2 into cells, interfere with its proliferation inside cells, and curb the hyperinflammatory state caused by the virus by modulating immune system regulators, minimizing the cytokine storm effect, and modulating the renin-angiotensin system. This chapter discusses the role of curcumin and its derivatives in the prevention and treatment of COVID-19 infection, considering the molecular mechanisms involved. It will also focus on the molecular and cellular profiling techniques as essential tools in this research, as these can be used in the identification and development of new biomarkers, drug targets, and therapeutic approaches for improved patient care.

In Silico Identification of Anti-SARS-CoV-2 Medicinal Plants Using Cheminformatics and Machine Learning

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of COVID-19, is spreading rapidly and has caused hundreds of millions of infections and millions of deaths worldwide. Due to the lack of specific vaccines and effective treatments for COVID-19, there is an urgent need to identify effective drugs. Traditional Chinese medicine (TCM) is a valuable resource for identifying novel anti-SARS-CoV-2 drugs based on the important contribution of TCM and its potential benefits in COVID-19 treatment. Herein, we aimed to discover novel anti-SARS-CoV-2 compounds and medicinal plants from TCM by establishing a prediction method of anti-SARS-CoV-2 activity using machine learning methods. We first constructed a benchmark dataset from anti-SARS-CoV-2 bioactivity data collected from the ChEMBL database. Then, we established random forest (RF) and support vector machine (SVM) models that both achieved satisfactory predictive performance with AUC values of 0.90. By using this method, a total of 1011 active anti-SARS-CoV-2 compounds were predicted from the TCMSP database. Among these compounds, six compounds with highly potent activity were confirmed in the anti-SARS-CoV-2 experiments. The molecular fingerprint similarity analysis revealed that only 24 of the 1011 compounds have high similarity to the FDA-approved antiviral drugs, indicating that most of the compounds were structurally novel. Based on the predicted anti-SARS-CoV-2 compounds, we identified 74 anti-SARS-CoV-2 medicinal plants through enrichment analysis. The 74 plants are widely distributed in 68 genera and 43 families, 14 of which belong to antipyretic detoxicate plants. In summary, this study provided several medicinal plants with potential anti-SARS-CoV-2 activity, which offer an attractive starting point and a broader scope to mine for potentially novel anti-SARS-CoV-2 drugs.

A multi-reference poly-conformational method for in silico design, optimization, and repositioning of pharmaceutical compounds illustrated for selected SARS-CoV-2 ligands

Background

This work presents a novel computational multi-reference poly-conformational algorithm for design, optimization, and repositioning of pharmaceutical compounds.

Methods

The algorithm searches for candidates by comparing similarities between conformers of the same compound and identifies target compounds, whose conformers are collectively close to the conformers of each compound in the reference set. Reference compounds may possess highly variable MoAs, which directly, and simultaneously, shape the properties of target candidate compounds.

Results

The algorithm functionality has been case study validated in silico, by scoring ChEMBL drugs against FDA-approved reference compounds that either have the highest predicted binding affinity to our chosen SARS-CoV-2 targets or are confirmed to be inhibiting such targets in-vivo. All our top scoring ChEMBL compounds also turned out to be either high-affinity ligands to the chosen targets (as confirmed in separate studies) or show significant efficacy, in-vivo, against those selected targets. In addition to method case study validation, in silico search for new compounds within two virtual libraries from the Enamine database is presented. The library's virtual compounds have been compared to the same set of reference drugs that we used for case study validation: Olaparib, Tadalafil, Ergotamine and Remdesivir. The large reference set of four potential SARS-CoV-2 compounds has been selected, since no drug has been identified to be 100% effective against the virus so far, possibly because each candidate drug was targeting only one, particular MoA. The goal here was to introduce a new methodology for identifying potential candidate(s) that cover multiple MoA-s presented within a set of reference compounds.

Exploring the Targets of Novel Corona Virus and Docking-based Screening of Potential Natural Inhibitors to Combat COVID-19

There is a need to explore natural compounds against COVID-19 due to their multitargeted actions against various targets of nCoV. They act on multiple sites rather than single targets against several diseases. Thus, there is a possibility that natural resources can be repurposed to combat COVID-19. However, the biochemical mechanisms of these inhibitors were not known. To reveal the mode of anti-nCoV action, structure-based docking plays a major role. The present study is an attempt to explore various potential targets of SARS-CoV-2 and the structure-based screening of various potential natural inhibitors to combat the novel coronavirus.

An integrated computational approach towards the screening of active plant metabolites as potential inhibitors of SARS-CoV-2: an overview

COVID-19 and its causative organism SARS-CoV-2 paralyzed the world and was designated a pandemic by the World Health Organization in March 2020. The worldwide health system is trying to discover an effective therapeutic measure since no clinically authorized medications are present. Screening of plant-derived pharmaceuticals may be a viable technique to fight COVID-19 in this vital situation. This review discusses the potential application of in silico approaches in developing new therapeutic molecules related to preventing SARS-CoV-2 infection. Also, it describes the binding affinity of various phytoconstituents with distinct SARS-CoV-2 target sites. In this perspective, an extensive literature survey was carried out to find the potential phytoconstituents to develop new therapeutic entities to treat COVID-19 in different online academic databases and books. Data retrieved from databases were analyzed and interpreted to conclude that many phytochemicals will bind with the 3-chymotrypsin-like (3CLpro) and papain-like proteases (PL^pro), spike glycoprotein, ACE-2, NSP15-endoribonuclease, and E protein targets of SARS-CoV-2 main protease using in silico molecular docking approach. The present investigations reveal that phytoconstituents such as curcumin, apigenin, chrysophanol, and gingerol are significantly binding with spike glycoprotein; laurolistine, acetoside, etc. are bound with M^pro for anti-SARS-CoV-2 therapies. Using virtual applications of in silico studies, the current study constitutes a progressive data analysis on the mechanism of binding efficiency of distinct classes of plant metabolites against the active sites of SARS-CoV-2. Furthermore, the current review also demonstrates the fundamental necessity of the alternative and complementary medicine for future therapeutic uses of phytoconstituents by phytochemists in the fight against 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.

Virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is considered the etiological agent of the disease that caused the COVID-19 pandemic, and for which there is currently no effective treatment. This pandemic has shown that the rapid identification of therapeutic compounds is critical (when a new virus with high transmissibility occurs) to prevent or reduce as much as possible the loss of human lives. To meet the urgent need for drugs, many strategies were applied for the discovery, respectively the identification of potential therapies / drugs for SARS-CoV-2. Molecular docking and virtual screening are two of the in silico tools/techniques that provided the identification of few SARS-CoV-2 inhibitors, removing ineffective or less effective drugs and thus preventing the loss of resources such as time and additional costs. The main target of this review is to provide a comprehensive overview of how in-silico tools have been used in the crisis management of anti-SARS-CoV-2 drugs, especially in virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses; also, completions were added to the way in which these methods came to meet the requirements of biomedical research in the field. Moreover, the importance and impact of the topic approached for researchers was highlighted by conducting an extensive bibliometric analysis.

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.

Repurposing antiviral phytochemicals from the leaf extracts of Spondias mombin (Linn) towards the identification of potential SARSCOV-2 inhibitors

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), a pneumonia-like disease with a pattern of acute respiratory symptoms, currently remains a significant public health concern causing tremendous human suffering. Although several approved vaccines exist, vaccine hesitancy, limited vaccine availability, high rate of viral mutation, and the absence of approved drugs account for the persistence of SARS-CoV-2 infections. The investigation of possibly repurposing of phytochemical compounds as therapeutic alternatives has gained momentum due to their reported affordability and minimal toxicity. This study investigated anti-viral phytochemical compounds from ethanolic leaf extracts of Spondias mombin L as potential inhibitor candidates against SARS-CoV-2. We identified Geraniin and 2-O-Caffeoyl-(+)-allohydroxycitric acid as potential SARS-CoV-2 inhibitor candidates targeting the SARS-CoV-2 RNA-dependent polymerase receptor-binding domain (RBD) of SARS-CoV-2 viral S-protein and the 3C-like main protease (3CLpro). Geraniin exhibited binding free energy (ΔGbind) of - 25.87 kcal/mol and - 21.74 kcal/mol towards SARS-CoV-2 RNA-dependent polymerase and receptor-binding domain (RBD) of SARS-CoV-2 viral S-protein respectively, whereas 2-O-Caffeoyl-(+)-allohydroxycitric acid exhibited a ΔGbind of - 32 kcal/mol towards 3CLpro. Molecular Dynamics simulations indicated a possible interference to the functioning of SARS-CoV-2 targets by the two identified inhibitors. However, further in vitro and in vivo evaluation of these potential SARS-CoV-2 therapeutic inhibitor candidates is needed.

Drug repurposing against main protease and RNA-dependent RNA polymerase of SARS-CoV-2 using molecular docking, MM-GBSA calculations and molecular dynamics

A virus called severe acute respiratory distress syndrome coronavirus type 2 (SARS‐CoV‐2) is the causing organism of coronavirus disease 2019 (COVID-19), which has severely affected human life and threatened public health. The pandemic took millions of lives worldwide and caused serious negative effects on human society and the economy. SARS-CoV-2 main protease (Mpro) and RNA-dependent RNA polymerase (RdRp) are interesting targets due to their crucial role in viral replication and growth. Since there is only one approved therapy for COVID-19, drug repurposing is a promising approach to finding molecules with potential activity against COVID-19 in a short time and at minimal cost. In this study, virtual screening was performed on the ChEMBL library containing 9923 FDA-approved drugs, using various docking filters with different accuracy. The best drugs with the highest docking scores were further examined for molecular dynamics (MD) studies and MM-GBSA calculations. The results of this study suggest that nadide, cangrelor and denufosol are promising potential candidates against COVID-19. Further in vitro, preclinical and clinical studies of these candidates would help to discover safe and effective anti-COVID-19 drugs.

Production of a functionally active recombinant SARS-CoV-2 (COVID-19) 3C-Like protease and a soluble inactive 3C-like protease-RBD chimeric in a prokaryotic expression system

During the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) intracellular life-cycle, two large polyproteins, pp1a and pp1ab, are produced. Processing of these by viral cysteine proteases, the papain-like protease (PLpro) and the chymotrypsin-like 3C-like protease (3CL-pro) release non-structural proteins necessary for the establishment of the viral replication and transcription complex (RTC), crucial for viral replication. Hence, these proteases are considered prime targets against which anti-coronavirus disease 2019 (COVID-19) drugs could be developed. Here, we describe the expression of a highly soluble and functionally active recombinant 3CL-pro using Escherichia coli BL21 cells. We show that the enzyme functions in a dimeric form and exhibits an unexpected inhibitory profile because its activity is potently blocked by serine rather than cysteine protease inhibitors. In addition, we assessed the ability of our 3CL-pro to function as a carrier for the receptor binding domain (RBD) of the Spike protein. The co-expressed chimeric protein, 3CLpro-RBD, did not exhibit 3CL-pro activity, but its enhanced solubility made purification easier and improved RBD antigenicity when tested against serum from vaccinated individuals in ELISAs. Chimeric proteins containing the 3CL-pro could represent an innovative approach to developing new COVID-19 vaccines.

Seeking antiviral drugs to inhibit SARS-CoV-2 RNA dependent RNA polymerase: A molecular docking analysis

COVID-19 outbreak associated with the severe acute respiratory syndrome coronavirus (SARS-CoV-2) raised health concerns across the globe and has been considered highly transmissible between people. In attempts for finding therapeutic treatment for the new disease, this work has focused on examining the polymerase inhibitors against the SARS-CoV-2 nsp12 and co-factors nsp8 and nsp7. Several polymerase inhibitors were examined against PDB ID: 6M71 using computational analysis evaluating the ligand's binding affinity to replicating groove to the active site. The findings of this analysis showed Cytarabine of -5.65 Kcal/mol with the highest binding probability (70%) to replicating groove of 6M71. The complex stability was then examined over 19 ns molecular dynamics simulation suggesting that Cytarabine might be possible potent inhibitor for the SARS-CoV-2 RNA Dependent RNA Polymerase.

Human/SARS-CoV-2 genome-scale metabolic modeling to discover potential antiviral targets for COVID-19

BACKGROUND

Coronavirus disease 2019 (COVID-19) has caused a substantial increase in mortality and economic and social disruption. The absence of US Food and Drug Administration-approved drugs for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) highlights the need for new therapeutic drugs to combat COVID-19.

METHODS

The present study proposed a fuzzy hierarchical optimization framework for identifying potential antiviral targets for COVID-19. The objectives in the decision-making problem were not only to evaluate the elimination of the virus growth, but also to minimize side effects causing treatment. The identified candidate targets could promote processes of drug discovery and development.

SIGNIFICANT FINDINGS

Our gene-centric method revealed that dihydroorotate dehydrogenase (DHODH) inhibition could reduce viral biomass growth and metabolic deviation by 99.4% and 65.6%, respectively, and increase cell viability by 70.4%. We also identified two-target combinations that could completely block viral biomass growth and more effectively prevent metabolic deviation. We also discovered that the inhibition of two antiviral metabolites, cytidine triphosphate (CTP) and uridine-5'-triphosphate (UTP), exhibits effects similar to those of molnupiravir, which is undergoing phase III clinical trials. Our predictions also indicate that CTP and UTP inhibition blocks viral RNA replication through a similar mechanism to that of molnupiravir.

Whole genome analysis and homology modeling of SARS-CoV-2 Indian isolate reveals potent FDA approved drug choice for treating COVID-19

Coronaviruses have caused enough devastation in the last two decades. These viruses have some rare features while sharing some common features. Novel coronavirus disease (nCoV-19) caused an outbreak with a fatality rate of 5%. It emerged from China and spread into many countries. The present research focused on genome analysis of Indian nCoV-19 Isolate and its translational product subjected to homology modeling and its subsequent molecular simulations to find out potent FDA approved drug for treating COVID-19. Phylogenetic analysis of SARS-CoV-2 Indian isolate shows close resemblance with 17 countries SARS-CoV-2 isolates. Homology modeling of four non-structural proteins translational product of Indian SARS-CoV-2 genome shows high similarity and allowed regions with the existing PDB deposited SARS-CoV-2 target proteins. Finally, these four generated proteins show more affinity with cobicistat, remdesivir and indinavir out of 14 screened FDA approved drugs in molecular docking which is further proven by molecular dynamics simulation and MMGBSA analysis of target ligand complex with best simulation trajectories. Overall our present research findings is that three proposed drugs namely cobicistat, remdesivir and indinavir showed higher interaction with the model SARS-CoV-2 viral target proteins from the Indian nCoV-19 isolate. These compounds could be used as a starting point for the creation of active antiviral drugs to combat the deadly COVID-19 virus during global pandemic and its subsequent viral infection waves across the globe.Communicated by Ramaswamy H. Sarma.

Antiviral drug discovery by targeting the SARS-CoV-2 polyprotein processing by inhibition of the main protease

The spread of SARS-CoV-2, the causative agent for COVID-19, has led to a global and deadly pandemic. To date, few drugs have been approved for treating SARS-CoV-2 infections. In this study, a structure-based approach was adopted using the SARS-CoV-2 main protease (M^pro) and a carefully selected dataset of 37,060 compounds comprising M^pro and antiviral protein-specific libraries. The compounds passed two-step docking filtration, starting with standard precision (SP) followed by extra precision (XP) runs. Fourteen compounds with the highest XP docking scores were examined by 20 ns molecular dynamics simulations (MDs). Based on backbone route mean square deviations (RMSD) and molecular mechanics/generalized Born surface area (MM/GBSA) binding energy, four drugs were selected for comprehensive MDs analysis at 100 ns. Results indicated that birinapant, atazanavir, and ritonavir potently bound and stabilized SARS-CoV-2 M^pro structure. Binding energies higher than -102 kcal/mol, RMSD values <0.22 nm, formation of several hydrogen bonds with M^pro, favourable electrostatic contributions, and low radii of gyration were among the estimated factors contributing to the strength of the binding of these three compounds with M^pro. The top two compounds, atazanavir and birinapant, were tested for their ability to prevent SARS-CoV-2 plaque formation. At 10 µM of birinapant concentration, antiviral tests against SARS-CoV-2 demonstrated a 37% reduction of virus multiplication. Antiviral assays demonstrated that birinapant has high anti-SARS-CoV-2 activity in the low micromolar range, with an IC50 value of 18 ± 3.6 µM. Therefore, birinapant is a candidate for further investigation to determine whether it is a feasible therapy option.

Structural biology of SARS-CoV-2: open the door for novel therapies

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the causative agent of the pandemic disease COVID-19, which is so far without efficacious treatment. The discovery of therapy reagents for treating COVID-19 are urgently needed, and the structures of the potential drug-target proteins in the viral life cycle are particularly important. SARS-CoV-2, a member of the Orthocoronavirinae subfamily containing the largest RNA genome, encodes 29 proteins including nonstructural, structural and accessory proteins which are involved in viral adsorption, entry and uncoating, nucleic acid replication and transcription, assembly and release, etc. These proteins individually act as a partner of the replication machinery or involved in forming the complexes with host cellular factors to participate in the essential physiological activities. This review summarizes the representative structures and typically potential therapy agents that target SARS-CoV-2 or some critical proteins for viral pathogenesis, providing insights into the mechanisms underlying viral infection, prevention of infection, and treatment. Indeed, these studies open the door for COVID therapies, leading to ways to prevent and treat COVID-19, especially, treatment of the disease caused by the viral variants are imperative.

Potential therapeutic options for COVID-19: an update on current evidence

SARS-CoV-2, a novel coronavirus, is the agent responsible for the COVID-19 pandemic and is a major public health concern nowadays. The rapid and global spread of this coronavirus leads to an increase in hospitalizations and thousands of deaths in many countries. To date, great efforts have been made worldwide for the efficient management of this crisis, but there is still no effective and specific treatment for COVID-19. The primary therapies to treat the disease are antivirals, anti-inflammatories and respiratory therapy. In addition, antibody therapies currently have been a many active and essential part of SARS-CoV-2 infection treatment. Ongoing trials are proposed different therapeutic options including various drugs, convalescent plasma therapy, monoclonal antibodies, immunoglobulin therapy, and cell therapy. The present study summarized current evidence of these therapeutic approaches to assess their efficacy and safety for COVID-19 treatment. We tried to provide comprehensive information about the available potential therapeutic approaches against COVID-19 to support researchers and physicians in any current and future progress in treating COVID-19 patients.

Discovery of Zafirlukast as a novel SARS-CoV-2 helicase inhibitor using in silico modelling and a FRET-based assay

The coronavirus helicase is an essential enzyme required for viral replication/transcription pathways. Structural studies revealed a sulphate moiety that interacts with key residues within the nucleotide-binding site of the helicase. Compounds with a sulphoxide or a sulphone moiety could interfere with these interactions and consequently inhibit the enzyme. The molecular operating environment (MOE) was used to dock 189 sulphoxide and sulphone-containing FDA-approved compounds to the nucleotide-binding site. Zafirlukast, a leukotriene receptor antagonist used to treat chronic asthma, achieved the lowest docking score at -8.75 kcals/mol. The inhibitory effect of the compounds on the SARS-CoV-2 helicase dsDNA unwinding activity was tested by a FRET-based assay. Zafirlukast was the only compound to inhibit the enzyme (IC50 = 16.3 µM). The treatment of Vero E6 cells with 25 µM zafirlukast prior to SARS-CoV-2 infection decreased the cytopathic effects of SARS-CoV-2 significantly. These results suggest that zafirlukast alleviates SARS-CoV-2 pathogenicity by inhibiting the viral helicase and impairing the viral replication/transcription pathway. Zafirlukast could be clinically developed as a new antiviral treatment for SARS-CoV-2 and other coronavirus diseases. This discovery is based on molecular modelling, in vitro inhibition of the SARS-CoV helicase activity and cell-based SARS-CoV-2 viral replication.

Binary-QSAR guided virtual screening of FDA approved drugs and compounds in clinical investigation against SARS-CoV-2 main protease

With the emergence of the new SARS-CoV-2 virus, drug repurposing studies have gained substantial importance. Combined with the efficacy of recent improvements in ligand- and target-based virtual screening approaches, virtual screening has become faster and more productive than ever. In the current study, an FDA library of approved drugs and compounds under clinical investigation were screened for their antiviral activity using the antiviral therapeutic activity binary QSAR model of the MetaCore/MetaDrug platform. Among 6733-compound collection, we found 370 compounds with a normalized therapeutic activity value greater than a cutoff of 0.75. Only these selected compounds were used for molecular docking studies against the SARS-CoV-2 main protease (M^pro). After initial short (10 ns) molecular dynamics (MD) simulations with the top-50 docking scored compounds and following molecular mechanics generalized born surface area (MM/GBSA) calculations, top-10 compounds were subjected to longer (100 ns) MD simulations and end-point MM/GBSA estimations. Our virtual screening protocol yielded Cefuroxime pivoxetil, an ester prodrug of second-generation cephalosporin antibiotic Cefuroxime, as being a considerable molecule for drug repurposing against the SARS-CoV-2 M^pro.

The dual role of phytochemicals on SARS-CoV-2 inhibition by targeting host and viral proteins

Background

The severe acute respiratory syndrome-2019 has affected more than 190 million people around the world and caused severe crises throughout the globe. Due to rapid mutation in the viral genome, its became important to simultaneously improvise the host immunity while targeting viral proteins to reduce the severity of infection.

Aim

The current computational work focuses on multi-level rigorous screening of 47 medicinal plant-based phytochemicals for discovering effective phytochemical inhibitors against the host and viral targets.

Experimental procedure

A total of 586 phytochemicals were analyzed in detail based on their drug-likeness, pharmacological properties, and structure-based activity against the viral proteins (Spike glycoprotein, Papain-like protease, and Main protease) and host proteins (ACE2, Importin-subunit α-5, and β-1). Phytochemicals showing higher binding affinity with the dual capacity to target both the categories of proteins were further analyzed by profiling of their chemical reactivity using Density-Functional Theory (DFT) based quantum chemical methods. Finally, detailed molecular dynamics simulations were performed to analyze the interactions of the complexes.

Results and conclusion

The results revealed that the selected phytochemicals from Andrographis paniculata, Aconitum heterophyllum, Costus speciosus and Inula racemosa may have the capacity to act with prominent affinity towards the host and viral proteins. Therefore, the combination of active phytochemicals of these plants may prove to be more beneficial and can be used for developing the potential phytotherapeutic intervention.

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COVID-19 caused severe crisis throughout the globe.

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Current drug discovery efforts are targeting SARS-CoV-2 viral and host proteins using repurposed drugs.

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Screening of 586 phytochemicals from 47 medicinal plants against both the host as well as viral targets.

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Phytochemicals probably acts by inhibiting specific targets, thus help in reducing SARS-CoV-2 infection.