In silico virtual screening, characterization, docking and molecular dynamics studies of crucial SARS-CoV-2 proteins

Exploring Cannabinoids as Potential Inhibitors of SARS-CoV-2 Papain-like Protease: Insights from Computational Analysis and Molecular Dynamics Simulations

The emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has triggered a global COVID-19 pandemic, challenging healthcare systems worldwide. Effective therapeutic strategies against this novel coronavirus remain limited, underscoring the urgent need for innovative approaches. The present research investigates the potential of cannabis compounds as therapeutic agents against SARS-CoV-2 through their interaction with the virus's papain-like protease (PLpro) protein, a crucial element in viral replication and immune evasion. Computational methods, including molecular docking and molecular dynamics (MD) simulations, were employed to screen cannabis compounds against PLpro and analyze their binding mechanisms and interaction patterns. The results showed cannabinoids with binding affinities ranging from -6.1 kcal/mol to -4.6 kcal/mol, forming interactions with PLpro. Notably, Cannabigerolic and Cannabidiolic acids exhibited strong binding contacts with critical residues in PLpro's active region, indicating their potential as viral replication inhibitors. MD simulations revealed the dynamic behavior of cannabinoid-PLpro complexes, highlighting stable binding conformations and conformational changes over time. These findings shed light on the mechanisms underlying cannabis interaction with SARS-CoV-2 PLpro, aiding in the rational design of antiviral therapies. Future research will focus on experimental validation, optimizing binding affinity and selectivity, and preclinical assessments to develop effective treatments against COVID-19.

Exploration of limonoids for their broad spectrum antiviral potential via DFT, molecular docking and molecular dynamics simulation approach

Limonoids serve as vital secondary metabolites. Citrus limonoids show a wide range of pharmacological potential. As a result of which limonoids from citrus are of considerable research interest. Identification of new therapeutic molecules from natural origins has been widely adopted as a successful strategy in drug discovery. This work mainly focused on the high-throughput computational exploration of the antiviral potential of three vital limonoids, i.e. Obacunone, Limonin and Nomilin against spike proteins of SARS CoV-2 (PDB:6LZG), Zika virus NS3 helicase (PDB:5JMT), Serotype 2 RNA dependent RNA polymerase of dengue virus (PDB:5K5M). Herein we report the molecular docking, MD simulation studies of nine docked complexes, and density functional theory (DFT) of selected limonoids. The results of this study indicated that all three limonoids have good molecular features but out of these three obacunone exerted satisfactory results for DFT, docking and MD simulation study.

Possible cerebroprotective effect of citronellal: molecular docking, MD simulation and in vivo investigations

This study focused on molecular docking, dynamic simulation, and in vivo approaches to examine the molecular interactions between citronellal (CT) and neurotoxic proteins. In silico studies of CT were performed using proteins involved in the pathophysiology of stroke, such as interleukin-6 (IL-6), interleukin-12 (IL-12), TNF-α, and nitric oxide synthase (NOS), to determine the binding affinity based on their interactions. The docking results of CT revealed that, among the targets, NOS had a better binding energy of -6.4 Kcal/mol. NOS showed good hydrophobic interactions: TYR A, 347; VAL A, 352; PRO A, 350; TYR A, 373 amino acids. Interactions with IL-6, TNF-α, and IL-12 resulted in lower binding affinities of -3.7, -3.9 and -3.1 Kcal/mol. Based on molecular dynamics simulations of 100 ns, the binding affinity of CT (-66.782 ± 7.309 kJ/mol) was well complemented, and NOS stability at the docked site was confirmed. In in vivo studies, cerebral stroke was induced by occlusion of the bilateral common carotid arteries for 30 min and reperfusion for 4 h. CT treatment protected the brain by decreasing cerebral infarction size, increasing GSH(p < 0.001***), decreasing MPO (p < 0.001***), MDA (p < 0.001***), NO production (p < 0.01**), and AChE (p < 0.001***) compared to stroke rats. Histopathological examination revealed that CT treatment reduced the severity of cerebral damage. The investigation concluded that CT strongly binds to NOS, as observed in molecular docking and dynamic simulation studies, which are involved in nitric oxide production, leading to cerebral damage, and CT treatment reduces NO production and oxidative stress parameters, and increases antioxidants via inhibition of NOS function.Communicated by Ramaswamy H. Sarma.

Unveiling the ESR1 Conformational Stability and Screening Potent Inhibitors for Breast Cancer Treatment

BACKGROUND

The current study recognizes the significance of estrogen receptor alpha (ERα) as a member of the nuclear receptor protein family, which holds a central role in the pathophysiology of breast cancer. ERα serves as a valuable prognostic marker, with its established relevance in predicting disease outcomes and treatment responses.

METHODS

In this study, computational methods are utilized to search for suitable drug-like compounds that demonstrate analogous ligand binding kinetics to ERα.

RESULTS

Docking-based simulation screened out the top 5 compounds - ZINC13377936, NCI35753, ZINC35465238, ZINC14726791, and NCI663569 against the targeted protein. Further, their dynamics studies reveal that the compounds ZINC13377936 and NCI35753 exhibit the highest binding stability and affinity.

CONCLUSION

Anticipating the competitive inhibition of ERα protein expression in breast cancer, we envision that both ZINC13377936 and NCI35753 compounds hold substantial promise as potential therapeutic agents. These candidates warrant thorough consideration for rigorous In vitro and In vivo evaluations within the context of clinical trials. The findings from this current investigation carry significant implications for the advancement of future diagnostic and therapeutic approaches for breast cancer.

Enhancing gel behavior of yellow croaker surimi by fruit extracts: Physicochemical properties and molecular mechanism

The aim of this study was to investigate the effects of grape seed extract (GSE), acerola cherry extract (ACE), and blueberry extract (BBE) on the physicochemical properties and structure of the yellow croaker surimi gel. In addition, molecular docking and molecular dynamics (MD) simulation were utilized to study the binding mechanism of yellow croaker's fibrillin and fruit extracts. Surimi gel with 1.5% GSE, ACE, and BBE had the highest water holding capacity, hardness, chewability, cohesion, breaking force, breaking distance, gel strength, and densest 3D network structure, according to the experiment's findings. Nevertheless, the cross-linking of proteins in surimi was blocked with the further increase of fruit extract (1.5%-2.0%), and the existing network of surimi was weakened or even destroyed. Three fruit extracts had little effect on the secondary structure of the surimi gel. Besides, hydrophobic and disulfide bonds are the main chemical bonds of croaker surimi. Molecular docking showed that B-type procyanidine (BP) interacted with ASN-183, SER-571, ASP-525, ARG-350, LYS-188, GLU-349, CYS-353, and other active amino acids in croaker protein. Moreover, it can form strong hydrogen bond interaction with ASN-183, SER-571, ASP-525, and ARG-350 at the active sites of protein. The BP-Larimichthys crocea protein system's MD simulation was carried out, and calculations for the simulation's root mean square deviation, root mean square fluctuation, radius of gyration, solvent accessible surface area, and hydrogen bonds were made. It was found that these indices can demonstrate that the BP binding contributes to the stability of the yellow croaker structure.

In Silico molecular docking and dynamic analysis of natural compounds against major non-structural proteins of SARS-COV-2

COVID-19 has infected millions and significantly affected the global economy and healthcare systems. Despite continuous lockdowns, symptomatic management with currently available medications, and numerous vaccination drives, it is still far more difficult to control. Against COVID-19 infection, the pressure to develop vaccines and drugs has led to using some currently available medications like remdesivir, azithromycin, hydroxychloroquine and ritonavir. Understanding the importance and potential of harmless molecules to tackle SARS-COV-2, we designed the present study to identify potential natural phytocompounds. In the present study, we docked natural compounds and standard drugs against SARS-COV-2 proteins: papain-like protease, main protease and helicase. ADME/T and ProTox-II analyses were used to determine the toxicity of phytocompounds and drugs. The docking analysis revealed that podophyllotoxin gave the highest binding affinity scores of -8.1, -7.1 and -7.4 kcal/mol against PLpro, Mpro and helicase, respectively. Among the control drugs, doxycycline hydrochloride showed the highest binding affinity of -10.5, -8.4 and -8.8 kcal/mol against PLpro, Mpro and helicase. The results of this study revealed that podophyllotoxin and doxycycline hydrochloride could be promising inhibitors against SARS-Cov-2. Molecular dynamic simulations were executed for the best docked (PLpro-podophyllotoxin) complex, and the results displayed stable conformation and convergence. Energy plot results predicted a global minima average energy of -95 kcal/mol and indicated podophyllotoxin's role in stabilizing protein and making it compact and complex. FarPPI server used MM/GBSA approach to determine free binding affinity, and helicase-gallic acid complex showed the highest affinity, respectively. Therefore, it can be concluded that there is still a need for in vitro and in vivo studies to support further and validate these findings and validate these findings.Communicated by Ramaswamy H. Sarma.

Marine drugs as putative inhibitors against non-structural proteins of SARS-CoV-2: an in silico study

INTRODUCTION

Coronavirus disease 2019 (COVID-19) is an unprecedented pandemic, threatening human health worldwide. The need to produce novel small-molecule inhibitors against the ongoing pandemic has resulted in the use of drugs such as chloroquine, azithromycin, dexamethasone, favipiravir, ribavirin, remdesivir and azithromycin. Moreover, the reports of the clinical trials of these drugs proved to produce detrimental effects on patients with side effects like nephrotoxicity, retinopathy, cardiotoxicity and cardiomyopathy. Recognizing the need for effective and non-harmful therapeutic candidates to combat COVID-19, we aimed to develop promising drugs against SARS-COV-2.

DISCUSSION

In the current investigation, high-throughput virtual screening was performed using the Comprehensive Marine Natural Products Database against five non-structural proteins: Nsp3, Nsp5, Nsp12, Nsp13 and Nsp15. Furthermore, standard precision (SP) docking, extra precision (XP) docking, binding free energy calculation and absorption, distribution, metabolism, excretion and toxicity studies were performed using the Schrӧdinger suite. The top-ranked 5 hits obtained by computational studies exhibited to possess a greater binding affinity with the selected non-structural proteins. Amongst the five hits, CMNPD5804, CMNPD20924 and CMNPD1598 hits were utilized to design a novel molecule (D) that has the capability of interacting with all the key residues in the pocket of the selected non-structural proteins. Furthermore, 200 ns of molecular dynamics simulation studies provided insight into the binding modes of D within the catalytic pocket of selected proteins.

CONCLUSION

Hence, it is concluded that compound D could be a promising inhibitor against these non-structural proteins. Nevertheless, there is still a need to conduct in vitro and in vivo studies to support our findings.

Insights on the interaction of SARS-CoV-2 variant B.1.617.2 with antibody CR3022 and analysis of antibody resistance

BACKGROUND

The existence of mutated Delta (B.1.617.2) variants of SARS-CoV-2 causes rapid transmissibility, increase in virulence, and decrease in the effectiveness of public health. Majority of mutations are seen in the surface spike, and they are considered as antigenicity and immunogenicity of the virus. Hence, finding suitable cross antibody or natural antibody and understanding its biomolecular recognition for neutralizing surface spike are crucial for developing many clinically approved COVID-19 vaccines. Here, we aim to design SARS-CoV-2 variant and hence, to understand its mechanism, binding affinity and neutralization potential with several antibodies.

RESULTS

In this study, we modelled six feasible spike protein (S1) configurations for Delta SARS-CoV-2 (B.1.617.2) and identified the best structure to interact with human antibodies. Initially, the impact of mutations at the receptor-binding domain (RBD) of B.1.617.2 was tested, and it is found that all mutations increase the stability of proteins (ΔΔG) and decrease the entropies. An exceptional case is noted for the mutation of G614D variant for which the vibration entropy change is found to be within the range of 0.133-0.004 kcal/mol/K. Temperature-dependent free energy change values (ΔG) for wild type is found to be - 0.1 kcal/mol, whereas all other cases exhibit values within the range of - 5.1 to - 5.5 kcal/mol. Mutation on spike increases the interaction with the glycoprotein antibody CR3022 and the binding affinity (CLUSpro energy =  - 99.7 kcal/mol). The docked Delta variant with the following antibodies, etesevimab, bebtelovimab, BD-368-2, imdevimab, bamlanivimab, and casirivimab, exhibit a substantially decreased docking score (- 61.7 to - 112.0 kcal/mol) and the disappearance of several hydrogen bond interactions.

CONCLUSION

Characterization of antibody resistance for Delta variant with respect to the wild type gives understanding regarding why Delta variant endures the resistance boosted through several trademark vaccines. Several interactions with CR3022 have appeared compared to Wild for Delta variant, and hence, it is suggested that modification on the CR3022 antibody could further improve for the prevention of viral spread. Antibody resistance decreased significantly due to numerous hydrogen bond interactions which clearly indicate that these marketed/launched vaccines (etesevimab) will be effective for Delta variants.

Identifying novel and potent inhibitors of EGFR protein for the drug development against the breast cancer

The epidermal growth factor receptor (EGFR) has been shown to be extremely important in numerous signaling pathways, particularly those involved in cancer progression. Many therapeutic inhibitors, consisting of both small molecules and monoclonal antibodies, have been developed to target inflammatory, triple-negative and metastatic breast cancer. With the emergence of resistance in breast cancer treatment strategies, there is a need to develop novel drug targets that not only overcome resistance, but also exhibit low toxicity and high specificity. The work presented here focuses on the identification of new inhibitors against the EGFR protein using combined computational approaches. Using a comprehensive machine learning-based virtual screening approach complemented by other computational approaches, we identified six new molecules from the ZINC database. The gold docking score of these six novel molecules is 125.95, 125.38, 123.13, 119.71, 115.64 and 113.73, respectively, while the gold score of the control group is 120.74. In addition, we also analyzed the FEC value of these compounds and found that the values of compounds 1, 2, 3 and 4 (-61.82, -63.98, -67.98 and -63.32, respectively) were higher are than those of the control group (-61.05). Furthermore, these molecules showed highly stable RMSD plots and good interaction of hydrogen bonds. The identified inhibitors provided interesting insights for understanding the electronic, hydrophobic, steric and structural requirements for EGFR inhibitory activity. Distinguishing these novel molecules could lead to the development of new drugs useful in treating breast cancer.Communicated by Ramaswamy H. Sarma.

Discovery of novel VEGFR2-TK inhibitors by phthalimide pharmacophore based virtual screening, molecular docking, MD simulation and DFT

Currently, numerous potent chemotherapeutic agents are available in the market but most of them show poor pharmacokinetics, lethal effects and drug resistance during their enduring use. The increased cancer cases, deaths and need of better treatment stimulates us to give newer lifesaving anticancer drugs. The phthalimide derivatives are structurally diverse and exert potential anticancer activity. In this regard, the 3D QSAR Pharmacophore model was developed and validated using fifty-eight phthalimide derivatives. The validation parameters corroborated the reliability and statistical robustness of CEASER Hypo 1. Three databases-NCI Open, Drug Bank, and Asinex were submitted to ADMET and drug-like filtering; 117893 drug-like compounds were mapped on CEASER Hypo 1; and 362 hits with IC50 <1 µM were discovered. These hits were docked on VEGFR2-TK, and in the form of results fifteen hits exhibited greater affinity than sorafenib. The top lead ASN 03206926 was subjected for MD simulation (100 ns) and RMSD, Rg, RMSF, number of hydrogen bonds, and SASA verified that the complex was stable, rigid and highly compact. Results demonstrated GLU885, PHE918, CYS919, LYS920, HIS1026, CYS1045, ASP1046 are the essential residues for favourable interactions. The binding free energy calculations support the affinity and stability revealed by docking and MD simulation. The DFT calculations, negative binding energy and lower HOMO-LUMO band gap revealed that the process is spontaneous and ASN 03206926 is very reactive. Following extensive analysis we suggest that the ASN 03206926 might be employed as a new VEGFR2-TK inhibitor for the treatment of breast and VEGFR2-TK associated cancers.Communicated by Ramaswamy H. Sarma.

Bioactive compounds as potential angiotensin-converting enzyme II inhibitors against COVID-19: a scoping review

Objective and design

The current study aimed to summarize the evidence of compounds contained in plant species with the ability to block the angiotensin-converting enzyme 2 (ACE-II), through a scoping review.

Methods

PubMed and Scopus electronic databases were used for the systematic search and a manual search was performed

Results

Studies included were characterized as in silico. Among the 200 studies retrieved, 139 studies listed after the exclusion of duplicates and 74 were included for the full read. Among them, 32 studies were considered eligible for the qualitative synthesis. The most evaluated class of secondary metabolites was flavonoids with quercetin and curcumin as most actives substances and terpenes (isothymol, limonin, curcumenol, anabsinthin, and artemisinin). Other classes that were also evaluated were alkaloid, saponin, quinone, substances found in essential oils, and primary metabolites as the aminoacid l-tyrosine and the lipidic compound 2-monolinolenin.

Conclusion

This review suggests the most active substance from each class of metabolites, which presented the strongest affinity to the ACE-II receptor, what contributes as a basis for choosing compounds and directing the further experimental and clinical investigation on the applications these compounds in biotechnological and health processes as in COVID-19 pandemic.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00011-022-01642-7.

Review of Electrostatic Force Calculation Methods and Their Acceleration in Molecular Dynamics Packages Using Graphics Processors

Molecular dynamics (MD) simulations probe the conformational repertoire of macromolecular systems using Newtonian dynamic equations. The time scales of MD simulations allow the exploration of biologically relevant phenomena and can elucidate spatial and temporal properties of the building blocks of life, such as deoxyribonucleic acid (DNA) and protein, across microsecond (μs) time scales using femtosecond (fs) time steps. A principal bottleneck toward extending MD calculations to larger time scales is the long-range electrostatic force measuring component of the naive nonbonded force computation algorithm, which scales with a complexity of (N, number of atoms). In this review, we present various methods to determine electrostatic interactions in often-used open-source MD packages as well as the implementation details that facilitate acceleration of the electrostatic interaction calculation.

Molecular dynamics and docking studies on potentially active natural phytochemicals for targeting SARS-CoV-2 main protease

In the present study, we screened eighty seven novel phytochemical compounds from four popular herbs, such as, Aegle Marmelos, Coleus Amboinicus, Aerva Lanata and Biophytum Sensitivum and identified the best three for targeting the main protease (M^pro) receptor of SARS-CoV-2. After categorizing all the phytochemicals based upon LibDock scores and hydrogen bonding interactions, the top ranked 26 compounds were further subjected for detailed Molecular dynamics (MD) study. From these screening we identified that Aegelinosides B leads the list with a high LibDock value of 142.50 (binding energy: -8.54 kcal/mol), which is better than several popular reference compounds namely, Tipranavir (LibDock score, 141.50), Saquinavir (125.34), Zopicole (122.9), Pirenepine (122.70), (115.37), Metixene (109.18), Oxiconazole Pimozide (138.00) and Rimonabant (91.88). Detailed analysis for structural stability (RMSD), Cα fluctuations (RMSF), intermolecular hydrogen bond interactions, effect of solvent accessibility (SASA) and compactness (Rg) factors were performed for the best six compounds and it is found that they are very stable and exhibit folding behavior. Apart from the docking and MD tests, through further drug-likeness and toxicity tests, three compounds, such as, Aegelinosides B, Epicatechin, and Feruloyltyramine (LibDock scores, respectively, 142.50, 124.33 and 129.06) can be suggested for fighting SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Targeting SARS-CoV-2 endoribonuclease: a structure-based virtual screening supported by in vitro analysis

Researchers are focused on discovering compounds that can interfere with the COVID-19 life cycle. One of the important non-structural proteins is endoribonuclease since it is responsible for processing viral RNA to evade detection of the host defense system. This work investigates a hierarchical structure-based virtual screening approach targeting NSP15. Different filtering approaches to predict the interactions of the compounds have been included in this study. Using a deep learning technique, we screened 823,821 compounds from five different databases (ZINC15, NCI, Drug Bank, Maybridge, and NCI Diversity set III). Subsequently, two docking protocols (extra precision and induced fit) were used to assess the binding affinity of the compounds, followed by molecular dynamic simulation supported by the MM-GBSA free binding energy. Interestingly, one compound (ZINC000104379474) from the ZINC15 database has been found to have a good binding affinity of − 7.68 kcal/Mol. The VERO-E6 cell line was used to investigate its therapeutic effect in vitro. Half-maximal cytotoxic concentration and Inhibitory concentration 50 were determined to be 0.9 mg/ml and 0.01 mg/ml, respectively; therefore, the selectivity index is 90. In conclusion, ZINC000104379474 was shown to be a good hit for targeting the virus that needs further investigations in vivo to be a drug candidate.

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.

Implication of in silico studies in the search for novel inhibitors against SARS-CoV-2

Corona Virus Disease-19 (COVID-19) is a pandemic disease mainly caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It had spread from Wuhan, China, in late 2019 and spread over 222 countries and territories all over the world. Earlier, at the very beginning of COVID-19 infection, there were no approved medicines or vaccines for combating this disease, which adversely affected a lot of individuals worldwide. Although frequent mutation leads to the generation of more deadly variants of SARS-CoV-2, researchers have developed several highly effective vaccines that were approved for emergency use by the World Health Organization (WHO), such as mRNA-1273 by Moderna, BNT162b2 by Pfizer/BioNTech, Ad26.COV2.S by Janssen, AZD1222 by Oxford/AstraZeneca, Covishield by the Serum Institute of India, BBIBP-CorV by Sinopharm, coronaVac by Sinovac, and Covaxin by Bharat Biotech, and the first US Food and Drug Administration-approved antiviral drug Veklury (remdesivir) for the treatment of COVID-19. Several waves of COVID-19 have already occurred worldwide, and good-quality vaccines and medicines should be available for ongoing as well as upcoming waves of the pandemic. Therefore, in silico studies have become an excellent tool for identifying possible ligands that could lead to the development of safer medicines or vaccines. Various phytoconstituents from plants and herbs with antiviral properties are studied further to obtain inhibitors of SARS-CoV-2. In silico screening of various molecular databases like PubChem, ZINC, Asinex Biol-Design Library, and so on has been performed extensively for finding effective ligands against targets. Herein, in silico studies carried out by various researchers are summarized so that one can easily find the best molecule for further in vitro and in vivo studies.

Repurposing FDA-approved Drugs Targeting SARS-CoV2 3CLpro: a study by applying Virtual Screening, Molecular Dynamics, MM-PBSA Calculations and Covalent Docking

Background:

Since the end of 2019, the etiologic agent SAR-CoV-2 responsible for one of the most significant epidemics in history has caused severe global economic, social, and health damages. The drug repurposing approach and application of Structure-based Drug Discovery (SBDD) using in silico techniques are increasingly frequent, leading to the identification of several molecules that may represent promising potential.

Method:

In this context, here we use in silico methods of virtual screening (VS), pharmacophore modeling (PM), and fragment-based drug design (FBDD), in addition to molecular dynamics (MD), molecular mechanics/Poisson-Boltzmann surface area (MM -PBSA) calculations, and covalent docking (CD) for the identification of potential treatments against SARS-CoV-2. We initially validated the docking protocol followed by VS in 1,613 FDA-approved drugs obtained from the ZINC database. Thus, we identified 15 top hits, of which three of them were selected for further simulations. In parallel, for the compounds with a fit score value ≤ of 30, we performed the FBDD protocol, where we designed 12 compounds

Result:

By applying a PM protocol in the ZINC database, we identified three promising drug candidates. Then, the 9 top hits were evaluated in simulations of MD, MM-PBSA, and CD. Subsequently, MD showed that all identified hits showed stability at the active site without significant changes in the protein's structural integrity, as evidenced by the RMSD, RMSF, Rg, SASA graphics. They also showed interactions with the catalytic dyad (His41 and Cys145) and other essential residues for activity (Glu166 and Gln189) and high affinity for MM-PBSA, with possible covalent inhibition mechanism.

Conclution:

Finally, our protocol helped identify potential compounds wherein ZINC896717 (Zafirlukast), ZINC1546066 (Erlotinib), and ZINC1554274 (Rilpivirine) were more promising and could be explored in vitro, in vivo, and clinical trials to prove their potential as antiviral agents.

Targeting autophagy with natural products to prevent SARS-CoV-2 infection

Autophagy is a catabolic process that maintains internal homeostasis and energy balance through the lysosomal degradation of redundant or damaged cellular components. During virus infection, autophagy is triggered both in parenchymal and in immune cells with different finalistic objectives: in parenchymal cells, the goal is to destroy the virion particle while in macrophages and dendritic cells the goal is to expose virion-derived fragments for priming the lymphocytes and initiate the immune response. However, some viruses have developed a strategy to subvert the autophagy machinery to escape the destructive destiny and instead exploit it for virion assembly and exocytosis. Coronaviruses (like SARS-CoV-2) possess such ability. The autophagy process requires a set of proteins that constitute the core machinery and is controlled by several signaling pathways. Here, we report on natural products capable of interfering with SARS-CoV-2 cellular infection and replication through their action on autophagy. The present study provides support to the use of such natural products as adjuvant therapeutics for the management of COVID-19 pandemic to prevent the virus infection and replication, and so mitigating the progression of the disease.

In Silico Target Analysis of Treatment for COVID-19 Using Huang-Lian-Shang-Qing-Wan, a Traditional Chinese Medicine Formula

Due to the significantly negative impact of the coronavirus (CoV) disease (COVID-19) pandemic on the health of the community and the economy, it remains urgent and necessary to develop a safe and effective treatment method for COVID-19. Huang-Lian-Shang-Qing-Wan (HLSQW) is a herbal formula of traditional Chinese medicine (TCM) that has been applied extensively for treating “wind-heat-associated” symptoms in the upper parts of the body. The objective of the present in silico study was to investigate the potential effects of HLSQW in the context of severe acute respiratory syndrome (SARS)-CoV-2 infection. We analyzed the possible interactions between bioactive compounds within HLSQW on targets that may confer antiviral activity using network pharmacology and pharmacophore-based screening. HLSQW was found to potentially target a number of pathways and the expression of various genes to regulate cell physiology and, consequently, the anti-viral effects against SARS-CoV-2. Bioactive compounds contained within HLSQW may exert combined effects to reduce the production of proinflammatory factors, which may trigger the “cytokine storm” in patients with severe COVID-19. Results from molecular modeling suggested that the bioactive HLSQW components puerarin, baicalin, and daidzin exhibit high binding affinity to the active site of 3-chymotrypsin-like cysteine protease (3CLpro) to form stable ligand-protein complexes, thereby suppressing SARS-CoV-2 replication. In addition, our results also demonstrated protective effects of the HLSQW extract against cell injury induced by the proinflammatory cytokines tumor necrosis factor-α, interleukin (IL)-1β, and IL-6, against reactive oxygen species production and nuclear factor-κB activity in normal human lung cells in vitro. To conclude, HLSQW is a potential TCM remedy that warrants further study with the aim of developing an effective treatment for COVID-19 in the future.

Novel Molecules derived from 3-O-(6-galloylglucoside) inhibit Main Protease of SARS-CoV 2 In Silico

The ongoing pandemic caused by the severe acute respiratory syndrome 2 (SARS-CoV 2) has led to more than 168 million confirmed cases with 3.5 million deaths as at 28th May, 2021 across 218 countries. The virus has a cysteine protease called main protease (Mpro) which is significant to it life cycle, tagged as a suitable target for novel antivirals. In this computer-assisted study, we designed 100 novel molecules through an artificial neural network-driven platform called LigDream (https://playmolecule.org/LigDream/) using 3-O-(6-galloylglucoside) as parent molecule for design. Druglikeness screening of the molecules through five (5) different rules was carried out, followed by a virtual screening of those molecules without a single violation of the druglike rules using AutoDock Vina against Mpro. The in silico pharmacokinetic features were predicted and finally, quantum mechanics/molecular mechanics (QM/MM) study was carried out using Molecular Orbital Package 2016 (MOPAC2016) on the overall hit compound with controls to determine the stability and reactivity of the lead molecule. The findings showed that eight (8) novel molecules violated none of the druglikeness rules of which three (3) novel molecules (C33, C35 and C54) showed the utmost binding affinity of −8.3 kcal/mol against Mpro; C33 showed a good in silico pharmacokinetic features with acceptable level of stability and reactively better than our controls based on the quantum chemical descriptors analysis. However, there is an urgent need to carry out more research on these novel molecules for the fight against the disease.

Natural Compounds Activities against SARS-CoV-2 Mpro through Bioinformatics Approaches for Development of Antivirus Candidates

Coronavirus infection (COVID-19) caused by SARS-CoV-2 appears as a pandemic that has spread to almost all countries in the world. Antiviral therapy using natural compounds is one alternative approach to overcome this infectious disease. The therapeutic mechanism is proven effective against the main protease (Mpro) of SARS-CoV-2. This research aims to perform bioinformatics studies, including ligand-docking simulations and protein-protein docking simulations, to identify, evaluate, and explore five compounds' activity on SARS-CoV-2 Mpro and their effects against Angiotensin-Converting Enzyme 2 (ACE-2). Protein-ligand docking simulations show kaempferol, flavonol, and their glycosides (Afzelin and Juglanin) and other flavonoids (Quercetin, Naringenin, and Genistein) have a high affinity towards SARS-CoV-2 Mpro. These results were then confirmed using protein-protein docking simulations to observe the ability of five compounds to prevent the attachment of ACE-2 to the active site. Based on the results of the bioinformatics studies, Quercetin has the best affinity, with a binding free energy value of −33.18 kJ/mol. The five compounds are predicted to be able to interact strongly with SARS-CoV-2. The results in this research are useful for further studies in the development of novel anti-infective drugs for COVID-19 that target SARS-CoV-2 Mpro.

Interaction of selected terpenoids with two SARS-CoV-2 key therapeutic targets: An in silico study through molecular docking and dynamics simulations

The outbreak of COVID-19 disease caused by SARS-CoV-2, along with the lack of targeted medicaments, forced the scientific world to search for new antiviral formulations. In the current emergent situation, drug repurposing of well-known traditional and/or approved drugs could be the most effective strategy. Herein, through computational approaches, we aimed to screen 14 natural compounds from limonoids and terpenoids class for their ability to inhibit the key therapeutic target proteins of SARS-CoV-2. Among these, some limonoids, namely deacetylnomilin, ichangin and nomilin, and the terpenoid β-amyrin provided good interaction energies with SARS-CoV-2 3CL hydrolase (Mpro) in molecular dynamic simulation. Interestingly, deacetylnomilin and ichangin showed direct interaction with the catalytic dyad of the enzyme so supporting their potential role in preventing SARS-CoV-2 replication and growth. On the contrary, despite the good affinity with the spike protein RBD site, all the selected phytochemicals lose contact with the amino acid residues over the course of 120ns-long molecular dynamics simulations therefore suggesting they scarcely can interfere in SARS-CoV-2 binding to the ACE2 receptor. The in silico analyses of docking score and binding energies, along with predicted pharmacokinetic profiles, indicate that these triterpenoids might have potential as inhibitors of SARS-CoV-2 Mpro, recommending further in vitro and in vivo investigations for a complete understanding and confirmation of their inhibitory potential.

Screening of FDA-approved compound library identifies potential small-molecule inhibitors of SARS-CoV-2 non-structural proteins NSP1, NSP4, NSP6 and NSP13: molecular modeling and molecular dynamics studies

COVID-19, the current global pandemic has caused immense damage to human lives and the global economy. It is instigated by the SARS-CoV-2 virus and there is an immediate need for the identification of effective drugs against this deadly virus. SARS-CoV-2 genome codes for four structural proteins, sixteen non-structural proteins (NSPs) and several accessory proteins for its survival inside the host cells. In the present study, through in silico approaches, we aim to identify compounds that are effective against the four NSPs namely, NSP1, NSP4, NSP6 and NSP13 of SARS-CoV-2. The selection criteria of these four NSP proteins are they are least explored and potential targets. First, we have modeled the 3D structures of these proteins using homology modeling methods. Further, through molecular docking studies, we have screened the FDA-approved compounds against these modeled proteins and reported their docking scores. To gain dynamic insights, molecular dynamics studies have also been carried out for the best scored ligand against the NSPs. This study can further pave way for exposing more number of compounds against these proteins and enhance COVID-19 treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42485-021-00067-w.

Molecular Docking Study of Antibiotics, Anti-Inflammatory Drugs and [Eu(TTA)3⋅AMX] Complex as COVID-19 Biomarker through Interaction of Its Main Protease (Mpro)

Coronavirus Acute Respiratory Syndrome (SARS-CoV-2) is a very recent viral infection and has generated one of the world’s biggest problems of all time. There is no scientific evidence and clinical trials to indicate that possible therapies have shown results in suspected or confirmed patients other than the use of immunizations. Given the above, some substances are being studied to be applied to contain their spread and further damage. This work aims to perform an in silico study of amoxicillin, widely known as an antibiotic and used to prevent bacterial infections and a possible biomarker made from a complex with Europium (Eu). It was shown to have the ability to interact with the COVID-19 protein in Mpro protease as ligands. The study was conducted using the AutoDock Vina with Lamarckian genetic model algorithm (GA) combined with the estimation of grid-based energy in rigid and flexible conformation. Compared to affinity energy, amoxicillin presented [Formula: see text][Formula: see text]kcal/mol, which was better than its co-crystallized ligand in the study. The Europium complex, where its synthesis was also demonstrated in this work, presented energy of [Formula: see text][Formula: see text]kcal/mol with hydrogen bonds and possible color change when UV light was applied. For the choice of the best poses in the simulation, the neural network parameter, NNScore2, was used. It can be affirmed that this study is still introductory but promising both in the treatment and identification of the virus.

Potential Candidates against COVID-19 Targeting RNA-Dependent RNA Polymerase: A Comprehensive Review

Due to the extremely contagious nature of SARS-COV-2, it presents a significant threat to humans worldwide. A plethora of studies are going on all over the world to discover the drug to fight SARS-COV-2. One of the most promising targets is RNA-dependent RNA polymerase (RdRp), responsible for viral RNA replication in host cells. Since RdRp is a viral enzyme with no host cell homologs, it allows the development of selective SARS-COV-2 RdRp inhibitors. A variety of studies used in silico approaches for virtual screening, molecular docking, and repurposing of already existing drugs and phytochemicals against SARS-COV-2 RdRp. This review focuses on collating compounds possessing the potential to inhibit SARS-COV-2 RdRp based on in silico studies to give medicinal chemists food for thought so that the existing drugs can be repurposed for the control and treatment of ongoing COVID-19 pandemic after performing in vitro and in vivo experiments.

Impact of dimerization and N3 binding on molecular dynamics of SARS-CoV and SARS-CoV-2 main proteases

SARS-CoV-2 main protease is one of the major targets in drug development efforts against Covid-19. Even though several structures were reported to date, its dynamics is not understood well. In particular, impact of dimerization and ligand binding on the dynamics is an important issue to investigate. In this study, we performed molecular dynamics simulations of SARS-CoV and SARS-CoV-2 main proteases to investigate influence of dimerization on the dynamics by modeling monomeric and dimeric apo and holo forms. The dimerization causes an organization of the interdomain dynamics as well as some local structural changes. Moreover, we investigated impact of a peptide mimetic (N3) on the dynamics of SARS-CoV and SARS-CoV-2 Mpro. The ligand binding to the dimeric forms causes some key local changes at the dimer interface and it causes an allosteric interaction between the active sites of two protomers. Our results support the idea that only one protomer is active on SARS-CoV-2 due to this allosteric interaction. Additionally, we analyzed the molecular dynamics trajectories from graph theoretical perspective and found that the most influential residues – as measured by eigenvector centrality – are a group of residues in active site and dimeric interface of the protease. This study may form a bridge between what we know about the dynamics of SARS-CoV and SARS-CoV-2 Mpro. We think that enlightening allosteric communication of the active sites and the role of dimerization in SARS-CoV-2 Mpro can contribute to development of novel drugs against this global health problem as well as other similar proteases.

Communicated by Ramaswamy H. Sarma

Molecular docking studies of some selected gallic acid derivatives against five non-structural proteins of novel coronavirus

BACKGROUND

The World Health Organization has recently declared a new coronavirus disease (COVID-19) a pandemic and a global health emergency. The pressure to produce drugs and vaccines against the ongoing pandemic has resulted in the use of some drugs such as azithromycin, chloroquine (sulfate and phosphate), hydroxychloroquine, dexamethasone, favipiravir, remdesivir, ribavirin, ivermectin, and lopinavir/ritonavir. However, reports from some of the clinical trials with these drugs have proved detrimental on some COVID-19 infected patients with side effects more of which cardiomyopathy, cardiotoxicity, nephrotoxicity, macular retinopathy, and hepatotoxicity have been recently reported. Realizing the need for potent and harmless therapeutic compounds to combat COVID-19, we attempted in this study to find promising therapeutic compounds against the imminent threat of this virus. In this current study, 16 derivatives of gallic acid were docked against five selected non-structural proteins of SARS-COV-2 known to be a good target for finding small molecule inhibitors against the virus, namely, nsp3, nsp5, nsp12, nsp13, and nsp14. All the protein crystal structures and 3D structures of the small molecules (16 gallic acid derivatives and 3 control drugs) were retrieved from the Protein database (PDB) and PubChem server respectively. The compounds with lower binding energy than the control drugs were selected and subjected to pharmacokinetics screening using AdmetSAR server.

RESULTS

4-O-(6-galloylglucoside) gave binding energy values of - 8.4, - 6.8, - 8.9, - 9.1, and - 7.5 kcal/mol against Mpro, nsp3, nsp12, nsp13, and nsp15 respectively. Based on the ADMET profile, 4-O-(6-galloylglucoside) was found to be metabolized by the liver and has a very high plasma protein binding.

CONCLUSION

The result of this study revealed that 4-O-(6-galloylglucoside) could be a promising inhibitor against these SAR-Cov-2 proteins. However, there is still a need for further molecular dynamic simulation, in vivo and in vitro studies to support these findings.

Shuxuetong injection simultaneously ameliorates dexamethasone-driven vascular calcification and osteoporosis

Osteoporosis (OP) and vascular calcification (VC) share a number of common risk factors, pathophysiological mechanisms and etiology, which are known as bone-vascular axis. The present study aimed to investigate the effects of Shuxuetong (SXT) injection on VC and osteoporosis. A rat model of VC and osteoporosis was induced by dexamethasone (DEX; 1 mg/kg/day for 4 weeks, intramuscularly). Simultaneously, 0.6 ml/kg/day SXT was intraperitoneally injected. Compared with control rats, DEX induced significantly more VC and OP, as determined by increased calcium deposition and alkaline phosphatase activity in the aorta, disturbed structure, decreased levels of cortical bone thickness and trabecular bone area, and increased apoptosis in the bone. SXT injection ameliorated DEX-induced VC and osteoporosis; furthermore, the osteoblastic differentiation of vascular smooth muscle cells and the activation of endoplasmic reticulum stress in the DEX group was also prevented by SXT injection. Compared with control rats, protein expression levels of sclerostin, a crucial crosslink of the bone-vascular axis, were significantly increased in the aorta and bone of rats with DEX, which was also attenuated by SXT injection. Thus, the present study suggested that SXT injection could ameliorate both VC and OP, and may be mediated by the regulation of sclerostin. The present study may provide the basis a novel strategy for the prevention and treatment of VC and OP, which emerge as side-effects of glucocorticoids.

Identification of Persuasive Antiviral Natural Compounds for COVID-19 by Targeting Endoribonuclease NSP15: A Structural-Bioinformatics Approach

SARS-CoV-2 is a positive-stranded RNA virus that bundles its genomic material as messenger-sense RNA in infectious virions and replicates these genomes through RNA intermediates. Several virus-encoded nonstructural proteins play a key role during the viral life cycle. Endoribonuclease NSP15 is vital for the replication and life cycle of the virus, and is thus considered a compelling druggable target. Here, we performed a combination of multiscoring virtual screening and molecular docking of a library of 1624 natural compounds (Nuclei of Bioassays, Ecophysiology and Biosynthesis of Natural Products (NuBBE) database) on the active sites of NSP15 (PDB:6VWW). After sequential high-throughput screening by LibDock and GOLD, docking optimization by CDOCKER, and final scoring by calculating binding energies, top-ranked compounds NuBBE-1970 and NuBBE-242 were further investigated via an indepth molecular-docking and molecular-dynamics simulation of 60 ns, which revealed that the binding of these two compounds with active site residues of NSP15 was sufficiently strong and stable. The findings strongly suggest that further optimization and clinical investigations of these potent compounds may lead to effective SARS-CoV-2 treatment.

Impact of Early Pandemic Stage Mutations on Molecular Dynamics of SARS-CoV-2 Mpro

A new coronavirus (SARS-CoV-2) is a global threat to world health and economy. Its dimeric main protease (Mpro), which is required for the proteolytic cleavage of viral precursor proteins, is a good candidate for drug development owing to its conservation and the absence of a human homolog. Improving our understanding of Mpro behavior can accelerate the discovery of effective therapies to reduce mortality. All-atom molecular dynamics (MD) simulations (100 ns) of 50 mutant Mpro dimers obtained from filtered sequences from the GISAID database were analyzed using root-mean-square deviation, root-mean-square fluctuation, Rg, averaged betweenness centrality, and geometry calculations. The results showed that SARS-CoV-2 Mpro essentially behaves in a similar manner to its SAR-CoV homolog. However, we report the following new findings from the variants: (1) Residues GLY15, VAL157, and PRO184 have mutated more than once in SARS CoV-2; (2) the D48E variant has lead to a novel "TSEEMLN"" loop at the binding pocket; (3) inactive apo Mpro does not show signs of dissociation in 100 ns MD; (4) a non-canonical pose for PHE140 widens the substrate binding surface; (5) dual allosteric pockets coinciding with various stabilizing and functional components of the substrate binding pocket were found to display correlated compaction dynamics; (6) high betweenness centrality values for residues 17 and 128 in all Mpro samples suggest their high importance in dimer stability-one such consequence has been observed for the M17I mutation whereby one of the N-fingers was highly unstable. (7) Independent coarse-grained Monte Carlo simulations suggest a relationship between the rigidity/mutability and enzymatic function. Our entire approach combining database preparation, variant retrieval, homology modeling, dynamic residue network (DRN), relevant conformation retrieval from 1-D kernel density estimates from reaction coordinates to other existing approaches of structural analysis, and data visualization within the coronaviral Mpro is also novel and is applicable to other coronaviral proteins.