Promising inhibitors of main protease of novel corona virus to prevent the spread of COVID-19 using docking and molecular dynamics simulation

In Silico Structural and Functional Insight into the Binding Interactions of the Modeled Structure of Watermelon Urease with Urea

Urease (EC 3.5.1.5) is an amidohydrolase. This nickel-dependent metalloenzyme converts urea into NH3 and CO2. Despite their vital role in plants, the structure and function of watermelon (Citrullus lanatus) urease are unknown. We used third- and fourth-generation gene prediction algorithms to annotate the C. lanatus urease sequence in this investigation. The solved urease structure from Canavalia ensiformis (PDB ID: 4GY7) was utilized as a template model to identify the target 3-D model structure of the unknown C. lanatus urease for the first time. Cluretox, the C. lanatus urease intrinsic disordered area identical to Jaburetox, was also found. The C. lanatus urease structure was docked with urea to study atom interaction, amino acid interactions, and binding analyses in the urease-urea complex at 3.5 Å. This study found that amino acids His517, Gly548, Asp631, Ala634, Thr569, His543, Met635, His407, His490, and Ala438 of C. lanatus urease bind urea. To study the molecular basis and mode of action of C. lanatus urease, molecular dynamics simulation was performed and RMSD, RMSF, Rg, SAS, and H-bond analyses were done. The calculated binding free energy (ΔG) for the urea-urease complex at 100 ns using the MM/PBSA method is -7.61 kJ/mol. Understanding its catalytic principles helps scientists construct more efficient enzymes, tailor fertilization to boost agricultural output, and create sustainable waste management solutions.

Synthesis, characterization, DNA binding interactions, DFT calculations, and Covid-19 molecular docking of novel bioactive copper(I) complexes developed via unexpected reduction of azo-hydrazo ligands

In this work, we focused on the 3rd goal of the sustainable development plan: achieving good health and supporting well-being. Two redox-active hydrazo ligands namely, phenylcarbonohydrazonoyldicyanide (PCHD) and pyridin-4-ylcarbonohydrazonoyl-dicyanide (PyCHD), and their copper(I) complexes have been synthesized and characterized. The analytical data indicates the formation of copper(I) complexes despite starting with copper(II) perchlorate salt. The 1H-NMR and UV-visible spectral studies in DMSO revealed that PyCHD mainly exists in its azo-form, while PCHD exists in azo ↔ hydrazo equilibrium form, and confirmed the copper(I) oxidation state. XPS, spectral and electrochemistry data indicated the existence of copper(I) valence of both complexes. Cyclic voltammetry of PCHD and its copper(I) complex supported the reduction power of the ligand. The antimicrobial activity, cytotoxicity against the mammalian breast carcinoma cell line (MCF7), and DNA interaction of the compounds are investigated. All compounds showed high antimicrobial, and cytotoxic activities, relative to the standard drugs. Upon studying the wheat DNA binding, PCHD and PyCHD were found to bind through external contacts, while both [Cu(PCHD)2]ClO4.H2O and [Cu(PyCHD)2]ClO4.H2O were intercalated binding. In-silico molecular docking simulations against Estrogen Receptor Alpha Ligand Binding Domain (ID: 6CBZ) were performed on all produced compounds and confirmed the invitro experimentally best anticancer activity of [Cu(PyCHD)2]ClO4.H2O. The molecular docking tests against SARS-CoV-2 main protease (ID: 6 WTT) showed promising activity in the order of total binding energy values: [Cu(PCHD)2]ClO4.H2O > [Cu(PyCHD)2]ClO4.H2O > PCHD > PyCHD.

A molecular dynamics simulations analysis of repurposing drugs for COVID-19 using bioinformatics methods

A number of multidisciplinary methods have piqued the interest of researchers as means to accelerate and lower the cost of medication creation. The goal of this research was to find target proteins and then select a lead drug against SARS-CoV-2. The three-dimensional structure is taken from the RCSB PDB using its specific PDB ID 6lu7. Virtual screening based on pharmacophores is performed using Molecular Operating Environment software. We looked for a potent inhibitor in the FDA-approved database. For docking, AutoDock Vina uses Pyrx. The compound-target protein binding interactions were tested using BIOVIA Discovery Studio. The stability of protein and inhibitor complexes in a physiological setting was investigated using Desmond's Molecular Dynamics Simulation (MD simulation). According to our findings, we repurpose the FDA-approved drugs ZINC000169677008 and ZINC000169289767, which inhibit the activity of the virus's main protease (6lu7). The scientific community will gain from this finding, which might create new medicine. The novel repurposed chemicals were promising inhibitors with increased efficacy and fewer side effects.Communicated by Ramaswamy H. Sarma.

Interactions between carbon nanotubes and external structures of SARS-CoV-2 using molecular docking and molecular dynamics

Molecular modeling techniques are used to describe the process of interaction between nanotubes and the main structures of the Covid-19 virus: the envelope protein, the main protease, and the Spike glycoprotein. Molecular docking studies show that the ligands have interaction characteristics capable of adsorbing the structures. Molecular dynamics simulations provide information on the mean squared deviation of atomic positions ​​between 0.5 and 3.0 Å. The Gibbs free energy model and solvent accessible surface area approaches are used. Through the results obtained through molecular dynamics simulations, it is noted that the zig-zag nanotube prefers to interact with E-pro, M-pro, and S-gly, respectively. Molecular couplings and free energy showed that the S-gly active site residues strongly interact with zigzag, chiral, and armchair nanotubes, in this order. The interactions demonstrated in this manuscript may predict some promising candidates for virus antagonists, which may be confirmed through experimental approaches.

Repurposing FDA-approved drugs cetilistat, abiraterone, diiodohydroxyquinoline, bexarotene, and remdesivir as potential inhibitors against RNA dependent RNA polymerase of SARS-CoV-2: A comparative in silico perspective

Vaccines are undoubtedly the most effective means of combating viral diseases like COVID-19. However, there are risks associated with vaccination, such as incomplete viral deactivation or potential adverse effects in humans. However, designing and developing a panel of new drug molecules is always encouraged. In an emergency, drug repurposing research is one of the most potent and rapid options. RdRp (RNA-dependent RNA polymerase) has been discovered to play a pivotal role in viral replication. In this study, FDA-approved drugs bexarotene, diiodohydroxyquinoline, abiraterone, cetilistat, and remdesivir were repurposed against the RdRp by molecular modeling, docking, and dynamic simulation. Furthermore, to validate the potency of these drugs, we compared them to the antiviral remdesivir, which inhibits RdRp. Our finding indicated that the selected drugs have a high potential to be developed as RdRp inhibitors and, with further validation studies, could serve as potential drugs for the treatment of COVID-19.

Sesquiterpenoids isolated from the rhizome of Curcuma phaeocaulis Valeton: antitumor activity, in silico molecular docking and molecular dynamics study

This work provides a deep insight into new sesquiterpenoids isolated from Curcumae Rhizoma acting as potential antitumor activity inhibitors.

Molecular dynamics simulation approach for discovering potential inhibitors against SARS-CoV-2: A structural review

Since the commencement of the novel Coronavirus, the disease has quickly turned into a worldwide crisis so that there has been growing attention in discovering possible hit compounds for tackling this pandemic. Discovering standard treatment strategies is a serious challenge because little information is available about this emerged infectious virus. Regarding the high impact of time, applying computational procedures to choose promising drugs from a catalog of licensed medications provides a precious chance for combat against the life-threatening disorder of COVID-19. Molecular dynamics (MD) simulation is a promising approach for assessing the binding affinity of ligand-receptor as well as observing the conformational trajectory of docked complexes over time. Given that many computational studies are performed using MD along with the molecular docking on various candidates as antiviral inhibitors of COVID-19 protease, there is a demand to conduct a comprehensive review of the most important studies to reveal and compare the potential introduced agents that this study covers this defect. In this context, the present review intends to prepare an overview of these studies by considering RMSD, RMSF, radius of gyration, binding free energy, and Solvent-Accessible Surface Area (SASA) as effective parameters for evaluation. The outcomes will offer a road map for adjusting antiviral inhibitors, which can facilitate the selection and development of drug candidates for use in the medical therapy. Finally, the molecular modeling approaches rendered by this study may be valuable for future computational studies.

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.

Target prediction, computational identification, and network-based pharmacology of most potential phytoconstituent in medicinal leaves of Justicia adhatoda against SARS-CoV-2

The current global epidemic of the novel coronavirus (SARS-CoV-2) has been labeled a global public health emergency since it is causing substantial morbidity and mortality on daily basis. We need to identify an effective medication against SARS-CoV-2 because of its fast dissemination and re-emergence. This research is being carried out as part of a larger strategy to identify the most promising therapeutic targets using protein-protein interactions analysis. Mpro has been identified as one of the most important therapeutic targets. In this study, we did in-silico investigations to identify the target and further molecular docking, ADME, and toxicity prediction were done to assess the potential phyto-active antiviral compounds from Justicia adhatoda as powerful inhibitors of the Mpro of SARS-COV-2. We also investigated the capacity of these molecules to create stable interactions with the Mpro using 100 ns molecular dynamics simulation. The highest scoring compounds (taraxerol, friedelanol, anisotine, and adhatodine) were also found to exhibit excellent solubility and pharmacodynamic characteristics. We employed MMPBSA simulations to assess the stability of docked molecules in the Mpro binding site, revealing that the above compounds form the most stable complex with the Mpro. Network-based Pharmacology suggested that the selected compounds have various modes of action against SARS-CoV-2 that include immunoreaction enrichment, inflammatory reaction suppression, and more. These findings point to a promising class of drugs that should be investigated further in biochemical and cell-based studies to see their effectiveness against nCOVID-19.Communicated by Ramaswamy H. Sarma.

A foundational theoreticalAl12E12(E = N, P) adsorption and quinolone docking study: cage–quinolone pairs, optics and possible therapeutic and diagnostic applications

This combined Al₁₂E₁₂ (E = N, P) surface adsorption and docking study describes the new possibility of prospective potential probing(photophysical/optical) and therapy(medicinal/biochemical) with these adsorbent conjugates. DFT investigations were undertaken herein to help generate geometrical models and better understand the possible favorable adsorption energetics. We attempt to explain their adsorption behaviors and docking involving SARS-CoV-2 viruses (PDB)to assess their possible pharmaceutical potential against the pandemic virus (COVID-19). The adsorption behavior of 8-hydroxy-2-methylquinoline (MQ) and its halogenated derivatives, 5,7-diiodo-8-hydroxy-2-methylquinoline (MQI), 5,7-dichloro-8-hydroxy-2-methylquinoline (MQCl), and 5,7-dibromo-8-hydroxy-2-methylquinoline (MQBr), with aluminum-nitrogen (AlN), and aluminum-phosphorous (AlP) fullerene-like nanocages is reported. A decrease in the hardness of the nanoclusters when adsorbed with drug molecules resulted in an incrementally improved chemical softness (see e.g., Hard-Soft Acid Base theory) indicating that reactivity of the drug molecule in the resulting complex increases upon cluster chemical adsorption. The energy gap is found to be maximized for AlN-MQ and minimized for AlP-MQI; the reduced density gradient (RDG) iso-surfaces and AIM studies also corroborated this. Therefore, these two were found, respectively, to be the least and most electrically conductive of the species under study. We selected a simple medicinal building block (chelator)in addition to selecting the cluster based on previous literature reports. Important parameters such as gap energies and global indices were determined. We assessed NLO properties. The SARS-CoV-2 virus PDB docking data for 6VW1, 6VYO, 6WKQ, 7AD1, 7AOL, 7B3C, were enlisted as ligand targets for studies of docking (PatchDock Server) using the requisite PDB geometries (For the structure of 6VW1, kindly see reference, 2020; For the structure of 6VYO kindly see reference, 2020; For the structure of 6WKQ kindly see reference, 2020; For the structure of 7AD1 kindly see reference, 2021; For the structure of 7AOL kindly see reference, 2021; For the structure of 7B3C kindly see reference, 2021). Such findings indicate that the AlN-drug conjugation have inhibitory effect against these selected receptors.Communicated by Ramaswamy H. Sarma.

Pyrido[1,2-e]purine: Design and Synthesis of Appropriate Inhibitory Candidates against the Main Protease of COVID-19

A series of tricyclic and polycyclic pyrido[1,2-e]purine derivatives were designed and synthesized via a two-step, one-pot reaction of 2,4-dichloro-5-amino-6-methylpyrimidine with pyridine under reflux conditions. Various derivatives of pyrido[1,2-e]purine were also synthesized by substituting the chlorine atom with secondary amines. After careful physiochemical and pharmacokinetic predictions, the inhibitory effects of the synthesized compounds against the main protease of SARS-CoV-2 have been evaluated by molecular docking and molecular dynamics approaches. The in silico results revealed that among all of the studied compounds, the morpholine/piperidine-substituted pyrido[1,2-e]purine derivatives are the best candidates as effective inhibitors of SARS-CoV-2.

Molecular docking and dynamic simulations study for repurposing of multitarget coumarins against SARS-CoV-2 main protease, papain-like protease and RNA-dependent RNA polymerase

Proteases and RNA-Dependent RNA polymerase, major enzymes which are essential targets involved in the life and replication of SARS-CoV-2. This study aims at in silico examination of the potential ability of coumarins and their derivatives to inhibit the replication of SARS-Cov-2 through multiple targets, including the main protease, papain-like protease and RNA-Dependent RNA polymerase. Several coumarins as biologically active compounds were studied, including coumarin antibiotics and some naturally reported antiviral coumarins. Aminocoumarin antibiotics, especially coumermycin, showed a high potential to bind to the enzymes’ active site, causing possible inhibition and termination of viral life. They demonstrate the ability to bind to residues essential for triggering the crucial cascades within the viral cell. Molecular dynamics simulations for 50 ns supported these data pointing out the formation of rigid, stable Coumermycin/enzyme complexes. These findings strongly suggest the possible use of Coumermycin, Clorobiocin or Novobiocin in the fight against COVID-19, but biological evidence is still required to support such suggestions.

In Silico Evaluation of Binding of 2-Deoxy-D-Glucose with Mpro of nCoV to Combat COVID-19

COVID-19 has threatened the existence of humanity andthis infection occurs due to SARS-CoV-2 or novel coronavirus, was first reported in Wuhan, China. Therefore, there is a need to find a promising drug to cure the people suffering from the infection. The second wave of this viral infection was shaking the world in the first half of 2021. Drugs Controllers of India has allowed the emergency use of 2-deoxy-D-glucose (2DG) in 2021 for patients suffering from this viral infection. The potentiality of 2-deoxy-D-glucose to intervene in D-glucose metabolism exists and energy deprivation is an effective parameter to inhibit cancer cell development. Once 2DG arrives in the cells, it becomes phosphorylated to 2-deoxy-D-glucose-6-phosphate (2-DG6P), a charged molecule expressively captured inside the cells. On the other hand, 2DG lacks the ability to convert into fructose-6-phosphate, resulting in a hampering of the activity of both glucose-6-phosphate isomerase and hexokinase, and finally causing cell death. Hence, the potential and effectiveness of 2DG with the main protease (Mpro) of novel coronavirus (nCoV) should be investigated using the molecular docking and molecular dynamics (MD) simulations. The ability of 2DG to inhibit the Mpro of nCoV is compared with 2-deoxyglucose (2DAG), an acyclic molecule, and 2-deoxy-D-ribose (2DR). The binding energy of the molecules with the Mpro of nCoV is calculated using molecular docking and superimposed analysis data is obtained. The binding energy of 2DG, 2DR and 2DAG was −2.40, −2.22 and −2.88 kcal/mol respectively. Although the molecular docking does not provide reliable information, therefore, the binding affinity can be confirmed by molecular dynamics simulations. Various trajectories such as Rg, RMSD, RMSF, and hydrogen bonds are obtained from the molecular dynamics (MD) simulations. 2DG was found to be a better inhibitor than the 2DAG and 2DR based on the results obtained from the MD simulations at 300 K. Furthermore, temperature-dependent MD simulations of the Mpro of nCoV with promising 2DG was performed at 295, 310 and 315 K, and the effective binding with the Mpro of nCoV occurred at 295 K. With the use of DFT calculations, optimized geometry and localization of electron density of the frontier molecular orbitals were calculated.

Can polyoxometalates (POMs) prevent of coronavirus 2019-nCoV cell entry? Interaction of POMs with TMPRSS2 and spike receptor domain complexed with ACE2 (ACE2-RBD): Virtual screening approaches

The unexpected appearance and global spread of COVID-19 create significant difficulties for healthcare systems and present an unusual challenge for the fast discovery of medicines to combat this fatal disease. Screening metallodrugs libraries from the medicinal inorganic chemistry society may expand the studied ‘chemical space’ and improve the probability of discovering effective anti-COVID drugs, including polyoxometalates. POMs are an oxygen-rich family of inorganic cluster systems that have previously been tested for antiviral action against different types of viruses. Human angiotensin-converting enzyme 2 (ACE2), human transmembrane protease serine 2 (TMPRSS2), and the SARS-CoV-2 spike glycoprotein are required for host cell-mediated viral entrance. Targeting these proteins demonstrates potential possibilities for preventing infections and transmissions in the initial stage. As a result, POMs with known antiviral effects were investigated for this purpose using molecular docking and dynamic simulations. This research shows that POMs can prevent SARS CoV-2 from entering cells by blocking TMPRSS2, which SARS-CoV-2 uses for spike glycoprotein priming. They may also engage with ACE2 and the spike glycoprotein and disrupt their binding by blocking the active sites. We think that a thorough investigation of POMs as possible anti-COVID-19 drugs will provide significant opportunities.

Screening of Severe Acute Respiratory Syndrome Coronavirus 2 RNA-Dependent RNA Polymerase Inhibitors Using Computational Approach

The detrimental effect of coronavirus disease 2019 (COVID-19) pandemic has manifested itself as a global crisis. Currently, no specific treatment options are available for COVID-19, so therapeutic interventions to tackle the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection must be urgently established. Therefore, cohesive and multidimensional efforts are required to identify new therapies or investigate the efficacy of small molecules and existing drugs against SARS-CoV-2. Since the RNA-dependent RNA Polymerase (RdRP) of SARS-CoV-2 is a promising therapeutic target, this study addresses the identification of antiviral molecules that can specifically target SARS-CoV-2 RdRP. The computational approach of drug development was used to screen the antiviral molecules from two antiviral libraries (Life Chemicals [LC] and ASINEX) against RdRP. Here, we report six antiviral molecules (F3407-4105, F6523-2250, F6559-0746 from LC and BDG 33693278, BDG 33693315, LAS 34156196 from ASINEX), which show substantial interactions with key amino acid residues of the active site of SARS-CoV-2 RdRP and exhibit higher binding affinity (>7.5 kcalmol^-1) than Galidesivir, an Food and Drug Administration-approved inhibitor of the same. Further, molecular dynamics simulation and Molecular Mechanics Poisson-Boltzmann Surface Area results confirmed that identified molecules with RdRP formed higher stable RdRP-inhibitor(s) complex than RdRP-Galidesvir complex. Our findings suggest that these molecules could be potential inhibitors of SARS-CoV-2 RdRP. However, further in vitro and preclinical experiments would be required to validate these potential inhibitors of SARS-CoV-2 protein.

In silico identification of potential inhibitors against main protease of SARS-CoV-2 6LU7 from Andrographis panniculata via molecular docking, binding energy calculations and molecular dynamics simulation studies

Background

The ongoing global outbreak of new corona virus (SARS-CoV-2) has been recognized as global public health concern since it causes high morbidity and mortality every day. Due to the rapid spreading and re-emerging, we need to find a potent drug against SARS-CoV-2. Synthetic drugs, such as hydroxychloroquine, remdisivir have paid more attention and the effects of these drugs are still under investigation, due to their severe side effects. Therefore, the aim of the present study was performed to identify the potential inhibitor against main protease SARS-CoV-2 6LU7.

Objective

In this study, RO5, ADME properties, molecular dynamic simulations and free binding energy prediction were mainly investigated.

Results

The molecular docking study findings revealed that andrographolide had higher binding affinity among the selected natural diterpenoids compared to co-crystal native ligand inhibitor N3. The persistent inhibition of Ki for diterpenoids was analogous. Furthermore, the simulations of molecular dynamics and free binding energy findings have shown that andrographolide possesses a large amount of dynamic properties such as stability, flexibility and binding energy.

Conclusion

In conclusion, findings of the current study suggest that selected diterpenoids were predicted to be the significant phytonutrient-based inhibitor against SARS-CoV-2 6LU7 (M^pro). However, preclinical and clinical trials are needed for the further scientific validation before use.

Antiviral peptides against the main protease of SARS-CoV-2: A molecular docking and dynamics study

The recent coronavirus outbreak has changed the world's economy and health sectors due to the high mortality and transmission rates. Because the development of new effective vaccines or treatments against the virus can take time, an urgent need exists for the rapid development and design of new drug candidates to combat this pathogen. Here, we obtained antiviral peptides obtained from the data repository of antimicrobial peptides (DRAMP) and screened their predicted tertiary structures for the ability to inhibit the main protease of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using multiple combinatorial docking programs, including PatchDock, FireDock, and ClusPro. The four best peptides, DRAMP00877, DRAMP02333, DRAMP02669, and DRAMP03804, had binding energies of -1125.3, -1084.5, -1005.2, and -924.2 Kcal/mol, respectively, as determined using ClusPro, and binding energies of -55.37, -50.96, -49.25, -54.81 Kcal/mol, respectively, as determined using FireDock, which were better binding energy values than observed for other peptide molecules. These peptides were found to bind with the active cavity of the SARS-CoV-2 main protease; at Glu166, Cys145, Asn142, Phe140, and Met165, in addition to the substrate-binding sites, Domain 2 and Domain 3, whereas fewer interactions were observed with Domain 1. The docking studies were further confirmed by a molecular dynamics simulation study, in which several descriptors, including the root-mean-square difference (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), radius of gyration (Rg), and hydrogen bond formation, confirmed the stable nature of the peptide-main protease complexes. Toxicity and allergenicity studies confirmed the non-allergenic nature of the peptides. This present study suggests that these identified antiviral peptide molecules might inhibit the main protease of SARS-CoV-2, although further wet-lab experiments remain necessary to verify these findings.

Exploring the potential of novel phenolic compounds as potential therapeutic candidates against SARS-CoV-2, using quantum chemistry, molecular docking and dynamic studies

In the current study, the interaction of SARS-CoV-2 protein (A and B chains of nsp13) with different recently synthesized phenolic compounds (Sreenivasulu et al., Synthetic Communications, 2020, 112-122) has been studied. The interactions have been investigated by using molecular docking, quantum chemical and molecular dynamics simulations methods. The molecular structures of all the ligands are studied quantum chemically in terms of their optimized structures, 3-D orbital distributions, global chemical descriptors, molecular electrostatic potential plots and HOMO-LUMO orbital energies. All the ligands show reasonably good binding affinities with nsp-13 protein. The ligand L2 shows to have better binding affinities to Chain A and Chain B of nsp13 protein, which are -6.7 and -6.4 kcal/mol. The study of intermolecular interactions indicates that L2 shows different hydrophobic and hydrogen bond interactions with both chains. Furthermore, molecular dynamic simulations of the nsp13-L2 complex are obtained over a time scale of 60 ns, which indicates its stability and flexibility behavior as assessed in terms of its RMSD and RMSF graphs. The ADMET analysis also shows no violation of Lipinski rule (RO5) by studied phenolic compounds. We believe that the current findings will be further confirmed by in vitro and in vivo studies of these recent phenolic compounds for their potential as inhibitors for SARS-Co-V-2 virus.

The identification of novel inhibitors of human angiotensin-converting enzyme 2 and main protease of Sars-Cov-2: A combination of in silico methods for treatment of COVID-19

The angiotensin-converting enzyme 2 (ACE2) and main protease (MPro), are the putative drug candidates for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we performed 3D-QSAR pharmacophore modeling and screened 1,264,479 ligands gathered from Pubchem and Zinc databases. Following the calculation of the ADMET properties, molecular docking was carried out. Moreover, the de novo ligand design was performed. MD simulation was then applied to survey the behavior of the ligand-protein complexes. Furthermore, MMPBSA has utilized to re-estimate the binding affinities. Then, a free energy landscape was used to find the most stable conformation of the complexes. Finally, the hybrid QM-MM method was carried out for the precise calculation of the energies.

The Hypo1 pharmacophore model was selected as the best model. Our docking results indicate that the compounds ZINC12562757 and 112,260,215 were the best potential inhibitors of the ACE2 and MPro, respectively. Furthermore, the Evo_1 compound enjoys the highest docking energy among the designed de novo ligands. Results of RMSD, RMSF, H-bond, and DSSP analyses have demonstrated that the lead compounds preserve the stability of the complexes’ conformation during the MD simulation. MMPBSA data confirmed the molecular docking results. The results of QM-MM showed that Evo_1 has a stronger potential for specific inhibition of MPro, as compared to the 112,260,215 compound.

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

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

A computational approach for the screening of potential antiviral compounds against SARS-CoV-2 protease: Ionic liquid vs herbal and natural compounds

The current scenario across the globe shows unprecedented healthcare and an economic crisis due to the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Recently, the World Health Organization (WHO) has declared a pandemic stage worldwide because of the high mortality and morbidity rate caused by novel infection disease. There have been several clinical trials and identification underway to find a treatment of this novel virus. For the treatment of severe infection involves the blocking of the replication of its CoV-2 protein. Hydroxychloroquine and remdesivir has been used on an emergency basis for its treatment. The uncontrolled infection and increasing death rate underline the emergence to develop the antiviral drug. In our study, the blind docking of various classes of compounds including control antiviral drugs (abacavir, acyclovir, quinoline, hydroxyquinoline), antimicrobial drugs (levofloxacin, amoxicillin, cloxacin, ofloxacin), natural compounds (lycorine, saikosaponins, myricetin, amentaflavone), herbal compounds (silymarin, palmatine, curcumin, eugenin) available in Indian Ayurveda was done. Besides, we have also performed the blind docking of various ionic liquids (ILs) such as pyrrolidinium, piperidinium, pyridinium, imidazolium based ILs against CoV-2 protease as they have recently emerged as a potential antimicrobial agent. Further, the pharmacokinetic properties and cytotoxicity of the compounds were determined computationally. The docking results showed successful binding to the active site or near a crucial site. The present computational approach was found helpful to predict the best possible inhibitor of protease and may result in an effective therapeutic agent against COVID-19.

Characterization, biological evaluation and molecular docking of mulberry fruit pectin

Contemplating the exemplary benefits of pectin on human health, we precisely characterized and evaluated the antibacterial and anticancer activities from purified Mulberry Fruit Pectins (MFP). Here, we tested BR-2 and S-13 varieties of mulberry fruit pectins against six bacterial strains and two human cancer cell lines (HT-29 and Hep G-2), using MIC and an in vitro cell-based assay respectively. The BR-2 mulberry fruit pectin performs superior to S-13 by inhibiting strong bacterial growth (MIC = 500–1000 μg/mL) against tested bacterial strains and cytotoxic activities at the lowest concentration (10 µg/ml) against the Hep G-2 cell line. However, both tested drugs failed to exhibit cytotoxicity on the human colon cancer cell line (HT-29). Based on molecular interaction through docking, pectin binds effectively with the receptors (1e3g, 3t0c, 5czz, 6j7l, 6v40, 5ibs, 5zsy, and 6ggb) and proven to be a promising antimicrobial and anti-cancer agents. The pursuit of unexploited drugs from mulberry fruit pectin will potentially combat against bacterial and cancer diseases. Finally, future perspectives of MFP for the treatment of many chronic diseases will help immensely due to their therapeutic properties.

Role of heterocyclic compounds in SARS and SARS CoV-2 pandemic

Coronaviruses have led to severe emergencies in the world since the outbreak of SARS CoV in 2002, followed by MERS CoV in 2012. SARS CoV-2, the novel pandemic caused by coronaviruses that began in December 2019 in China has led to a total of 24,066,076 confirmed cases and a death toll of 823,572 as reported by World Health Organisation on 26 August 2020, spreading to 213 countries and territories. However, there are still no vaccines or medications available till date against SARS coronaviruses which is an urgent requirement to control the current pandemic like situations. Since many decades, heterocyclic scaffolds have been explored exhaustively for their anticancer, antimalarial, anti-inflammatory, antitubercular, antimicrobial, antidiabetic, antiviral and many more treatment capabilities. Therefore, through this review, we have tried to emphasize on the anticipated role of heterocyclic scaffolds in the design and discovery of the much-awaited anti-SARS CoV-2 therapy, by exploring the research articles depicting different heterocyclic moieties as targeting SARS, MERS and SARS CoV-2 coronaviruses. The heterocyclic motifs mentioned in the review can serve as crucial resources for the development of SARS coronaviruses treatment strategies.

Xanthene based hybrid analogues to inhibit protease of novel corona Virus: Molecular docking and ADMET studies

In December 2019, the SARS-CoV-2 was reported for the first time and the infected person is reported at Wuhan, China. Till date, about twenty four million people around the world are infected due to the SARS-CoV-2. The structure of this corona virus is new and different from other corona viruses. The genome has a positive sense single RNA strand and it is responsible for the encoding of the protein. The protease of the SARS-CoV-2 is responsible for the cleavage and therefore, it should be targeted to develop medicine. Till date, no medicine or vaccine is in the market to cure from the infection. Researchers around the world are working on the development of efficacious and safe vaccine/ drug to cure from the infection. Therefore, the authors used previously synthesized compounds, xanthene-triazole-chloroquinoline/ xanthene-chloroquinoline hybrids for the inhibition of the main protease of the SARS-CoV-2 via using computational tools, molecular docking and ADMET properties. COMD AP3 was found to be the best candidate from the library of the designed molecules. It has acceptable solubility along with the distribution and metabolism property. ADMET results corroborate the docking result towards the potency of COMP AP3.

In-silico prediction of novel drug-target complex of nsp3 of CHIKV through molecular dynamic simulation

Literature reported that nsp3 of CHIKV is an important target for the designing of drug as it involves in the replication, survival etc. Herein, about eighteen million molecules available in the ZINC database are filtered against nsp3 using RASPD. Top five hit drug molecules were then taken from the total screened molecules (6988) from ZINC database. Then, a one pot-three components reaction is designed to get the pyrazolophthalazine and its formation was studied using DFT method. Authors created a library of 200 compounds using the product obtained in the reaction and filtered against nsp3 of CHIKV based on docking using iGEMDOCK, a computational tool. Authors have studied the best molecules after applying the the Lipinski's rule of five and bioactive score. Further, the authors took the best compound i.e. CMPD178 and performed the MD simulations and tdMD simulations with nsp3 protease using AMBER18. MD trajectories were studied to collect the information about the nsp3 of CHIKV with and without screened compound and then, MM-GBSA calculations were performed to calculate change in binding free energies for the formation of complex. The aim of the work is to find the potential candidate as promising inhibitor against nsp3 of CHIKV.