Identification of potential molecules against COVID-19 main protease through structure-guided virtual screening approach

Computational evaluation and benchmark study of 342 crystallographic holo-structures of SARS-CoV-2 Mpro enzyme

The coronavirus disease 19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global health crisis with millions of confirmed cases and related deaths. The main protease (Mpro) of SARS-CoV-2 is crucial for viral replication and presents an attractive target for drug development. Despite the approval of some drugs, the search for effective treatments continues. In this study, we systematically evaluated 342 holo-crystal structures of Mpro to identify optimal conformations for structure-based virtual screening (SBVS). Our analysis revealed limited structural flexibility among the structures. Three docking programs, AutoDock Vina, rDock, and Glide were employed to assess the efficiency of virtual screening, revealing diverse performances across selected Mpro structures. We found that the structures 5RHE, 7DDC, and 7DPU (PDB Ids) consistently displayed the lowest EF, AUC, and BEDROCK scores. Furthermore, these structures demonstrated the worst pose prediction results in all docking programs. Two structural differences contribute to variations in docking performance: the absence of the S1 subsite in 7DDC and 7DPU, and the presence of a subpocket in the S2 subsite of 7DDC, 7DPU, and 5RHE. These findings underscore the importance of selecting appropriate Mpro conformations for SBVS, providing valuable insights for advancing drug discovery efforts.

Raman spectroscopy study of 7,8-dihydrofolate inhibition on the Wuhan strain SARS-CoV-2 binding to human ACE2 receptor

Emerging evidence suggests that elevated levels of folic acid in the bloodstream may confer protection against Wuhan-SARS-CoV-2 infection and mitigate its associated symptoms. Notably, two comprehensive studies of COVID-19 patients in Israel and UK uncovered a remarkable trend, wherein individuals with heightened folic acid levels exhibited only mild symptoms and necessitated no ventilatory support. In parallel, research has underscored the potential connection between decreased folic acid levels and the severity of Covid-19 among hospitalized patients. Yet, the underlying mechanisms governing this intriguing inhibition remain elusive. In a quest to elucidate these mechanisms, we conducted a molecular dynamics simulation approach followed by a Raman spectroscopy study to delve into the intricate interplay between the folic acid metabolite, 7,8-dihydrofolate (DHF), and the angiotensin-converting enzyme ACE2 receptor, coupled with its interaction with the receptor-binding domain (RBD) of the Wuhan strain of SARS-CoV-2. Through a meticulous exploration, we scrutinized the transformation of the ACE2 + RBD complex, allowing these reactants to form bonds. This was juxtaposed with a similar investigation where ACE2 was initially permitted to react with DHF, followed by the exposure of the ACE2 + DHF complex to RBD. We find that DHF, when bonded to ACE2, functions as a physical barrier, effectively inhibiting the binding of the Wuhan strain RBD. This physicochemical process offers a cogent explanation for the observed inhibition of host cell infection in subjects receiving supplementary folic acid doses, as epidemiologically substantiated in multiple studies. This study not only sheds light on a potential avenue for mitigating SARS-CoV-2 infection but also underscores the crucial role of folic acid metabolites in host-virus interactions. This research paves the way for novel therapeutic strategies in the battle against COVID-19 and reinforces the significance of investigating the molecular mechanisms underlying the protective effects of folic acid in the context of viral infections.

Molecular modeling of novel 2-aminopyridine derivatives as potential JAK2 inhibitors: a rational strategy for promising anticancer agents

Janus kinase 2(JAK2) is a potential target for anticancer drugs in the treatment of numerous myeloproliferative diseases due to its central role in the JAK/STAT signaling cascade. In this study, the binding behavior of 2 amino-pyridine derivatives as JAK2 inhibitors was investigated by using multifaceted strategies including 3D-QSAR, molecular docking, Fingerprint analysis, MD simulations, and MM-PBSA calculations. A credible COMFA (q2 = 0.606 and r2 = 0.919) and COMSIA (q2 = 0.641 and r2 = 0.992) model was developed, where the internal and external validation revealed that the obtained 3D-QSAR models could be capable of predicting bioactivities of JAK2 inhibitors. The structural criteria provided by the contour maps of model were used to computationally develop more potent 100 new JAK2 inhibitors. Docking studies were conducted on the model data set and newly developed compounds (in-house library) to demonstrate their binding mechanism and highlight the key interacting residues within JAK2 active site. The selected docked complexes underwent MD simulation (100 ns), which contributed in the further study of the binding interactions. Binding free energy analyses (MMGB/PBSA) revealed that key residues such as Glu930, Leu932 (hinge region), Asp939 (solvent accessible region), Arg980, Asn981and Asp994 (catalytic site) have a significantly facilitate ligand-protein interactions through H-bonding and van der Waals interactions. The preliminary in-silico ADMET evaluation revealed encouraging results for all the modeled and in-house library compounds. The findings of this research have the potential to offer valuable recommendations for the advancement of novel, potent, and efficacious JAK2 inhibitors. Overall, this work has successfully employed a wide range of computer-based methodologies to understand the interaction dynamics between 2-amino-pyridine derivatives and the JAK2 enzyme, which is a crucial target in myeloproliferative disorders.Communicated by Ramaswamy H. Sarma.

Targeting Viral and Cellular Cysteine Proteases for Treatment of New Variants of SARS-CoV-2

The continuous emergence of SARS-CoV-2 variants caused the persistence of the COVID-19 epidemic and challenged the effectiveness of the existing vaccines. The viral proteases are the most attractive targets for developing antiviral drugs. In this scenario, our study explores the use of HIV-1 protease inhibitors against SARS-CoV-2. An in silico screening of a library of HIV-1 proteases identified four anti-HIV compounds able to interact with the 3CLpro of SARS-CoV-2. Thus, in vitro studies were designed to evaluate their potential antiviral effectiveness against SARS-CoV-2. We employed pseudovirus technology to simulate, in a highly safe manner, the adsorption of the alpha (α-SARS-CoV-2) and omicron (ο-SARS-CoV-2) variants of SARS-CoV-2 and study the inhibitory mechanism of the selected compounds for cell-virus interaction. The results reported a mild activity against the viral proteases 3CLpro and PLpro, but efficient inhibitory effects on the internalization of both variants mediated by cathepsin B/L. Our findings provide insights into the feasibility of using drugs exhibiting antiviral effects for other viruses against the viral and host SARS-CoV-2 proteases required for entry.

Molecular Dynamics and Other HPC Simulations for Drug Discovery

High performance computing (HPC) is taking an increasingly important place in drug discovery. It makes possible the simulation of complex biochemical systems with high precision in a short time, thanks to the use of sophisticated algorithms. It promotes the advancement of knowledge in fields that are inaccessible or difficult to access through experimentation and it contributes to accelerating the discovery of drugs for unmet medical needs while reducing costs. Herein, we report how computational performance has evolved over the past years, and then we detail three domains where HPC is essential. Molecular dynamics (MD) is commonly used to explore the flexibility of proteins, thus generating a better understanding of different possible approaches to modulate their activity. Modeling and simulation of biopolymer complexes enables the study of protein-protein interactions (PPI) in healthy and disease states, thus helping the identification of targets of pharmacological interest. Virtual screening (VS) also benefits from HPC to predict in a short time, among millions or billions of virtual chemical compounds, the best potential ligands that will be tested in relevant assays to start a rational drug design process.

Harnessing the druggability at orthosteric and allosteric sites of PD-1 for small molecule discovery by an integrated in silico pipeline

The PD-1/PD-L1 interaction is a promising target for small molecule inhibitors in cancer immunotherapy, but targeting this interface has been challenging. While efforts have been made to identify compounds that target the orthosteric sites, no reports have explored the potential of small molecules to target the allosteric region of PD-1. Therefore, our study aims to establish a pipeline to identify small molecules that can effectively bind to either the orthosteric or allosteric pockets of PD-1. We categorized the PD-1 interface into two hot-spot zones (P-and N-zones) based on extensive analysis of its structural, dynamical, and energetic properties. These zones correspond to the orthosteric and allosteric PPI sites, respectively, targeted by monoclonal antibodies. We used a guided virtual screening workflow to identify hits from ∼7 million compounds library, which were then clustered based on structural similarity and assessed by interaction fingerprinting. The selective and diverse chemical representatives were subjected to MD simulations and binding energetics calculations to filter out false positives and identify actual binders. Binding poses metadynamics calculations confirmed the stability of the final hits in the pocket. This study emphasizes the need for an integrated pipeline that uses molecular dynamics simulations and binding energetics to identify potential binders for the dynamic PD-1/PD-L1 interface, due to the lack of small molecule co-crystals. Only a few potential binders were discovered from a large pool of molecules targeting both the allosteric and orthosteric zones. Our results suggest that the allosteric site has more potential than the orthosteric site for inhibitor design. The identified "computational hits" hold potential as starting points for in vitro evaluations followed by hit-to-lead optimization. Overall, this study represents an effort to establish a computational pipeline for exploring and enriching both the allosteric and orthosteric sites of PPI interfaces, "a tough but indispensable nut to crack".

Fangchinoline inhibits SARS-CoV-2 and MERS-CoV entry

The COVID-19 pandemic caused by SARS-CoV-2, lead to mild to severe respiratory illness and resulted in 6.9 million deaths worldwide. Although vaccines are effective in preventing COVID-19, they may not be sufficient to protect immunocompromised individuals from this respiratory illness. Moreover, novel emerging variants of SARS-CoV-2 pose a risk of new COVID-19 waves. Therefore, identification of effective antivirals is critical in controlling SARS and other coronaviruses, such as MERS-CoV. We show that Fangchinoline (Fcn), a bisbenzylisoquinoline alkaloid, inhibits replication of SARS-CoV, SARS-CoV-2, and MERS-CoV in a range of in vitro assays, by blocking entry. Therapeutic use of Fcn inhibited viral loads in the lungs, and suppressed associated airway inflammation in hACE2. Tg mice and Syrian hamster infected with SARS-CoV-2. Combination of Fcn with remdesivir (RDV) or an anti-leprosy drug, Clofazimine, exhibited synergistic antiviral activity. Compared to Fcn, its synthetic derivative, MK-04-003, more effectively inhibited SARS-CoV-2 and its variants B.1.617.2 and BA.5 in mice. Taken together these data demonstrate that Fcn is a pan beta coronavirus inhibitor, which possibly can be used to combat novel emerging coronavirus diseases.

Literature-Based Discovery to Elucidate the Biological Links between Resistant Hypertension and COVID-19

Multiple studies have reported new or exacerbated persistent or resistant hypertension in patients previously infected with COVID-19. We used literature-based discovery to identify and prioritize multi-scalar explanatory biology that relates resistant hypertension to COVID-19. Cross-domain text mining of 33+ million PubMed articles within a comprehensive knowledge graph was performed using SemNet 2.0. Unsupervised rank aggregation determined which concepts were most relevant utilizing the normalized HeteSim score. A series of simulations identified concepts directly related to COVID-19 and resistant hypertension or connected via one of three renin-angiotensin-aldosterone system hub nodes (mineralocorticoid receptor, epithelial sodium channel, angiotensin I receptor). The top-ranking concepts relating COVID-19 to resistant hypertension included: cGMP-dependent protein kinase II, MAP3K1, haspin, ral guanine nucleotide exchange factor, N-(3-Oxododecanoyl)-L-homoserine lactone, aspartic endopeptidases, metabotropic glutamate receptors, choline-phosphate cytidylyltransferase, protein tyrosine phosphatase, tat genes, MAP3K10, uridine kinase, dicer enzyme, CMD1B, USP17L2, FLNA, exportin 5, somatotropin releasing hormone, beta-melanocyte stimulating hormone, pegylated leptin, beta-lipoprotein, corticotropin, growth hormone-releasing peptide 2, pro-opiomelanocortin, alpha-melanocyte stimulating hormone, prolactin, thyroid hormone, poly-beta-hydroxybutyrate depolymerase, CR 1392, BCR-ABL fusion gene, high density lipoprotein sphingomyelin, pregnancy-associated murine protein 1, recQ4 helicase, immunoglobulin heavy chain variable domain, aglycotransferrin, host cell factor C1, ATP6V0D1, imipramine demethylase, TRIM40, H3C2 gene, COL1A1+COL1A2 gene, QARS gene, VPS54, TPM2, MPST, EXOSC2, ribosomal protein S10, TAP-144, gonadotropins, human gonadotropin releasing hormone 1, beta-lipotropin, octreotide, salmon calcitonin, des-n-octanoyl ghrelin, liraglutide, gastrins. Concepts were mapped to six physiological themes: altered endocrine function, 23.1%; inflammation or cytokine storm, 21.3%; lipid metabolism and atherosclerosis, 17.6%; sympathetic input to blood pressure regulation, 16.7%; altered entry of COVID-19 virus, 14.8%; and unknown, 6.5%.

Structural interaction fingerprints and machine learning for predicting and explaining binding of small molecule ligands to RNA

Ribonucleic acids (RNAs) play crucial roles in living organisms and some of them, such as bacterial ribosomes and precursor messenger RNA, are targets of small molecule drugs, whereas others, e.g. bacterial riboswitches or viral RNA motifs are considered as potential therapeutic targets. Thus, the continuous discovery of new functional RNA increases the demand for developing compounds targeting them and for methods for analyzing RNA-small molecule interactions. We recently developed fingeRNAt-a software for detecting non-covalent bonds formed within complexes of nucleic acids with different types of ligands. The program detects several non-covalent interactions and encodes them as structural interaction fingerprint (SIFt). Here, we present the application of SIFts accompanied by machine learning methods for binding prediction of small molecules to RNA. We show that SIFt-based models outperform the classic, general-purpose scoring functions in virtual screening. We also employed Explainable Artificial Intelligence (XAI)-the SHapley Additive exPlanations, Local Interpretable Model-agnostic Explanations and other methods to help understand the decision-making process behind the predictive models. We conducted a case study in which we applied XAI on a predictive model of ligand binding to human immunodeficiency virus type 1 trans-activation response element RNA to distinguish between residues and interaction types important for binding. We also used XAI to indicate whether an interaction has a positive or negative effect on binding prediction and to quantify its impact. Our results obtained using all XAI methods were consistent with the literature data, demonstrating the utility and importance of XAI in medicinal chemistry and bioinformatics.

Non-oncology drug (meticrane) shows anti-cancer ability in synergy with epigenetic inhibitors and appears to be involved passively in targeting cancer cells

Emerging evidence suggests that chemotherapeutic agents and targeted anticancer drugs have serious side effects on the healthy cells/tissues of the patient. To overcome this, the use of non-oncology drugs as potential cancer therapies has been gaining momentum. Herein, we investigated one non-oncology drug named meticrane (a thiazide diuretic used to treat essential hypertension), which has been reported to indescribably improve the therapeutic efficacy of anti-CTLA4 in mice with AB1 HA tumors. In our hypothesis-driven study, we tested anti-cancer potential meticrane in hematological malignance (leukemia and multiple myeloma) and liver cancer cell lines. Our analysis showed that: 1) Meticrane induced alteration in the cell viability and proliferation in leukemia cells (Jurkat and K562 cells) and liver cancer (SK-hep-1), however, no evidence of apoptosis was detectable. 2) Meticrane showed additive/synergistic effects with epigenetic inhibitors (DNMT1/5AC, HDACs/CUDC-101 and HDAC6/ACY1215). 3) A genome-wide transcriptional analysis showed that meticrane treatment induces changes in the expression of genes associated with non-cancer associated pathways. Of importance, differentially expressed genes showed favorable correlation with the survival-related genes in the cancer genome. 4) We also performed molecular docking analysis and found considerable binding affinity scores of meticrane against PD-L1, TIM-3, CD73, and HDACs. Additionally, we tested its suitability for immunotherapy against cancers, but meticrane showed no response to the cytotoxicity of cytokine-induced killer (CIK) cells. To our knowledge, our study is the first attempt to identify and experimentally confirm the anti-cancer potential of meticrane, being also the first to test the suitability of any non-oncology drug in CIK cell therapy. Beyond that, we have expressed some concerns confronted during testing meticrane that also apply to other non-oncology drugs when considered for future clinical or preclinical purposes. Taken together, meticrane is involved in some anticancer pathways that are passively targeting cancer cells and may be considered as compatible with epigenetic inhibitors.

Design and Identification of Inhibitors for the Spike-ACE2 Target of SARS-CoV-2

When an epidemic started in the Chinese city of Wuhan in December 2019, coronavirus was identified as the cause. Infection by the virus occurs through the interaction of viral S protein with the hosts' angiotensin-converting enzyme 2. By leveraging resources such as the DrugBank database and bioinformatics techniques, ligands with potential activity against the SARS-CoV-2 spike protein were designed and identified in this investigation. The FTMap server and the Molegro software were used to determine the active site of the Spike-ACE2 protein's crystal structure. Virtual screening was performed using a pharmacophore model obtained from antiparasitic drugs, obtaining 2000 molecules from molport^®. The ADME/Tox profiles were used to identify the most promising compounds with desirable drug characteristics. The binding affinity investigation was then conducted with selected candidates. A molecular docking study showed five structures with better binding affinity than hydroxychloroquine. Ligand_003 showed a binding affinity of -8.645 kcal·mol^-1, which was considered an optimal value for the study. The values presented by ligand_033, ligand_013, ligand_044, and ligand_080 meet the profile of novel drugs. To choose compounds with favorable potential for synthesis, synthetic accessibility studies and similarity analyses were carried out. Molecular dynamics and theoretical IC₅₀ values (ranging from 0.459 to 2.371 µM) demonstrate that these candidates are promising for further tests. Chemical descriptors showed that the candidates had strong molecule stability. Theoretical analyses here show that these molecules have potential as SARS-CoV-2 antivirals and therefore warrant further investigation.

Structural insights into SARS-CoV-2 main protease conformational plasticity

The spread of different severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants underscores the need for insights into the structural properties of its structural and non-structural proteins. The highly conserved homo-dimeric chymotrypsin-like protease (3CL M^PRO ), belonging to the class of cysteine hydrolases, plays an indispensable role in processing viral polyproteins that are involved in viral replication and transcription. Studies have successfully demonstrated the role of M^PRO as an attractive drug target for designing antiviral treatments because of its importance in the viral life cycle. Herein, we report the structural dynamics of six experimentally solved structures of M^PRO (i.e., 6LU7, 6M03, 6WQF, 6Y2E, 6Y84, and 7BUY including both ligand-free and ligand-bound states) at different resolutions. We have employed a structure-based balanced forcefield, CHARMM36m through state-of-the-art all-atoms molecular dynamics simulations at µ-seconds scale at room temperature (303K) and pH 7.0 to explore their structure-function relationship. The helical domain-III responsible for dimerization mostly contributes to the altered conformational states and destabilization of M^PRO . A keen observation of the high degree of flexibility in the P5 binding pocket adjoining domain II-III highlights the reason for observation of conformational heterogeneity among the structural ensembles of M^PRO . We also observe a differential dynamics of the catalytic pocket residues His41, Cys145, and Asp187, which may lead to catalytic impairment of the monomeric proteases. Among the highly populated conformational states of the six systems, 6LU7 and 7M03 forms the most stable and compact M^PRO conformation with intact catalytic site and structural integrity. Altogether, our findings from this extensive study provides a benchmark to identify physiologically relevant structures of such promising drug targets for structure-based drug design and discovery of potent drug-like compounds having clinical potential.

Elucidating the Potential Inhibitor against Type 2 Diabetes Mellitus Associated Gene of GLUT4

Diabetes is a chronic hyperglycemic disorder that leads to a group of metabolic diseases. This condition of chronic hyperglycemia is caused by abnormal insulin levels. The impact of hyperglycemia on the human vascular tree is the leading cause of disease and death in type 1 and type 2 diabetes. People with type 2 diabetes mellitus (T2DM) have abnormal secretion as well as the action of insulin. Type 2 (non-insulin-dependent) diabetes is caused by a combination of genetic factors associated with decreased insulin production, insulin resistance, and environmental conditions. These conditions include overeating, lack of exercise, obesity, and aging. Glucose transport limits the rate of dietary glucose used by fat and muscle. The glucose transporter GLUT4 is kept intracellular and sorted dynamically, and GLUT4 translocation or insulin-regulated vesicular traffic distributes it to the plasma membrane. Different chemical compounds have antidiabetic properties. The complexity, metabolism, digestion, and interaction of these chemical compounds make it difficult to understand and apply them to reduce chronic inflammation and thus prevent chronic disease. In this study, we have applied a virtual screening approach to screen the most suitable and drug-able chemical compounds to be used as potential drug targets against T2DM. We have found that out of 5000 chemical compounds that we have analyzed, only two are known to be more effective as per our experiments based upon molecular docking studies and virtual screening through Lipinski's rule and ADMET properties.

A comprehensive perspective of traditional Arabic or Islamic medicinal plants as an adjuvant therapy against COVID-19

COVID-19 is a pulmonary disease caused by SARS-CoV-2. More than 200 million individuals are infected by this globally. Pyrexia, coughing, shortness of breath, headaches, diarrhoea, sore throats, and body aches are among the typical symptoms of COVID-19. The virus enters into the host body by interacting with the ACE2 receptor. Despite many SARS-CoV-2 vaccines manufactured by distinct strategies but any evidence-based particular medication to combat COVID-19 is not available yet. However, further research is required to determine the safety and effectiveness profile of the present therapeutic approaches. In this study, we provide a summary of Traditional Arabic or Islamic medicinal (TAIM) plants' historical use and their present role as adjuvant therapy for COVID-19. Herein, six medicinal plants Aloe barbadensis Miller, Olea europaea, Trigonella foenum-graecum, Nigella sativa, Cassia angustifolia, and Ficus carica have been studied based upon their pharmacological activities against viral infections. These plants include phytochemicals that have antiviral, immunomodulatory, antiasthmatic, antipyretic, and antitussive properties. These bioactive substances could be employed to control symptoms and enhance the development of a possible COVID-19 medicinal synthesis. To determine whether or if these TAIMs may be used as adjuvant therapy and are appropriate, a detailed evaluation is advised.

Phytochemical rich Himalayan Rhododendron arboreum petals inhibit SARS-CoV-2 infection in vitro

Phytochemicals with potential to competitively bind to the host receptors or inhibit SARS-CoV-2 replication, may prove to be useful as adjunct therapeutics for COVID-19. We profiled and investigated the phytochemicals of Rhododendron arboreum petals sourced from Himalayan flora, undertook in vitro studies and found it as a promising candidate against SARS-CoV-2. The phytochemicals were reported in various scientific investigations to act against a range of virus in vitro and in vivo, which prompted us to test against SARS-CoV-2. In vitro assays of R. arboreum petals hot aqueous extract confirmed dose dependent reduction in SARS-CoV-2 viral load in infected Vero E6 cells (80% inhibition at 1 mg/ml; IC50 = 173 µg/ml) and phytochemicals profiled were subjected to molecular docking studies against SARS CoV-2 target proteins. The molecules 5-O-Feruloyl-quinic acid, 3-Caffeoyl-quinic acid, 5-O-Coumaroyl-D-quinic acid, Epicatechin and Catechin showed promising binding affinity with SARS-CoV-2 Main protease (M^Pro; PDB ID: 6LU7; responsible for viral replication) and Human Angiotensin Converting Enzyme-2 (ACE2; PDB ID: 1R4L; mediate viral entry in the host). Molecular dynamics (MD) simulation of 5-O-Feruloyl-quinic acid, an abundant molecule in the extract complexed with the target proteins showed stable interactions. Taken together, the phytochemical profiling, in silico analysis and in vitro anti-viral assay revealed that the petals extract act upon M^Pro and may be inhibiting SARS-CoV-2 replication. This is the first report highlighting R. arboreum petals as a reservoir of antiviral phytochemicals with potential anti-SARS-CoV-2 activity using an in vitro system.

Molecular docking, molecular dynamics simulation and MM-GBSA studies of the activity of glycyrrhizin relevant substructures on SARS-CoV-2 RNA-dependent-RNA polymerase

SARS-CoV-2 is the causative agent of Coronavirus Disease (COVID-19), which is a life-threatening disease. The World Health Organization has classified COVID-19 as a severe worldwide public health pandemic due to its high death rate, quick transmission, and lack of medicines. To counteract the recurrence of the severe acute respiratory syndrome, active antiviral medications are urgently required. Glycyrrhizin was documented with activity on different viral proteins, including SARS-CoV-2; in this study, the activity of glycyrrhizin and its substructures (604 molecules) were screened on SARS-CoV-2 RNA-dependent-RNA polymerase using molecular docking, molecular dynamic (MD) simulation, and MM/GBSA. Sixteen molecules exhibited docking energy higher than -7 kcal/mol; four compounds (10772603, 101088272, 154730753 and glycyrrhizin) showed the highest binding energy, and good stability during MD simulation. The glycyrrhizin compound exhibited favorable docking energy (-7.9 kcal/mol), and it was the most stable complex during MD simulation. The predicted binding free energy of the glycyrrhizin complex was -57 ± 8 kcal/mol. These findings suggest that this molecule, after more validation, could become a good candidate for developing and manufacturing an anti-SARS-CoV-2 medication.Communicated by Ramaswamy H. Sarma.

Discovery of non-nucleoside oxindole derivatives as potent inhibitors against dengue RNA-dependent RNA polymerase

A series of thiazole linked Oxindole-5-Sulfonamide (OSA) derivatives were designed as inhibitors of RNA-dependent RNA polymerase (RdRp) activity of Dengue virus. These were synthesized and then evaluated for their efficacy in ex-vivo virus replication assay using human cell lines. Among 20 primary compounds in the series, OSA-15 was identified as a hit. A series of analogues were synthesized by replacing the difluoro benzyl group of OSA-15 with different substituted benzyl groups. The efficacy of OSA-15derivatives was less than that of the parent compound, except OSA-15-17, which has shown improved efficacy than OSA-15. The further optimization was carried out by adding dimethyl (DM) groups to both the sulfonamide and oxindole NH's to produce OSA-15-DM and OSA-15-17-DM. These two compounds were showing no detectable cytotoxicity and the latter was more efficacious. Further, both these compounds were tested for inhibition in all the serotypes of the Dengue virus using an ex-vivo assay. The EC₅₀ of OSA-15-17-DM was observed in a low micromolar range between 2.5 and 5.0 µg/ml. Computation docking and molecular dynamics simulation studies confirmed the binding of identified hits to DENV RdRp. OSA15-17-DM blocks the RNA entrance and elongation site for their biological activity with high binding affinity. Overall, the identified oxindole derivatives are novel compounds that can inhibit Dengue replication, working as non-nucleoside inhibitors (NNI) to explore as anti-viral RdRp activity.

Finding a prospective dual-target drug for the treatment of coronavirus disease by theoretical study

Spike protein of coronavirus is a key protein in binding and entrance of virus to the human cell via binding to the receptor-binding domain (RBD) domain of S1 subunit to peptidase domain region of ACE2 receptor. In this study, the possible effect of 24 antiviral drugs on the RBD domain of spike protein was investigated via docking and molecular dynamics simulation for finding a dual-target drug. At first, all drugs were docked to the RBD domain of spike protein, and then all complexes and free RBD domains were separately used for molecular dynamics simulation for 50 ns via amber18 software. The simulation results showed that 10 ligands from 28 ligands were separated from the RBD domain, and among 18 remained ligands, baloxavir marboxil, and danoprevir drugs, besides endonuclease activity and protease inhibitory, can bind to key residues of the RBD domain. Then these drugs have a dual target and should be more effective than current drugs, and experimental studies should be done on baloxavir marboxil and danoprevir as more potential drugs for coronavirus disease Communicated by Ramaswamy H. Sarma.

Characterizing the ligand-binding affinity toward SARS-CoV-2 Mpro via physics- and knowledge-based approaches

Computational approaches, including physics- and knowledge-based methods, have commonly been used to determine the ligand-binding affinity toward SARS-CoV-2 main protease (Mpro or 3CLpro). Strong binding ligands can thus be suggested as potential inhibitors for blocking the biological activity of the protease. In this context, this paper aims to provide a short review of computational approaches that have recently been applied in the search for inhibitor candidates of Mpro. In particular, molecular docking and molecular dynamics (MD) simulations are usually combined to predict the binding affinity of thousands of compounds. Quantitative structure-activity relationship (QSAR) is the least computationally demanding and therefore can be used for large chemical collections of ligands. However, its accuracy may not be high. Moreover, the quantum mechanics/molecular mechanics (QM/MM) method is most commonly used for covalently binding inhibitors, which also play an important role in inhibiting the activity of SARS-CoV-2. Furthermore, machine learning (ML) models can significantly increase the searching space of ligands with high accuracy for binding affinity prediction. Physical insights into the binding process can then be confirmed via physics-based calculations. Integration of ML models into computational chemistry provides many more benefits and can lead to new therapies sooner.

A review on computer-aided chemogenomics and drug repositioning for rational COVID-19 drug discovery

Application of materials capable of energy harvesting to increase the efficiency and environmental adaptability is sometimes reflected in the ability of discovery of some traces in an environment-either experimentally or computationally-to enlarge practical application window. The emergence of computational methods, particularly computer-aided drug discovery (CADD), provides ample opportunities for the rapid discovery and development of unprecedented drugs. The expensive and time-consuming process of traditional drug discovery is no longer feasible, for nowadays the identification of potential drug candidates is much easier for therapeutic targets through elaborate in silico approaches, allowing the prediction of the toxicity of drugs, such as drug repositioning (DR) and chemical genomics (chemogenomics). Coronaviruses (CoVs) are cross-species viruses that are able to spread expeditiously from the into new host species, which in turn cause epidemic diseases. In this sense, this review furnishes an outline of computational strategies and their applications in drug discovery. A special focus is placed on chemogenomics and DR as unique and emerging system-based disciplines on CoV drug and target discovery to model protein networks against a library of compounds. Furthermore, to demonstrate the special advantages of CADD methods in rapidly finding a drug for this deadly virus, numerous examples of the recent achievements grounded on molecular docking, chemogenomics, and DR are reported, analyzed, and interpreted in detail. It is believed that the outcome of this review assists developers of energy harvesting materials and systems for detection of future unexpected kinds of CoVs or other variants.

Solanaceae Family Phytochemicals as Inhibitors of 3C-Like Protease of SARS-CoV-2: An In Silico Analysis

COVID-19, caused by the coronavirus SARS-CoV-2, emerged in late December 2019 in Wuhan, China. As of 8 April 2022, the virus has caused a global pandemic, resulting in 494,587,638 infections leading to 6,170,283 deaths around the world. Although several vaccines have received emergency authorization from USA and UK drug authorities and two more in Russia and China, it is too early to comment on the prolonged effectiveness of the vaccines, their availability, and affordability for the developing countries of the world, and the daunting task to vaccinate 7 billion people of the world with two doses of the vaccine with additional booster doses. As a result, it is still worthwhile to search for drugs and several promising leads have been found, mainly through in silico studies. In this study, we have examined the binding energies of several alkaloids and anthocyanin derivatives from the Solanaceae family, a family which contains common consumable vegetables and fruit items such as eggplant, pepper, and tomatoes. Our study demonstrates that Solanaceae family alkaloids such as incanumine and solaradixine, as well as anthocyanins and anthocyanidins, have very high predicted binding energies for the 3C-like protease of SARS-CoV-2 (also known as Mpro). Since Mpro is vital for SARS-CoV-2 replication, the compounds merit potential for further antiviral research towards the objective of obtaining affordable drugs.

Virtual Screening of Repurposed Drugs as Potential Spike Protein Inhibitors of Different SARS-CoV-2 Variants: Molecular Docking Study

Like most of the RNA viruses, SARS-CoV-2 continuously mutates. Although many mutations have an insignificant impact on the virus properties, mutations in the surface protein, especially those in the receptor-binding domain, may lead to immune or vaccine escape variants, or altered binding activities to both the cell receptor and the drugs targeting such a protein. The current study intended to assess the ability of different variants of interest (VOIs) and variants of concern (VOCs) of SARS-CoV-2 for their affinities of binding to different repurposed drugs. Seven FDA approved drugs, namely, camostat, nafamostat mesylate, fenofibrate, umifenovir, nelfinavir, cefoperazone and ceftazidime, were selected based on their reported in vitro and clinical activities against SARA-CoV-2. The S1 protein subunit from eleven different variants, including the latest highly contiguous omicron variant, were used as targets for the docking study. The docking results revealed that all tested drugs possess moderate to high binding energies to the receptor-binding domain (RBD) of the S1 protein for all different variants. Cefoperazone was found to possess the highest binding energy to the RBD of the S1 protein of all the eleven variants. Ceftazidime was the second-best drug in terms of binding affinity towards the S1 RBD of the investigated variants. On the other hand, fenofibrate showed the least binding affinity towards the RBD of the S1 protein of all eleven variants. The binding affinities of anti-spike drugs varied among different variants. Most of the interacting amino acid residues of the receptor fall within the RBD (438–506).

Molecular mechanism of inhibition of COVID-19 main protease by β-adrenoceptor agonists and adenosine deaminase inhibitors using in silico methods

Novel coronavirus (COVID-19) responsible for viral pneumonia which emerged in late 2019 has badly affected the world. No clinically proven drugs are available yet as the targeted therapeutic agents for the treatment of this disease. The viral main protease which helps in replication and transcription inside the host can be an effective drug target. In the present study, we aimed to discover the potential of β-adrenoceptor agonists and adenosine deaminase inhibitors which are used in asthma and cancer/inflammatory disorders, respectively, as repurposing drugs against protease inhibitor by ligand-based and structure-based virtual screening using COVID-19 protease-N3 complex. The AARRR pharmacophore model was used to screen a set of 22,621 molecules to obtain hits, which were subjected to high-throughput virtual screening. Extra precision docking identified four top-scored molecules such as +/--fenoterol, FR236913 and FR230513 with lower binding energy from both categories. Docking identified three major hydrogen bonds with Gly143, Glu166 and Gln189 residues. 100 ns MD simulation was performed for four top-scored molecules to analyze the stability, molecular mechanism and energy requirements. MM/PBSA energy calculation suggested that van der Waals and electrostatic energy components are the main reasons for the stability of complexes. Water-mediated hydrogen bonds between protein-ligand and flexibility of the ligand are found to be responsible for providing extra stability to the complexes. The insights gained from this combinatorial approach can be used to design more potent and bio-available protease inhibitors against novel coronavirus.Communicated by Ramaswamy H. Sarma.

COVID-19 and the Importance of Being Prepared: A Multidisciplinary Strategy for the Discovery of Antivirals to Combat Pandemics

During an emergency, such as a pandemic in which time and resources are extremely scarce, it is important to find effective and rapid solutions when searching for possible treatments. One possibility in this regard is the repurposing of available “on the market” drugs. This is a proof of the concept study showing the potential of a collaboration between two research groups, engaged in computer-aided drug design and control of viral infections, for the development of early strategies to combat future pandemics. We describe a QSAR (quantitative structure activity relationship) based repurposing study on molecular topology and molecular docking for identifying inhibitors of the main protease (Mpro) of SARS-CoV-2, the causative agent of COVID-19. The aim of this computational strategy was to create an agile, rapid, and efficient way to enable the selection of molecules capable of inhibiting SARS-CoV-2 protease. Molecules selected through in silico method were tested in vitro using human coronavirus 229E as a surrogate for SARS-CoV-2. Three strategies were used to screen the antiviral activity of these molecules against human coronavirus 229E in cell cultures, e.g., pre-treatment, co-treatment, and post-treatment. We found >99% of virus inhibition during pre-treatment and co-treatment and 90−99% inhibition when the molecules were applied post-treatment (after infection with the virus). From all tested compounds, Molport-046-067-769 and Molport-046-568-802 are here reported for the first time as potential anti-SARS-CoV-2 compounds.

Molecular interactions and inhibition of the SARS‐CoV‐2 main protease by a thiadiazolidinone derivative

We report molecular interactions and inhibition of the main protease (M^Pro) of SARS‐CoV‐2, a key enzyme involved in the viral life cycle. By using a thiadiazolidinone (TDZD) derivative as a chemical probe, we explore the conformational dynamics of M^Pro via docking protocols and molecular dynamics simulations in all‐atom detail. We reveal the local and global dynamics of M^Pro in the presence of this inhibitor and confirm the inhibition of the enzyme with an IC₅₀ value of 1.39 ± 0.22 μM, which is comparable to other known inhibitors of this enzyme.

Identification and validation of potent inhibitor of Escherichia coli DHFR from MMV pathogen box

The present study is conducted to find the solution of rising antimicrobial resistance (AMR) in Escherichia coli which is a pathogen responsible for fatal systemic infections in human and animals. The enzyme dihydrofolate reductase (DHFR) is found in all organisms. In this study DHFR of E. coli (ec-DHFR) and human DHFR (h-DHFR) is targeted by novel chemical entities (NCE) from the Pathogen box of Medicines for Malaria Venture, Switzerland (MMV) using molecular modelling. The in-silico studies were further validated by in-vitro assays. The virtual screening of 400 MMV compounds was conducted using PyRx standard tool followed by manual docking of selected compounds by Autodock vina and Ligplot program. The in-silico studies showed good binding energy and strong hydrogen bond in docking of MMV675968 with ec-DHFR and no hydrogen bond with h-DHFR. This was further validated by the Molecular dynamic studies that revealed high binding free energy in ec-DHFR and in-vitro assays that produced good synergy in combination study of MMV675968 with last line (meropenem) and last resort (colistin) antibiotics. The extensive MD simulation and energetic analysis thus concludes that MMV675968 targets ec-DHFR. The combination studies were conducted with MMV675968 and FDA approved drugs against a panel of multidrug resistant Escherichia coli isolates. The synergistic results obtained in combination studies concluded that in-vitro data is consistent with in-silico data and that MMV675968 is a potential lead for future process of antimicrobial drug development against the multidrug resistance E. coli.Communicated by Ramaswamy H. Sarma.

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.

Determination of potential inhibitors based on isatin derivatives against SARS-CoV-2 main protease (mpro): a molecular docking, molecular dynamics and structure-activity relationship studies

SARS-COV-2, the novel coronavirus and root of global pandemic COVID-19 caused a severe health threat throughout the world. Lack of specific treatments raised an effort to find potential inhibitors for the viral proteins. The recently invented crystal structure of SARS-CoV-2 main protease (Mpro) and its key role in viral replication; non-resemblance to any human protease makes it a perfect target for inhibitor research. This article reports a computer-aided drug design (CADD) approach for the screening of 118 compounds with 16 distinct heterocyclic moieties in comparison with 5 natural products and 7 repurposed drugs. Molecular docking analysis against Mpro protein were performed finding isatin linked with a oxidiazoles (A2 and A4) derivatives to have the best docking scores of -11.22 kcal/mol and -11.15 kcal/mol respectively. Structure-activity relationship studies showed a good comparison with a known active Mpro inhibitor and repurposed drug ebselen with an IC50 value of -0.67 μM. Molecular Dynamics (MD) simulations for 50 ns were performed for A2 and A4 supporting the stability of the two compounds within the binding pocket, largely at the S1, S2 and S4 domains with high binding energy suggesting their suitability as potential inhibitors of Mpro for SARS-CoV-2.

Computer aided identification of potential SARS CoV-2 main protease inhibitors from diterpenoids and biflavonoids of Torreya nucifera leaves

SARS CoV-2 is the causative agent of the pandemic disease COVID-19. There is an urgent need for effective drugs or vaccines which can effectively combat this outbreak. The main protease (Mpro), a key component for the SARS CoV-2 replication, is considered to be one of the important drug targets for developing anti-COVID-19 drugs. This SARS CoV-2 Mpro/cysteine protease has high sequence similarity with the same protease from SARS CoV-1. Previously, it has been shown experimentally that eight diterpenoids and four biflavonoids derived from the leaf of Torreya nucifera show inhibitory effect on the cleavage/catalytic activity of the SARS CoV-1 Mpro. But whether these phytochemicals exhibit any inhibitory effect on SARS CoV-2 Mpro is unclear. To understand this fact, here, we have adopted various in-silico approaches. Diterpenoids and biflavonoids those qualified pharmacological test (hinokiol, amentoflavone, bilobetin and ginkgetin) and two well-known Mpro inhibitors (N3 and lopinavir) were subjected for molecular docking studies. Only three biflavonoids (amentoflavone, bilobetin and ginkgetin) were selected by comparing their binding affinities with N3 and lopinavir. They interacted with two most important catalytic residues of Mpro (His41 and Cys145). Molecular dynamics studies further revealed that these three Mpro-biflavonoid complexes are highly stable and share a similar degree of compactness. Besides, these complexes experience less conformational fluctuations and more expansion than Mpro-N3 and/or Mpro-lopinavir complex. MM-GBSA and H-bond analysis further corroborated these findings. Altogether, our study suggested that these three biflavonoids could possibly inhibit the proteolytic/catalytic activity of SARS CoV-2 Mpro and might be useful for COVID-19 treatment.Communicated by Ramaswamy H. Sarma.

Computational insight of dexamethasone against potential targets of SARS-CoV-2

The health sector has been on the race to find a potent therapy for coronavirus disease (COVID)-19, a diseases caused by severe acute respiratory syndrome coronavirus (SARS-CoV)-2. Repurposed anti-viral drugs have played a huge role in combating the virus, and most recently, dexamethasone (Dex) have shown its therapeutic activity in severe cases of COVID-19 patients. The study sought to provide insights on the anti-COVID-19 mechanism of Dex at both atomic and molecular level against SARS-CoV-2 targets. Computational methods were employed to predict the binding affinity of Dex to SARS-CoV-2 using the Schrodinger suite (v2020-2). The target molecules and ligand (Dex) were retrieved from PDB and PubChem, respectively. The selected targets were SARS-CoV-2 main protease (Mpro), and host secreted molecules glucocorticoid receptor, and Interleukin-6 (IL-6). Critical analyses such as Protein and ligand preparation, molecular docking, molecular dynamic (MD) simulations, and absorption, distribution, metabolism, excretion (ADME), and toxicity analyses were performed using the targets and the ligand as inputs. Dex showed stronger affinity to its theoretical (glucocorticoid) receptor with a superior docking score of -14.7 and a good binding energy value of -147.48 kcal/mol; while short hydrogen bond distances were observed in both Mpro and IL-6 when compared to glucocorticoid receptor. Based on these findings, Dex-target complexes were used to perform MD simulations to analyze Dex stability at 50 ns. This study demonstrates that Dex could bind to both the viral and host receptors as a potential drug candidate for COVID-19. To ascertain the biological fitness of this study, other SARS-CoV-2 targets should be explored. Also, the in vitro studies of dexamethasone against several SARS-CoV-2 targets warrant further investigation.Communicated by Ramaswamy H. Sarma.

Chemical Pattern Recognition for Quality Analysis of Lonicerae Japonicae Flos and Lonicerae Flos Based on Ultra-High Performance Liquid Chromatography and Anti-SARS-CoV2 Main Protease Activity

Lonicerae japonicae flos (L. japonicae flos, Lonicera japonica Thunb.) is one of the most commonly prescribed botanical drugs in the treatment or prevention of corona virus disease 2019. However, L. japonicae flos is often confused or adulterated with Lonicerae flos (L. flos, Lonicera macrantha (D.Don) Spreng., Shanyinhua in Chinese). The anti-SARS-CoV2 activity and related differentiation method of L. japonicae flos and L. flos have not been documented. In this study, we established a chemical pattern recognition model for quality analysis of L. japonicae flos and L. flos based on ultra-high performance liquid chromatography (UHPLC) and anti-SARS-CoV2 activity. Firstly, chemical data of 59 batches of L. japonicae flos and L. flos were obtained by UHPLC, and partial least squares-discriminant analysis was applied to extract the components that lead to classification. Next, anti-SARS-CoV2 activity was measured and bioactive components were acquired by spectrum-effect relationship analysis. Finally, characteristic components were explored by overlapping feature extracted components and bioactive components. Accordingly, eleven characteristic components were successfully selected, identified, quantified and could be recommended as quality control marker. In addition, chemical pattern recognition model based on these eleven components was established to effectively discriminate L. japonicae flos and L. flos. In sum, the demonstrated strategy provided effective and highly feasible tool for quality assessment of natural products, and offer reference for the quality standard setting.

COVID-19 Knowledge Extractor (COKE): A Curated Repository of Drug-Target Associations Extracted from the CORD-19 Corpus of Scientific Publications on COVID-19

The COVID-19 pandemic has catalyzed a widespread effort to identify drug candidates and biological targets of relevance to SARS-COV-2 infection, which resulted in large numbers of publications on this subject. We have built the COVID-19 Knowledge Extractor (COKE), a web application to extract, curate, and annotate essential drug-target relationships from the research literature on COVID-19. SciBiteAI ontological tagging of the COVID Open Research Data set (CORD-19), a repository of COVID-19 scientific publications, was employed to identify drug-target relationships. Entity identifiers were resolved through lookup routines using UniProt and DrugBank. A custom algorithm was used to identify co-occurrences of the target protein and drug terms, and confidence scores were calculated for each entity pair. COKE processing of the current CORD-19 database identified about 3000 drug-protein pairs, including 29 unique proteins and 500 investigational, experimental, and approved drugs. Some of these drugs are presently undergoing clinical trials for COVID-19. The COKE repository and web application can serve as a useful resource for drug repurposing against SARS-CoV-2. COKE is freely available at https://coke.mml.unc.edu/, and the code is available at https://github.com/DnlRKorn/CoKE.

Proteomics advances towards developing SARS-CoV-2 therapeutics using in silico drug repurposing approaches

Standing amidst the COVID-19 pandemic, we have faced major medical and economic crisis in recent times which remains to be an unresolved issue till date. Although the scientific community has made significant progress towards diagnosis and understanding the disease; however, effective therapeutics are still lacking. Several omics-based studies, especially proteomics and interactomics, have contributed significantly in terms of identifying biomarker panels that can potentially be used for the disease prognosis. This has also paved the way to identify the targets for drug repurposing as a therapeutic alternative. US Food and Drug Administration (FDA) has set in motion more than 500 drug development programs on an emergency basis, most of them are focusing on repurposed drugs. Remdesivir is one such success of a robust and quick drug repurposing approach. The advancements in omics-based technologies has allowed to explore altered host proteins, which were earlier restricted to only SARS-CoV-2 protein signatures. In this article, we have reviewed major contributions of proteomics and interactomics techniques towards identifying therapeutic targets for COVID-19. Furthermore, in-silico molecular docking approaches to streamline potential drug candidates are also discussed.

Synthesis, crystal structure, computational study and anti-virus effect of mixed ligand copper (II) complex with ONS donor Schiff base and 1, 10-phenanthroline

This work deals with the synthesis, crystal structure, computational study and antiviral potential of mixed ligand copper(II) complex [Cu(L)(phen)](1), (where, H₂L = (Z)-N'-((E)-2-hydroxy-3,5-diiodobenzylidene)-N,N-dimethylcarbamohydrazonothioic acid, phen = 1,10-phenanthroline). The Schiff base ligand (H₂L) is coordinated with Cu(II) ion in O, N, S-tridentate mode. The copper complex (1) crystallized in the monoclinic system of the space group P21/c with eight molecules in the unit cell and reveals a square pyramidal geometry. Furthermore, we also perform quantum chemical calculations to get insights into the structure-property relationship and functional properties of ligand (H₂L) and its copper (II) complex [Cu(L)(phen)](1). Complex [Cu(L)(phen)](1) was also virtually designed in-silico evaluation by Swiss-ADME. Additionally, inspiring by recent developments to find a potential inhibitor for the COVID-19 virus, we have also performed molecular docking study of ligand and its copper complex (1) to see if our compounds shows an affinity for the main protease (M^pro) of COVID-19 spike protein (PDB ID: 7C8U). Interestingly, the results are found quite encouraging where the binding affinity and inhibition constant were found to be -7.14 kcal/mol and 5.82 μM for ligand (H₂L) and -6.18 kcal/mol and 0.76 μM for complex [Cu(L)(phen)](1) with M^pro protein. This binding affinity is reasonably well as compared to recently known antiviral drugs. For instance, the binding affinity of ligand and complex was found to be better than docking results of chloroquine (-6.293 kcal/mol), hydroxychloroquine (-5.573 kcal/mol) and remdesivir (-6.352 kcal/mol) with M^pro protein. The present study may offer the technological solutions and potential inhibition to the COVID-19 virus in the ongoing and future challenges of the global community. In the framework of synthesis and characterization of mixed ligand copper (II) complex; the major conclusions can be drawn as follow.

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

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

Structure-based drug repurposing against COVID-19 and emerging infectious diseases: methods, resources and discoveries

To attain promising pharmacotherapies, researchers have applied drug repurposing (DR) techniques to discover the candidate medicines to combat the coronavirus disease 2019 (COVID-19) outbreak. Although many DR approaches have been introduced for treating different diseases, only structure-based DR (SBDR) methods can be employed as the first therapeutic option against the COVID-19 pandemic because they rely on the rudimentary information about the diseases such as the sequence of the severe acute respiratory syndrome coronavirus 2 genome. Hence, to try out new treatments for the disease, the first attempts have been made based on the SBDR methods which seem to be among the proper choices for discovering the potential medications against the emerging and re-emerging infectious diseases. Given the importance of SBDR approaches, in the present review, well-known SBDR methods are summarized, and their merits are investigated. Then, the databases and software applications, utilized for repurposing the drugs against COVID-19, are introduced. Besides, the identified drugs are categorized based on their targets. Finally, a comparison is made between the SBDR approaches and other DR methods, and some possible future directions are proposed.

Phenylethanoid glycosides as a possible COVID-19 protease inhibitor: a virtual screening approach

From the beginning of pandemic, more than 240 million people have been infected with a death rate higher than 2%. Indeed, the current exit strategy involving the spreading of vaccines must be combined with progress in effective treatment development. This scenario is sadly supported by the vaccine's immune activation time and the inequalities in the global immunization schedule. Bringing the crises under control means providing the world population with accessible and impactful new therapeutics. We screened a natural product library that contains a unique collection of 2370 natural products into the binding site of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro). According to the docking score and to the interaction at the active site, three phenylethanoid glycosides (forsythiaside A, isoacteoside, and verbascoside) were selected. In order to provide better insight into the atomistic interaction and test the impact of the three selected compounds at the binding site, we resorted to a half microsecond-long molecular dynamics simulation. As a result, we are showing that forsythiaside A is the most stable molecule and it is likely to possess the highest inhibitory effect against SARS-CoV-2 Mpro. Phenylethanoid glycosides also have been reported to have both protease and kinase activity. This kinase inhibitory activity is very beneficial in fighting viruses inside the body as kinases are required for viral entry, metabolism, and/or reproduction. The dual activity (kinase/protease) of phenylethanoid glycosides makes them very promising anit-COVID-19 agents.

In-Silico approach for identification of effective and stable inhibitors for COVID-19 main protease (Mpro) from flavonoid based phytochemical constituents of Calendula officinalis

The recent outbreak of the coronavirus disease COVID-19 is putting the world towards a great threat. A recent study revealed COVID-19 main protease (Mpro) is responsible for the proteolytic mutation of this virus and is essential for its life cycle. Thus inhibition of this protease will eventually lead to the destruction of this virus. In-Silico Molecular docking was performed with the Native ligand and the 15 flavonoid based phytochemicals of Calendula officinals to check their binding affinity towards the COVID-19 main protease. Finally, the top 3 compounds with the highest affinity have been chosen for molecular dynamics simulation to analyses their dynamic properties and conformational flexibility or stability. In-Silico Docking showed that major phytochemicals of Calendula officinals i.e. rutin, isorhamnetin-3-O-β-D, calendoflaside, narcissin, calendulaglycoside B, calenduloside, calendoflavoside have better binding energy than the native ligand (inhibitor N3). MD simulation of 100 ns revealed that all the protease-ligand docked complexes are overall stable as compare to Mpro-native ligand (inhibitor N3) complex. Overall, rutin and caledoflaside showed better stability, compactness, and flexibility. Our in silico (Virtual molecular docking and Molecular dynamics simulation) studies pointed out that flavonoid based phytochemicals of calendula (rutin, isorhamnetin-3-O-β-D, calendoflaside) may be highly effective for inhibiting Mpro which is the main protease for SARS-CoV-2 causing the deadly disease COVID-19. Rutin is already used as a drug and the other two compounds can be made available for future use. Thus the study points a way to combat COVID-19 by the use of major flavonoid based phytochemicals of Calendula officinals. Communicated by Ramaswamy H. Sarma.

SARS-CoV-2 nucleocapsid protein forms condensates with viral genomic RNA

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection causes Coronavirus Disease 2019 (COVID-19), a pandemic that seriously threatens global health. SARS-CoV-2 propagates by packaging its RNA genome into membrane enclosures in host cells. The packaging of the viral genome into the nascent virion is mediated by the nucleocapsid (N) protein, but the underlying mechanism remains unclear. Here, we show that the N protein forms biomolecular condensates with viral genomic RNA both in vitro and in mammalian cells. While the N protein forms spherical assemblies with homopolymeric RNA substrates that do not form base pairing interactions, it forms asymmetric condensates with viral RNA strands. Cross-linking mass spectrometry (CLMS) identified a region that drives interactions between N proteins in condensates, and deletion of this region disrupts phase separation. We also identified small molecules that alter the size and shape of N protein condensates and inhibit the proliferation of SARS-CoV-2 in infected cells. These results suggest that the N protein may utilize biomolecular condensation to package the SARS-CoV-2 RNA genome into a viral particle.

Drug repurposing against coronavirus disease 2019 (COVID-19): A review

Since December 2019, severe acute respiratory syndrome coronavirus 2 has been found to be the culprit in the coronavirus disease 2019 (COVID-19), causing a global pandemic. Despite the existence of many vaccine programs, the number of confirmed cases and fatalities due to COVID-19 is still increasing. Furthermore, a number of variants have been reported. Because of the absence of approved anti-coronavirus drugs, the treatment and management of COVID-19 has become a global challenge. Under these circumstances, drug repurposing is an effective method to identify candidate drugs with a shorter cycle of clinical trials. Here, we summarize the current status of the application of drug repurposing in COVID-19, including drug repurposing based on virtual computer screening, network pharmacology, and bioactivity, which may be a beneficial COVID-19 treatment.

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Mechanism of SARS-CoV-2 infection and drug targets were reviewed.

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Drug repurposing against COVID-19 based on computer virtual screening, network pharmacology, bioactivity were summarized.

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The use of drug repurposing in COVID-19 was addressed.

Drug repurposing studies targeting SARS-CoV-2: an ensemble docking approach on drug target 3C-like protease (3CLpro)

The COVID-19 pandemic has been responsible for several deaths worldwide. The causative agent behind this disease is the Severe Acute Respiratory Syndrome - novel Coronavirus 2 (SARS-CoV-2). SARS-CoV-2 belongs to the category of RNA viruses. The main protease, responsible for the cleavage of the viral polyprotein is considered as one of the hot targets for treating COVID-19. Earlier reports suggest the use of HIV anti-viral drugs for targeting the main protease of SARS-CoV, which caused SARS in the year 2002-2003. Hence, drug repurposing approach may prove to be useful in targeting the main protease of SARS-CoV-2. The high-resolution crystal structure of the main protease of SARS-CoV-2 (PDB ID: 6LU7) was used as the target. The Food and Drug Administration approved and SWEETLEAD database of drug molecules were screened. The apo form of the main protease was simulated for a cumulative of 150 ns and 10 μs open-source simulation data was used, to obtain conformations for ensemble docking. The representative structures for docking were selected using RMSD-based clustering and Markov State Modeling analysis. This ensemble docking approach for the main protease helped in exploring the conformational variation in the drug-binding site of the main protease leading to the efficient binding of more relevant drug molecules. The drugs obtained as top hits from the ensemble docking possessed anti-bacterial and anti-viral properties. This in silico ensemble docking approach would support the identification of potential candidates for repurposing against COVID-19.Communicated by Ramaswamy H. Sarma.

Comprehensive Consensus Analysis of SARS-CoV-2 Drug Repurposing Campaigns

The current COVID-19 pandemic has elicited extensive repurposing efforts (both small and large scale) to rapidly identify COVID-19 treatments among approved drugs. Herein, we provide a literature review of large-scale SARS-CoV-2 antiviral drug repurposing efforts and highlight a marked lack of consistent potency reporting. This variability indicates the importance of standardizing best practices-including the use of relevant cell lines, viral isolates, and validated screening protocols. We further surveyed available biochemical and virtual screening studies against SARS-CoV-2 targets (Spike, ACE2, RdRp, PLpro, and Mpro) and discuss repurposing candidates exhibiting consistent activity across diverse, triaging assays and predictive models. Moreover, we examine repurposed drugs and their efficacy against COVID-19 and the outcomes of representative repurposed drugs in clinical trials. Finally, we propose a drug repurposing pipeline to encourage the implementation of standard methods to fast-track the discovery of candidates and to ensure reproducible results.

From Fighting Critters to Saving Lives: Polyphenols in Plant Defense and Human Health

Polyphenols, such as flavonoids and phenolic acids, are a group of specialized metabolites in plants that largely aid in plant defense by deterring biotic stressors and alleviating abiotic stress. Polyphenols offer a wide range of medical applications, acting as preventative and active treatments for diseases such as cancers and diabetes. Recently, researchers have proposed that polyphenols may contribute to certain applications aimed at tackling challenges related to the COVID-19 pandemic. Understanding the beneficial impacts of phytochemicals, such as polyphenols, could potentially help prepare society for future pandemics. Thus far, most reviews have focused on polyphenols in cancer prevention and treatment. This review aims to provide a comprehensive discussion on the critical roles that polyphenols play in both plant chemical defense and human health based on the most recent studies while highlighting prospective avenues for future research, as well as the implications for phytochemical-based applications in both agricultural and medical fields.

Effectiveness of Natural Antioxidants against SARS-CoV-2? Insights from the In-Silico World

The SARS CoV-2 pandemic has affected millions of people around the globe. Despite many efforts to find some effective medicines against SARS CoV-2, no established therapeutics are available yet. The use of phytochemicals as antiviral agents provides hope against the proliferation of SARS-CoV-2. Several natural compounds were analyzed by virtual screening against six SARS CoV-2 protein targets using molecular docking simulations in the present study. More than a hundred plant-derived secondary metabolites have been docked, including alkaloids, flavonoids, coumarins, and steroids. SARS CoV-2 protein targets include Main protease (MPro), Papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp), Spike glycoprotein (S), Helicase (Nsp13), and E-Channel protein. Phytochemicals were evaluated by molecular docking, and MD simulations were performed using the YASARA structure using a modified genetic algorithm and AMBER03 force field. Binding energies and dissociation constants allowed the identification of potentially active compounds. Ligand-protein interactions provide an insight into the mechanism and potential of identified compounds. Glycyrrhizin and its metabolite 18-β-glycyrrhetinic acid have shown a strong binding affinity for MPro, helicase, RdRp, spike, and E-channel proteins, while a flavonoid Baicalin also strongly binds against PLpro and RdRp. The use of identified phytochemicals may help to speed up the drug development and provide natural protection against SARS-CoV-2.

Virtual screening and dynamics of potential inhibitors targeting RNA binding domain of nucleocapsid phosphoprotein from SARS-CoV-2

The emergence of the coronavirus disease-2019 pandemic has led to an outbreak in the world. The SARS-CoV-2 is seventh and latest in coronavirus family with unique exonucleases for repairing any mismatches in newly transcribed genetic material. Therefore, drugs with novel additional mechanisms are required to simultaneously target and eliminate the virus. Thus, a newly deciphered N protein is taken as a target that belongs to SARS-CoV-2. They play a vital role in RNA transcription, viral replication and new virion formation. This study used virtual screening, molecular modeling and docking of the 8987 ligands from Asinex and PubChem databases against this novel target protein. Three hotspot sites having DScore ≥1 (Site 1, Site 2 and Site 3) for ligand binding were selected. Subsequently, high throughput screening, standard precision and extra precision docking process and molecular dynamics concluded three best drugs from two libraries. Two antiviral moieties from Asinex databases (5817 and 6799) have docking scores of -10.29 and -10.156; along with their respective free binding energies (ΔG bind) of -51.96 and -64.36 on Site 3. The third drug, Zidovudine, is from PubChem database with docking scores of -9.75 with its binding free energies (ΔG bind) of -59.43 on Site 3. The RMSD and RMSF were calculated for all the three drugs through molecular dynamics simulation studies for 50 ns. Zidovudine shows a very stable interaction with fluctuation starting at 2.4 Å on 2 ns and remained stable at 3 Å from 13 to 50 ns. Thus, paving the way for further biological validation as a potential treatment.Communicated by Ramaswamy H. Sarma.

Structurally modified compounds of hydroxychloroquine, remdesivir and tetrahydrocannabinol against main protease of SARS-CoV-2, a possible hope for COVID-19: Docking and molecular dynamics simulation studies

Now a days, more than 200 countries faces the health crisis due to epidemiological disease COVID-19 caused by SARS-CoV-2 virus. It will cause a very high impact on world's economy and global health sector. Earlier the structure of main protease (M^pro) protein was deposited in the RCSB protein repository. Hydroxychloroquine (HCQ) and remdesivir were found to effective in treatment of COVID-19 patients. Here we have performed docking and molecule dynamic (MD) simulation study of HCQ and remdesivir with M^pro protein which gave promising results to inhibit M^pro protein in SARS-CoV-2. On the basis of results obtained we designed structurally modified 18 novel derivatives of HCQ, remdesivir and tetrahydrocannabinol (THC) and carried out docking studies of all the derivatives. From the docking studies six molecules DK4, DK7, DK10, DK16, DK17 and DK19 gave promising results and can be use as inhibitor for M^pro of SARS-CoV-2 to control COVID-19 very effectively. Further, molecular dynamics simulation of one derivative of HCQ and one derivative of tetrahydrocannabinol showing excellent docking score was performed along with the respective parent molecules. The two derivatives gave excellent docking score and higher stability than the parent molecule as validated with molecular dynamics (MD) simulation for the binding affinities towards M^pro of SARS-CoV-2 thus represented as strong inhibitors at very low concentration.

Repurposing cefuroxime for treatment of COVID-19: a scoping review of in silico studies

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of Coronavirus disease 19 (COVID-19), is a novel human Coronavirus that is responsible for about 300,000 deaths worldwide. To date, there is no confirmed treatment or vaccine prevention strategy against COVID-19. Due to the urgent need for effective treatment, drug repurposing is regarded as the immediate option. Potential drugs can often be identified via in silico drug screening experiments. Consequently, there has been an explosion of in silico experiments to find drug candidates or investigate anecdotal claims. One drug with several anecdotal accounts of benefit is Cefuroxime. The aim of this study was to identify and summarize in silico evidence for possible activity of Cefuroxime against SARS-CoV-2.To this end, we performed a scoping review of literature of in silico drug repurposing experiments for SARS-CoV-2 using PRISMA-ScR. We searched Medline, Embase, Scopus, Web of Knowledge, and Google Scholar for original studies published between 1st Feb, 2020 and 15th May, 2020 that screened drug libraries, and identified Cefuroxime as a top-ranked potential inhibitor drug against SARS-CoV-2 proteins. Six studies were identified. These studies reported Cefuroxime as a potential inhibitor of 3 key SARS-CoV-2 proteins; main protease, RNA dependent RNA polymerase, and ACE2-Spike complex. We provided a summary of the methodology and findings of the identified studies. Our scoping review identified significant in silico evidence that Cefuroxime may be a potential multi-target inhibitor of SARS-CoV-2. Further in vitro and in vivo studies are required to evaluate the potential of Cefuroxime for COVID-19.Communicated by Ramaswamy H. Sarma.

Computational Chemistry to Repurposing Drugs for the Control of COVID-19

Thus far, in 2021, 219 countries with over 175 million people have been infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 is a positive sense, single-stranded RNA virus, and is the causal agent for coronavirus disease (COVID-19). Due to the urgency of the situation, virtual screening as a computational modeling method offers a fast and effective modality of identifying drugs that may be effective against SARS-CoV-2. There has been an overwhelming abundance of molecular docking against SARS-CoV-2 in the last year. Due to the massive volume of computational studies, this systematic review has been created to evaluate and summarize the findings of existing studies. Herein, we report on computational articles of drugs which target, (1) viral protease, (2) Spike protein-ACE 2 interaction, (3) RNA-dependent RNA polymerase, and (4) other proteins and nonstructural proteins of SARS-CoV-2. Based on the studies presented, there are 55 identified natural or drug compounds with potential anti-viral activity. The next step is to show anti-viral activity in vitro and translation to determine effectiveness into human clinical trials.