key: cord-0904230-mb4tkde8
authors: Naik, Biswajit; Gupta, Nidhi; Ojha, Rupal; Singh, Satyendra; Prajapati, Vijay Kumar; Prusty, Dhaneswar
title: High throughput virtual screening reveals SARS-CoV-2 multi-target binding natural compounds to lead instant therapy for COVID-19 treatment
date: 2020-05-26
journal: Int J Biol Macromol
DOI: 10.1016/j.ijbiomac.2020.05.184
sha: 6e1f1c5423ab2f106a0ebfb0bc43c4c6a5afd7b2
doc_id: 904230
cord_uid: mb4tkde8

The present-day world is severely suffering from the recently emerged SARS-CoV-2. The lack of prescribed drugs for the deadly virus has stressed the likely need to identify novel inhibitors to alleviate and stop the pandemic. In the present high throughput virtual screening study, we used in silico techniques like receptor-ligand docking, Molecular dynamic (MD), and ADME properties to screen natural compounds. It has been documented that many natural compounds display antiviral activities, including anti–SARS-CoV effect. The present study deals with compounds of Natural Product Activity and Species Source (NPASS) database with known biological activity that probably impedes the activity of six essential enzymes of the virus. Promising drug-like compounds were identified, demonstrating better docking score and binding energy for each druggable targets. After an extensive screening analysis, three novel multi-target natural compounds were predicted to subdue the activity of three/more major drug targets simultaneously. Concerning the utility of natural compounds in the formulation of many therapies, we propose these compounds as excellent lead candidates for the development of therapeutic drugs against SARS-CoV-2.

Coronavirus helicase catalyses the processive separation of double-stranded DNA and RNA in a 5ꞌ-to-3ꞌ direction [24, 25] . Moreover, helicase (EC 3.6.4.12) inhibitors such as bananin and its derivatives have shown promising anti-cornonaviridae activity [26] . The nonstructural protein 15 have endoribonuclease (EC 3.1. 26 .3) activity that cleaves preferentially at uridine residues [27, 28] . A non-structural protein (nsp) 14 has also been shown to have exoribonuclease (ExoN) (EC 3.1.13.1) activity and involved in CoV replicative machinery.

The active site mutations of the protein revealed severe defects in CoV RNA synthesis [29] .

In the SARS-CoV replication study, it has been shown that AdoMet dependent methyltransferase inhibitors inhibit SARS-CoV replication [30] by targeting Nmethyltransferases (EC 2.1.1.35) of the virus [31] . Due to strictly virus-specific activity, the RNA-dependent RNA polymerase (RdRp) (EC 2.7.7.6) has been considered as a promising wide-spectrum drug target for antiviral drug development. Several studies discovered that inhibitors against RdRp could effectively intervene in the coronavirus lifecycle [32, 33] .

RNA viruses are unique pathogens in terms of exceptionally genetically variable. They accumulate mutations in their genome by employing viral reverse transcriptase that lacks a proofreading mechanism. This unique feature of RNA viruses makes it challenging to design active therapeutic agents. Most of the antiviral drugs in use are designed to specifically target single viral enzyme, which is essential for viral replication or invasion [34, 35] . However, the high rate of mutations in the viral drug targets has been accounted for the reduced susceptibility of currently available antiviral drugs [36] . A combination of drugs that have different molecular targets can be a better choice; however, some times, the combination therapy is not safe due to unwanted drug interactions [37] . Besides, drugs designed for multiple protein targets are extensively used for the treatment of both infectious and inherited diseases [38] [39] [40] [41] [42] . For the immediate drug requirement for SARS-CoV-2, biologically active drug-like molecules that target multiple viral enzymes of the viral replication cycle are highly wanted.

Natural compounds of plant-based origin have been studied as an exciting class of pharmacologically active molecules, some of them have an ancient history of antiviral activity [43] [44] [45] [46] [47] [48] [49] [50] . Extensive studies have been performed over the past decades to identify anti-CoV agents using natural products [51] . The saikosaponins (A, B2, C, and D), for example, exerts antiviral activity by interfering viral attachment and penetration, against HCoV-22E9 [52] . Besides, several natural products such as Lycoris radiata, Artemisia annua, Pyrrosia lingua, and Lindera aggregate have been reported to display significant J o u r n a l P r e -p r o o f anti-SARS-CoV properties [53] . Moreover, inhibitors from natural origin have been identified against the SARS-CoV enzymes, such as helicase and 3CL pro and viral RdRp [54] [55] [56] [57] . NPASS database is freely accessible (http://bidd2.nus.edu.sg/NPASS/) that provides the literature-reported experimentally-determined activity (e.g., IC50, Ki, EC50, GI50, and MIC) values of the natural products against macromolecule or cell targets along with the taxonomy of the species sources of 35032 unique natural products [58] . In the heart of the current Corona Virus Disease 2019 outbreak, these NPASS compounds may be used for capable therapy as they can remarkably reduce the time taken to design a therapeutic regimen.

Structure-based drug design by virtual screening and molecular docking studies has become a valuable primary step in the identification of novel lead molecules for the treatment of diseases [59, 60] , and proven to be a very efficient tool for antiviral [61] [62] [63] [64] and antibacterial [65, 66] and antiprotozoal [67, 68] drug discovery. Therefore, a virtual screening experiment was conducted to determine the interaction of natural ligands of the NPASS database within the binding pocket of putative drug targets of the virus that was calculated in terms of docking scores and MM-GBSA values. Our high throughput virtual screening revealed 21 natural compounds having higher docking scores and MM-GBSA values for six potent therapeutic targets of SARS-CoV-2 over the known chemical inhibitors. Remarkably, we suggested three natural compounds that able to bind the catalytic site of three/more crucial viral enzymes with a relatively high affinity, which ultimately can be used for the development of instant drugs for the emerging COVID-19.

For developing the structure of SARS-CoV-2 functional enzymes, the amino acid sequences of SARS-CoV-2 (accession NC_045512.1) were downloaded from the NCBI database [77] . Therefore, the refinement of the homology model is a very crucial step to identify the accurate near-native structure [78] . It is known that the geometrical/predicted structure of the target sequence affects the function of the protein, which also includes pharmacophore drug designing.

Here, we have used the 3D-refine server (http://sysbio.rnet.missouri.edu/3Drefine/) for the refinement of the modeled structures of each target protein of SARS-CoV-2. This refinement server works on the two-step protocol, which reliably brings the predicted homology model closer to its native structure [79] [80] [81] [82] [83] [84] . Where the first step is the optimization of the hydrogen bond network, and second is the minimization of atomic-level energy of optimized homology models using the knowledge-based force fields [85] . This server requires a homology model in PDB format as an input query. The server provides the five refined models as an output with best on the top in PDB format. There are several parameters for the selection of bestrefined models, which include the Molprobity score, which is the measure of the local quality of the structure [86] , the lower score shows the excellent model. Another given parameters as output scores are GDT-TS score, GDT-HA score, and RMSD, which tells about the positioning of Calpha atoms. GDT-TS and GDT-HA score of the refined model, which ranges from 0 to 1, where the lower score shows a good quality model [87] . The .pdb files of refined structures of respective target proteins were uploaded on the RAMPAGE server Journal Pre-proof J o u r n a l P r e -p r o o f (http://mordred.bioc.cam.ac.uk/~rapper/rampage.php), which had generated the Ramachandran plot. This plot is generated to obtain the value of the total count of amino acids present in the allowed, disallowed, and favorable regions [88] .

Refined homology models of the COVID-19 drug targets (proteins) were used for the further downstream steps. These protein structures were defined as a receptor and opened via protein preparation wizard in maestro v11.9 [89] . The standard refined model of protein does not fit for the docking with ligand molecules vis-a-vis calculation of the binding affinity. Therefore, models were preprocessed and optimized by filling the missing side chain using prepwizard module of the Schrodinger suite 2019-1. Heavy water molecules were removed with less than 3 H-bonds followed by energy minimization, which convert the heavy atoms to RMSD 0.30 Å.

Natural compounds from the NPASS database [58] were used as ligands to target the inhibitors were known for Influenza virus protein and member of DEddH family of exonucleases ( Figure 1 ).

J o u r n a l P r e -p r o o f 

The generation of the grid is a very crucial step for the binding of a ligand to the receptor.

Here, a 3-dimensional boundary for the ligand binding was generated in the receptor using Glide, version 8.2 [95] of Maestro, Schrodinger. The receptor grid for each target protein was generated by indicating the active sites amino acid residues, which were searched from previously reported studies appropriate to each target. Amino acid residues involved as the active site with respect to the target, along with their references, are available in supplementary table 1. The size of the receptor grid was set at default, i.e., 20 Å. Active site amino acids are crucial because they may affect the entry of the ligand, followed by binding to the target protein.

After grid generation, the natural compounds/ligands were docked to the target protein/receptor using the protocol of Glide grid version v8.2 [95] . The software internally generates different conformations, which passes across several filters viz. euler angles, gridbased force field evaluation, and Monte Carlo energy minimization. Lastly, the evaluation of conformers takes place based upon the docking score, and one of the best conformations per ligand is generated as an output. The docking was performed in three steps, which include high throughput virtual screening (HTVS), standard precision (SP), and extra precision (XP).

The first two steps of docking, HTVS, and SP utilize the self-same scoring function, whereas XP reduces the intermediate conformations and thoroughness of the torsional refinement and sampling [96] . A total of 4,570 natural compounds were docked against each target protein with their respective positive control inhibitor (mentioned earlier). Subsequently, top scorers were set forth for SP docking, and the output of SP docking was put forward in XP docking with positive control. The docking score is a binding energy/affinity given in the kcal/mol.

All the statistical data of top scorers for each target protein wrt control obtained is presented in result tables.

It has been shown that the natural compounds do not follow Lipinski's rule as these compounds tend to keep low hydrophobicity as well as the potential of donating the intermolecular H-bond [97] . We have used QikPropv5.9 of the Schrodinger suite, which analyzes the druggable properties of the ligands. This module takes ligprep file as an input and predicts the ADME properties in the form of several physicochemical properties and principal descriptor values, which were found in the acceptable range. GBSA energy score [98] .

Further, there are several other metrics, which are currently in use to evaluate the performance of virtual screening docking protocol, for instance, enrichment factor (EF), area under the ROC curve, and Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC) etc [99] . In this study, receiver operating characteristic (ROC) plots were also generated to assess the performance of the SP and XP docking methodology, which differentiates the active compounds with false positives means decoys [100] . These statistical curves represented the probability and were plotted to correctly classify the ligands into actives and decoys that finally attested our docking performance. It gives the value between 0 and 1, where 0 represents the worst performance of docking, and 1 represents the best performance [99, 101] . To plot these curves, sensitivity (on Y-axis) was plotted against 1-specificity (on X-axis). Here, sensitivity signifies the true positive, whereas 1-specificity signifies the decoys/false positive. All-natural compounds/ligands performed best on SP and XP docking were subjected to the docking protocol validation. Separate ROC curves to validate for both XP and SP docking protocols were generated. In addition to this, we have also calculated the Enrichment factor (an enrichment calculator from Schrodinger suite was used), Area Under Accumulation (AUC), and BEDROC values were also predicted.

For comprehending the properties of the structure and their microscopic interaction, molecular dynamics (MD) simulation was performed. For this, systems were built for best three multi-target natural compounds with one of their potent targets viz. helicase and NPC270578, exoribonuclease, and NPC214620 & methyltransferase and NPC52382 complex using Desmond v5.6, system builder panel (Schrodinger 2019-1). The optimized potentials were used for the liquid simulations at the OPLS3e force field, and these solvated systems were opened in the molecular dynamics panel [102] . Firstly, the solvated system builder was i.e., 300.0 K and standard atmospheric pressure, i.e., 1 bar. Upon the equilibration step, the total time for each simulation was appointed ten nanoseconds with trajectories analysis at regular intervals for the protein-ligand complex. Ultimately, the RMSD was analyzed to identify the stability of the target protein in its natural motion.

The amino acid lengths of the selected protein targets for SARS-CoV-2 were found to be 601 function of SWISS-MODEL, which relies on modeling error quantification and expected model accuracy. The GMQE and QSQE scores generally lie between 0 and 1, where higher the score, the higher the reliability of the modeled structure means expected accuracy of interchain interactions for a given template, whereas, in case of QMEAN, a score lower than 4.0 gives reliability [104] . After the model generation and refinement, each enzyme's structure was validated through the generation of the Ramachandran plot (Table 1 ).

Ramachandran plot confirmed that all target models after refinement would be used for molecular docking with ligand except 3C-like proteinase. In case of 3C-like proteinase the model obatined from Swiss-modelling was used for moelcular docking. The structure generation confirms the amino acid mapping in the allowed region, which shows the stable nature of existing proteins.

J o u r n a l P r e -p r o o f To screen effective inhibitors for SARS-CoV-2, we used compounds of NPASS database against six potential therapeutic targets of the virus, such as helicase, endoribonuclease, exoribonuclease, RNA-dependent RNA polymerase, N-methyltransferase, and 3C-like protease in our molecular docking experiment. HTVS, SP, and XP step-wise screening protocol were followed to find potent compounds having higher docking scores and binding energy as follows.

In a SARS-CoV replicon assay, it has been shown that the specific inhibition of SARS-CoV helicase by SSYA10-001 blocked viral replication [90] . Therefore, we used this compound as a control to find out more effective inhibitors for COVID-19 during our high throughput virtual screening experiment of natural compounds. Interestingly, we found five compounds such as NPC270578, NPC52382, NPC473043, NPC175107, and NPC22192 displayed docking score and MM-GBSA value 2.5 and 1.5 times greater than the control, respectively J o u r n a l P r e -p r o o f (Table 2) . Notably, NPC52382 has been shown to have biological activity against the malaria parasite in the NPASS database.

The antiviral property of endoribonuclease inhibitors has been validated for the influenza virus in multiple in vitro assay [93] . The essential function of endonuclease in the initiation of viral transcription supports its potential as a promising target for the development of antiviral agents. We find five compounds such as NPC169474, NPC297657, NPC19721, NPC279121, and NPC10737, which have more than two-fold docking scores and better MM-GBSA value than the known viral endoribonuclease inhibitor ( Table 2 ). Subsequent biological activity analysis of these compounds in the NPASS database reveals that NPC279121 has antiviral activity against Hepatitis C virus by inhibition of RdRp [105] , Influenza A virus by inhibition of neuraminidase [106] , HIV-1 by inhibition of integrase [107] and Simian virus 40 by unknown mechanism whereas NPC10737 has antiviral property (IC50=34µg/ml ) against HIV1 through suppression of transcription from 5ꞌ-long terminal repeat including activation via NF-kB [108] .

Inhibitors for exonuclease of the Lassa fever virus have been identified [94] . Our molecular docking studies identified five compounds, such as NPC137813, NPC191146, NPC3825, NPC270578, and NPC52382, bearing 1.8 to 2.7fold higher docking score and 2 to 2.5fold

higher MM-GBSA value as compared to the general lead exonuclease inhibitor MES (2-(Nmorpholino) ethanesulfonic acid) ( Table 2) . Surprisingly, we did not get any hints of the antiviral studies of these compounds in the NPASS database.

It is essential to find out novel compounds against COVID-19 based on broad-spectrum antiviral compounds. Several studies revealed the potent antiviral activities of remdesivir through the inhibition of RdRp [109] [110] [111] . Further, remdesivir has also shown antiviral activities against SARS-CoV and MERS-CoV [111] . To study whether the NPASS database has some compounds active against RdRP of SARS-CoV-2, we conducted molecular docking studies. We found a compound, NPC161224, having a 1.35 fold higher docking score but with a lower MM-GBSA value than remdesivir (Table 2 ). According to the NPASS database, this compound has also shown RdRP inhibition property against HIV1.

3CL pro is an attractive target for antiviral therapeutics because of its essential role in the processing of CoV polyprotein [112, 113] . Numerous 3CL pro inhibitors have been shown to block CoV replication in cell culture [114, 115] . TG-0205221, a known inhibitor of 3CL pro of SARS coronavirus, could significantly reduce the viral titer of SARS CoV in cell culture [92] . The binding mode information of TG-0205221 is employed here towards the discovery of new 3CL pro inhibitors from the NPASS database. From our intensive docking studies, we report five molecules such as NPC19709, NPC61506, NPC107109, NPC130230, and NPC175552 having three-fold higher docking score than TG-0205221. However, these molecules have a relatively lower MM-GBSA value than the control (Table 2) . Notable, the antiviral activity (IC 50 =14.48µg/ml) against Influenza A virus of NPC130230 by inhibition of neuraminidase [116] has been described in the NPASS database.

Methylation of the viral mRNA cap structure at the N7 position of the guanine is indispensable for the synthesis of viral proteins [117] . N7-methyltransferase has been shown as a potential antiviral target for SARS-CoV in a yeast-based screening assay [118] . In our docking experiment, three natural compounds such as NPC226294, NPC270578, and NPC52382 has shown better docking scores and MM-GBSA value than, Sinefungin, the known inhibitor of N7-methyltransferase (Table 2) . Besides, we get one compound NPC70622 that has antiviral activities such as IC 50 =300 µg/ml against the Hepatitis B virus by inhibition of HBV-DNA production [119] and EC 50 = 0.2µM against Hepatitis C virus by inhibition of RdRp [105] as described in the NPASS database. 

Lipinski's Rule of Five is not a strict criterion for natural compounds [120] . Therefore, some crucial ADME properties for the lead compounds were evaluated using Schrӧdinger QikProp module. Various basic physiochemical properties such as PlogPo/w (Predicted octanol/water partition coefficient), PlogS (Predicted aqueous solubility), PlogHERG (Predicted IC50 value for the blockage of HERG K + channels), PPCaco (Predicted apparent Caco-2 cell permeability for the gut blood barrier), PlogBB(predicted brain/blood partition coefficient), PPMDCK (Predicted apparent MDCK cell permeability in nm/sec), and PlogKhsa (prediction of binding to human serum albumin) of these compounds were predicted. The values of those compounds found in the acceptable range were shown in Table 3 Table   4 .

J o u r n a l P r e -p r o o f J o u r n a l P r e -p r o o f

In machine learning and data mining research, Receiver Operating Characteristic (ROC)

curves are usually used to study the performance of scoring function [121] . The ROC curve value detects predictive ability, which varies in the range 0.5 for random prediction to 1.0 for perfect prediction [122, 123] . For analyzing the performance of our scoring functions, SP and Table 5 . 

To understand the conformational changes of the protein and ligand during the course on interactions, we have performed ten nanoseconds of MD simulation using Desmond v 5. 2C ). Similar observation was indicated for the two thiocarbazate enantiomers of cathepsin L. Molecular docking studies revealed the docking score of S-enantioner (9.03 kcal/mol) more than the Renantiomer (7.02 kcal/mol), the difference was also validated in their biological activity; Senantiomer, with an IC50 of 56 nM and R-enantiomer, with an IC50 of 33 µM [128] . The importance of enantiomerism in the interaction of compounds with their binding sites, evaluated by docking scores, was also mentioned in other works [129, 130] . On the basis of the earlier reports, it can be accepted that endoribonuclease has shown a better binding affinity for one enantiomer than the other in the present molecular docking study.

Reports from in silico work have aided in ranking the molecule/compound, thus plummeting the chances related to the poor selection of lead molecules. Therefore, such studies are worthwhile for research groups working on wet-lab experiments intending to identify novel antiviral lead compounds. Recent advances in computational approaches are playing a substantial role in the screening of drug and their design. Here, we will discuss a story of successful drug identified via structure-based virtual screening of compounds, i.e., a researcher's team successfully discovered neuraminidase inhibitor against influenza virus [131] . This is a potent, highly selective, novel, and orally active compound against influenza A and influenza B named BCX-1812, RWJ-270201 (cyclopentane peramivir). Further, the group conducted the in vitro studies and experiments on mice, rats, and ferrets and found higher potency than known drug named zanamivir and oseltamivir [131] .

After human clinical trials, the drug, premavir found safe and effective [132] , and the team got US patent [133] . This cyclopentane drug premavir, was approved by US-FDA to be administered as an intravenous under an Emergency Use Authorization during H1N1 pandemic in 2009 [134, 135] and later on IV peramivir was approved by FDA under the brand name Rapivab TM [136] . Several other major successful drugs are existing in the market, which was discovered by in silico structure-based work includes drug (retroviral protease inhibitor) against HIV-1 [137] . Potential drugs, namely ratirexed [138] , an inhibitor of thymidylate synthetase against HIV-1, and amprenavir target the protease of HIV-1 [137, 139] .

Other popular examples are drugs; namely, Isoniazid targets the InhA enzyme works against tuberculosis, which is also a major global health problem discovered by virtual screening [140] and Norfloxacin targets topoisomerase II & IV enzyme and treats the Urinary Tract infection [141] . All these successful drugs pave us the way to work upon the virtual Journal Pre-proof J o u r n a l P r e -p r o o f screening based strategy to combat the ongoing pandemic. By considering this work now, researchers will be able to plan the experimental work on lead compounds identified in this study. However, the only concern is that there are several failure stories also reported in the documents; for instance, an antidepressant (RPX00023) was declared to be an agonist of 5-HT1A receptor while it was found to be an inhibitor [142] . Therefore, in vitro activity experiments with individual protein targets followed by SARS-CoV-2 replication assays of the compound identified from this study may support the development of novel and highly potent therapeutics for the treatment of rapidly spreading COVID-19.

Human coronaviruses

Nidovirales: evolving the largest RNA virus genome

Cultivation of a novel type of common-cold virus in organ cultures

Identification of a novel coronavirus in patients with severe acute respiratory syndrome

Koch's postulates fulfilled for SARS virus

A novel coronavirus associated with severe acute respiratory syndrome

Bats Are Natural Reservoirs of SARS-Like Coronaviruses

Isolation and characterization of viruses related to the SARS coronavirus from animals in southern China

Progress in global surveillance and response capacity 10 years after severe acute respiratory syndrome

The chronology of the 2002-2003 SARS mini pandemic

Emergence of the Middle East respiratory syndrome coronavirus

Countries Agree Next Steps to Combat Global Health Threat by MERS-CoV, WHO

Human betacoronavirus 2c EMC/2012-related viruses in bats

Close Relative of Human Middle East Respiratory Syndrome Coronavirus in Bat

A novel coronavirus from patients with pneumonia in China

Severe acute respiratory syndrome-related coronavirus-The species and its viruses, a statement of the Coronavirus Study Group

A pneumonia outbreak associated with a new coronavirus of probable bat origin

Drug targets for corona virus: A systematic review

Recent insights into the development of therapeutics against coronavirus diseases by targeting N protein

An Overview of Severe Acute Respiratory Syndrome-Coronavirus (SARS-CoV) 3CL Protease Inhibitors: Peptidomimetics and Small Molecule Chemotherapy

Identification and characterization of a serine-like proteinase of the murine coronavirus MHV-A59

Broad-spectrum inhibitors against 3C-like proteases of feline coronaviruses and feline caliciviruses

Crystal structure of SARS-CoV-2 main protease provides a basis for design of improved α-ketoamide inhibitors

Mechanism of nucleic acid unwinding by SARS-CoV helicase

Biochemical Characterization of Middle East Respiratory Syndrome Coronavirus Helicase

The adamantane-derived bananins are potent inhibitors of the helicase activities and replication of SARS coronavirus

The severe acute respiratory syndrome coronavirus Nsp15 protein is an endoribonuclease that prefers manganese as a cofactor

Major genetic marker of nidoviruses encodes a replicative endoribonuclease

Discovery of an RNA virus 3′→ 5′ exoribonuclease that is critically involved in coronavirus RNA synthesis

Potent and selective inhibition of SARS coronavirus replication by aurintricarboxylic acid

In vitro reconstitution of SARS-coronavirus mRNA cap methylation

Coronavirus susceptibility to the antiviral remdesivir (GS-5734) is mediated by the viral polymerase and the proofreading exoribonuclease

Zn2+ inhibits coronavirus and arterivirus RNA polymerase activity in vitro and zinc ionophores block the replication of these viruses in cell culture

Antiviral Drug Targets of Single-Stranded RNA Viruses Causing Chronic Human Diseases

The Viral Macrodomain Counters Host Antiviral ADP-Ribosylation

Antiviral drug resistance

Polypharmacy in the HIV-infected older adult population

The efficiency of multi-target drugs: the network approach might help drug design

Molecular model of shikimate kinase from Mycobacterium tuberculosis

Experimental approaches to evaluate the thermodynamics of protein-drug interactions

New catalytic mechanism for human purine nucleoside phosphorylase

Experimental approaches to evaluate the thermodynamics of protein-drug interactions

Viral infectious disease and natural products with antiviral activity

Antioxidant and radical scavenging properties of curcumin

Antioxidant activity of eugenol: A structure-activity relationship study

Antioxidant activity of food constituents: an overview

Antioxidants and antioxidant methods: an updated overview

Perspectives of Plant Natural Products in Inhibition of Cancer Invasion and Metastasis by Regulating Multiple Signaling Pathways

Do the Natural Chemical Compounds Interact with the Same Targets of Current Pharmacotherapy for Weight Management?-A Review

Natural Products as Potential anti-Alzheimer Agents

Antiviral natural products and herbal medicines

Antiviral effects of saikosaponins on human coronavirus 229E in vitro

Identification of natural compounds with antiviral activities against SARSassociated coronavirus

Anti-SARS coronavirus 3C-like protease effects of Isatis indigotica root and plantderived phenolic compounds

Biflavonoids from Torreya nucifera displaying SARS-CoV 3CLpro inhibition

Identification of myricetin and scutellarein as novel chemical inhibitors of the SARS coronavirus helicase

Immunomodulatory and anti-SARS activities of Houttuynia cordata

NPASS: natural product activity and species source database for natural product research, discovery and tool development

Structure-based strategies for drug design and discovery

In silico virtual screening approaches for anti-viral drug discovery

Identification of Zika virus NS2B-NS3 protease inhibitors by Structure-Based Virtual Screening and Drug Repurposing Approaches

Discovery of benzoazepinequinoline (BAQ) derivatives as novel, potent, orally bioavailable respiratory syncytial virus fusion inhibitors

Identification of small molecule compounds targeting the interaction of HIV-1 Vif and human APOBEC3G by virtual screening and biological evaluation

Structure-based virtual screening, free energy of binding and molecular dynamics simulations to propose novel inhibitors of Mtb-MurB oxidoreductase enzyme

New active leads for tuberculosis booster drugs by structure-based drug discovery

Computational approaches for drug discovery against trypanosomatid-caused diseases

Discovery of new potent hits against intracellular Trypanosoma cruzi by QSAR-based virtual screening

NCBI BLAST: a better web interface

SWISS-MODEL: homology modelling of protein structures and complexes

Cysteine proteases secreted by the pinewood nematode, Bursaphelenchus xylophilus: in silico analysis

Streptococcal Collagen-like Protein 1 Binds Wound Fibronectin: Implications in Pathogen Targeting

Homology Modeling of Protein Targets with MODELLER, Docking Screens for Drug Discovery

Molecular models of NS3 protease variants of the Hepatitis C virus

Protein crystallography in drug discovery

Structural bioinformatics study of EPSP synthase from Mycobacterium tuberculosis

A multi-template combination algorithm for protein comparative modeling

A molecular dynamics approach for the generation of complete protein structures from limited coordinate data

What makes it difficult to refine protein models further via molecular dynamics simulations?

i3Drefine software for protein 3D structure refinement and its assessment in CASP10

Assessment of refinement of template-based models in CASP11

Protein structure prediction: when is it useful?

Experimental accuracy in protein structure refinement via molecular dynamics simulations

CASP 11 refinement experiments with ROSETTA

Cloning and characterization of four novel coral acid-rich proteins that precipitate carbonates in vitro

MolProbity: all-atom structure validation for macromolecular crystallography

SomamiR 2.0: a database of cancer somatic mutations altering microRNA-ceRNA interactions

Structure validation by Cα geometry: ϕ, ψ and Cβ deviation

Schrödinger Suite 2019-1 Protein Preparation Wizard

Severe acute respiratory syndrome coronavirus replication inhibitor that interferes with the nucleic acid unwinding of the viral helicase

The antiviral compound remdesivir potently inhibits RNA-dependent RNA polymerase from Middle East respiratory syndrome coronavirus

Synthesis, Crystal Structure, Structure− Activity Relationships, and Antiviral Activity of a Potent SARS Coronavirus 3CL Protease Inhibitor

A novel endonuclease inhibitor exhibits broad-spectrum anti-influenza virus activity in vitro

Identification of Inhibitors for the DEDDh Family of Exonucleases and a Unique Inhibition Mechanism by Crystal Structure Analysis of CRN-4 Bound with 2-Morpholin-4-ylethanesulfonate (MES)

Glide: a new approach for rapid, accurate J o u r n a l P r e -p r o o f docking and scoring. 1. Method and assessment of docking accuracy

Developing imidazole analogues as potential inhibitor for Leishmania donovani trypanothione reductase: virtual screening, molecular docking, dynamics and ADMET approach

The impact of natural products upon modern drug discovery

Accurate prediction of the relative potencies of members of a series of kinase inhibitors using molecular docking and MM-GBSA scoring

Evaluating virtual screening methods: good and bad metrics for the "early recognition" problem

ROC graphs with instance-varying costs

The discovery of potential acetylcholinesterase inhibitors: a combination of pharmacophore modeling, virtual screening, and molecular docking studies

OPLS3: a force field providing broad coverage of drug-like small molecules and proteins

QMEAN server for protein model quality estimation

Discovery of flavonoid derivatives as anti-HCV agents via pharmacophore search combining molecular docking strategy

Structure-activity relationship of flavonoids as influenza virus neuraminidase inhibitors and their in vitro antiviral activities

Design and discovery of flavonoid-based HIV-1 integrase inhibitors targeting both the active site and the interaction with LEDGF/p75

Low molecular weight lignin suppresses activation of NF-κB and HIV-1 promoter

Discovery and Synthesis of a Phosphoramidate Prodrug of a Pyrrolo

GS-5734 and its parent nucleoside analog inhibit Filo-, Pneumo-, and Paramyxoviruses

Therapeutic efficacy of the small molecule GS-5734 against Ebola virus in rhesus monkeys

Characterization of a novel coronavirus associated with severe acute respiratory syndrome

The genome sequence of the SARS-associated coronavirus

Synthesis and evaluation of keto-glutamine analogues as potent inhibitors of severe acute respiratory syndrome 3CLpro

Design and synthesis of peptidomimetic severe acute respiratory syndrome chymotrypsin-like protease inhibitors

QSAR study of flavonoids and biflavonoids as influenza H1N1 virus neuraminidase inhibitors

Mutagenesis of S-adenosyll-methionine-binding residues in coronavirus nsp14 N7-methyltransferase demonstrates differing requirements for genome translation and resistance to innate immunity

Yeast-based assays for the high-throughput screening of inhibitors of coronavirus RNA cap guanine-N7-methyltransferase

Identification of natural compounds with anti-hepatitis B virus activity from Rheum palmatum L. ethanol extract

Chris Lipinski discusses life and chemistry after the Rule of Five

An introduction to ROC analysis

Pharmacophore modeling, virtual screening, docking and in silico ADMET analysis of protein kinase B (PKB β) inhibitors

Computational identification of novel histone deacetylase inhibitors by docking based QSAR

The evolutionary genetics of emerging viruses

Herbal lead as ideal bioactive compounds against probable drug targets of Ebola virus in comparison with known chemical analogue: A computational drug discovery perspective

A metabolite profiling approach to identify biomarkers of flavonoid intake in humans

Rational design of novel, potent small molecule pan-selectin antagonists

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Acknowledgments: DP is thankful to UGC for providing a start-up grant.

Journal Pre-proof J o u r n a l P r e -p r o o f

The authors appreciate and extend thanks for the kind consideration and thorough review of this manuscript that provided us the opportunity to revise and improve it. Keeping the reviewers useful and validly raised concerns and questions in mind we revised and improved the manuscript. We are extremely thankful to the editor for the slection of five reviewers and humbly thankful to all reviewers for giving your valublae suggestion which will not only be useful for the improvement of this manuscript but also useful in the fight against minacious COVID-19 present situation. We have addressed the questions raised or corrections suggested by reviewers point by point.

Dhaneswar Prusty