Structure-based screening of Natural product libraries in search of potential antiviral drug-leads as rst-line treatment to Covid-19 infection

The study describes a novel strategy to screen natural products (NPs) based on their structural similarities with chemical drugs and their use as rst-line treatment to Covid-19 infection. In the present study, the in-house natural product libraries, consisting of a total of 26,311 structures, were screened against potential targets of 2019-nCoV/SARS-CoV-2 based on their structural similarities with the prescribed chemical drugs. The comparison was based on molecular properties, 2 and 3-dimensional structural similarities, activity cliffs, and core fragments of NPs with chemical drugs. The screened NPs were evaluated for their therapeutic effects based on predicted in-silico pharmacokinetic and pharmacodynamics properties, binding interactions with the appropriate targets, and structural stability of the bound complex. The study yielded NPs with signicant structural similarities to synthetic drugs currently used to treat Covid-19 infections. The study proposes the selected NPs as Anti-retroviral protease inhibitors, RNA-dependent RNA polymerase inhibitors, and viral entry inhibitors. against chemical drugs currently under prescription/study to treat COVID 19 infection. The comparison is based on 2 and 3-dimensional structural similarities, activity cliffs (ACs), and core fragments (CFs). The structural similarities were assessed based on the number of fragments that both molecules have to the number of fragments found in any two structures [68]. The structural scaffolds (SSs) were analyzed based on plane ring system to determine the sub-structures. ACs, CFs, and SSs were determined employing Osiris DataWarrior V.4.4.3


Introduction
Viral infections play an important role in human diseases, and their regular outbreaks repeatedly underlined the need for their prevention in safeguarding public health [1]. The recent outbreak of the novel coronavirus Covid-19 was declared 'public health emergency of international concern' by World Health Organization (WHO) in view of its severity [2]. The Coronavirus disease (COVID- 19), previously known as '2019 novel coronavirus' or '2019-nCoV', is an infectious disease caused by a newly discovered coronavirus; severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2 [3]. The SARS-CoV-2 is a member of the Coronavirinae family belonging to the Betacorona genus [4]. Structurally it is spherical or pleomorphic in shape, with a diameter of about 60-140nm. All ages are susceptible to COVID-19 infection, and its clinical manifestations range from asymptomatic to mild to severe and even to death depending on the underlying health conditions of individuals [5,6]. The most commonly reported symptoms are fever, chills, headache, body aches, dry cough, fatigue, pneumonia, and complicated dyspnea. The virus transmits from person to person via the nasal, oral, eye, and mucosal secretions of the infected patient and direct transmission through the inhalation of droplets released during the patient's cough or sneeze [7,8].
For the clinical diagnosis of SARS-CoV-2, the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) method is widely being used today [9]. It is a nucleic acid detection test where nasopharyngeal and oropharyngeal samples were used for the detection. However, to provide quick diagnosis techniques like transcription loop-mediated isothermal ampli cation (RT-LAMP), transcription-mediated ampli cation (TMA), CRISPR-based assays, rolling circle ampli cation, and microarray hybridization assays have been developed and are currently in use [10,11].
To prevent the transmission of SARS-CoV-2, the development of an effective vaccine is highly essential. Therefore, scientists around the world are engaged in developing potential vaccines. However, at this stage, it is unclear which vaccine strategy would be most effective. Figure-1 describes some of the most widely used vaccines currently developed against Covid-19. The other potential treatment strategies include inhibition of RNA-Dependent RNA Polymerase activity, viral protease inhibition, viral entry inhibition, immune modulation, monoclonal antibodies, janus kinase inhibitors, nutritional supplements, and the conventional plasma therapy (Table 1) [11]. The developmental status of different antiviral drugs to treat Covid-19 conditions is shown in gure 3. Table 1: Mechanism of action of some of the COVID-19 prescribed drugs and their common usage.

COVID-19 prescribed Drugs
Known mechanism of action and their common usage Inhibiting the RNA-Dependent RNA Polymerase Remdesivir Inhibits viral RNA production and replication of EBOV [12] Favipiravir Anti-in uenza drug [13] Galidesivir Hepatitis C treatment [14] Ribavirin Hepatitis C treatment viral hemorrhagic fevers [15] Sofosbuvir Hepatitis C treatment [16] Viral Protease Inhibitors Lopinavir/Ritonavir Anti-retroviral protease inhibitor [17] Nel navir Inhibits HIV-1 and HIV-2 retroviral proteases [18] Atazanavir Anti-retroviral protease inhibitor used to treat HIV infections [19] Darunavir anti-retroviral protease inhibitor [20] Danoprevir HCV Protease Inhibitor [21] Viral Entry Inhibitor Hydroxychloroquine Antimalarial drug [22] Arbidol Anti-in uenza drug [23] Ivermectin Antiviral/antiparasitic drug [24] Immune Modulators Interferon-alpha (IFN-2b) Antiviral and/or anti-neoplastic drug [25] Tacrolimus Inhibits T-lymphocyte signal transduction and IL-2 transcription [26] Monoclonal Antibodies Sarilumab IL-6 receptor blocker [27] Tocilizumab Treatment of rheumatoid arthritis and juvenile idiopathic arthritis. Inhibits the IL-6 signaling pathway [28] Janus Kinase Inhibitors Fedratinib Inhibits JAK2 the treatment of rheumatoid arthritis [29] Baricitinib Reversible inhibitor of both JAK1 and JAK2 in the treatment of rheumatoid arthritis [30] Nutritional Supplements Vitamin C Boosts immunity by stimulating IFN production [31] Vitamin D Involved in adaptive immunity, immune cell differentiation, proliferation, and maturation [32] Folic Acid Important for rapid cell proliferation [33] Miscellaneous Valsartan Angiotensin-converting enzyme (ACE) inhibitors and angiotensin receptor blockers [34] Disul ram Inhibitor of the peripheral benzodiazepine receptor and acetaldehyde dehydrogenase enzyme [45] Cyclosporin Calcineurin inhibitor [46] Prograf Inhibits T-lymphocyte signal transduction and IL-2 transcription [26] Sirolimus Suppress viral replication [47] 7-Methylguanosine 5'-diphosphate and triphosphate Translation initiation factor activity [48] Convalescent Plasma Therapy Adoptive immunotherapy [49] Natural products and traditional medicines have been serving as the greatest source for modern drug discovery. Their derivatives are recognized for many years as the source of the therapeutic potential and structural diversity. There are over 200,000 compounds reported in the scienti c literature. NPs are more often structurally complex, with well-organized structure and steric properties offering e cacy, e ciency, and selectivity of molecular targets [50]. However, their utilization on many health conditions is well documented; it is in the hands of existing traditional practitioners and herbologists to de ne their applications for newly emerging diseases. The biological activities reported from different plant extracts often narrow down to pre-reported molecules rather than novel compounds [51], creating a real challenge to medicinal chemists. In this avenue, the search for new therapeutic molecules is the need of the hour to combat against new health challenges.
The biological activity of any molecule is attributed to its structural arrangements. If two molecules have a similar structure, they will most probably have a similar biological effect [52][53][54] (Fig.3). The computational chemists are successful in exploiting this principle for the construction of diverse compound libraries and select compounds for high-throughput screening experiments [52]. Computational advancements with the introduction of parallel processing clusters, cloud-based computing, and highly effective graphical processing units (GPUs), tremendous success has been achieved in the eld of modern drug discovery [55]. The knowledge of natural products and ligands, earlier used as starting points for drug discovery, has greatly in uenced computational biology techniques [56]. These advancements have been speeded up by the creation of new algorithms for more accurate predictions, simulations, and interpretations [57][58][59][60][61][62]. The extensive molecular dynamics (MD) simulations can provide insights into the host-virus interactions, disease spread, and possible regulative/preventive mechanisms [63]. The present study proceeds to identify natural products as rst-line treatment options for Covid-19 infections in this avenue. By considering the structural properties of prescribed chemical drugs currently used to treat different Covid-19 conditions, natural product libraries were screened to identify potential antiviral drug molecules. The study extends to describe the possible mechanism of their therapeutic actions creating new opportunities for nature-based therapeutics.

Materials And Methods
Dataset collection and library construction: An in-house natural product library consisting of 26,311 natural product structures was constructed using natural products information from different databases like Dr Structure-based screening of Natural products: The non-redundant natural product libraries were compared against chemical drugs currently under prescription/study to treat COVID 19 infection. The comparison is based on 2 and 3-dimensional structural similarities, activity cliffs (ACs), and core fragments (CFs). The structural similarities were assessed based on the number of fragments that both molecules have to the number of fragments found in any two structures [68]. The structural scaffolds (SSs) were analyzed based on plane ring system to determine the sub-structures. ACs, CFs, and SSs were determined employing Osiris DataWarrior V.4.4.3 software [68].
Molecular properties based PK/PD analysis: Natural products are the major source of oral drugs 'beyond Lipinski's rule of ve' [69][70][71]. The druglikeness assessment, pharmacokinetic (PK), and pharmacodynamics (PD) of NPs were determined based on their molecular properties like molecular weight, cLogP, hydrogen atom donors, hydrogen atom acceptors, and rotatable hydrogen bonds. These properties are used as ltering parameters to estimate the oral bioavailability, solubility, and permeability of new drug candidates [69,71,72]. The natural products obtained from structural comparison were considered as hits for in-silico PK/PD assessment. Molecular properties were predicted using Osiris Data warrior V.4.4.3 software [68]. The admetSAR server [73] was used to predict different parameters constituting the PK/PD properties of the selected molecules.
Automated docking was performed to deduce the binding interactions of selected natural products with appropriate target proteins. Broyden-Fletcher-Goldfarb-Shanno algorithm implemented in the AutoDockVina was employed to study proper binding modes of the selected natural products in different conformations [74]. The antiviral drugs currently being prescribed for Covid-19 rst-line treatment were retrieved from the drugvirus.info server, and their action mechanisms were studied using the Inxight: Drugs database (https://drugs.ncats.io/) ( Table 1).
Based on the action mechanism of the standard drugs, HIV-1 protease I50V isolate, in uenza virus hemagglutinin, SARS-CoV NSP12 polymerase and HIV-1 protease A02 isolate were selected for the docking studies. The protein structures were retrieved from protein databank (https://www.rcsb.org/) and were prepared for docking studies. For each target, residues forming the binding site were identi ed using the PDBsum server. The antiviral drug; Lopinavir and its related natural products were docked against anti-retroviral protease inhibitor (I50V isolate) (PDB ID 3OXV), Ritonavir and its related natural products were docked against anti-retroviral protease inhibitor (A02 isolate) (PDB ID 4NJV), Remdesivir, and its related natural products were docked against anti-retroviral protease inhibitor (PDB ID 7BV2), and Arbidol and its related natural products were docked against anti-retroviral protease inhibitor (PDB ID 5T6S). For the ligand molecules, all the torsions were allowed to rotate during docking. The in-silico studies were performed on a local machine equipped with AMD Ryzen 5 six-core 3.4 GHz processor, 8GB graphics, and 16 GB RAM with Microsoft Windows 10 and Ubuntu 16.04 LTS dual boot operating systems.
Molecular dynamic simulations to predict the protein structural stability: the structural stability of the free and bound targets was assessed using MD simulations run for a time scale of 20 ns [75,76] by employing the GROMOS96 54a7 [77] force eld implemented in the GROMACS-2018 package [78]. A periodic cubic solvated box was created around the target proteins with at least 10 Å distance from the edge of the box and solvated using the simple point charge (SPC) model [79] and neutralized using sodium and chloride ions. Temperature coupling at 300K was done using V-rescale thermostat [80], and pressure coupling at 10 5 Pa was done using Parrinello-Rahman barostat [81]. Bond parameters were adjusted using the LINCS algorithm [82], and the particle mesh Ewald method (PME) [83] was used to evaluate electrostatic interactions. The nal MD trajectories were prepared for a time scale of 20ns at a time step of 2fs with trajectory coordinates updated at 10ps intervals. The nal trajectories were analyzed using gmx energy, gmx rms, gmx rmsf, gmx gyrate, gmx do_dssp, and gmx sasa modules of GROMACS along with interaction energies in terms of electrostatic and van der Waals energy between the ligand and the macromolecule.
Biding free energy calculations using g_mmpbsa: For Molecular mechanics/Poisson-Boltzmann surface area (MMPBSA) calculations, trajectory les were created from the nal 10 ns with coordinates updated every 200ps. The g_mmpbsa package was used for binding energy calculations [84]. The g_mmpbsa package uses the following equation to calculate the binding energy of the protein-ligand complex; The 'G' term can be further decomposed into the following components- clinical trials drug library. Among the total number of molecules screened, 17,798 natural product structures were found to have more than 60% structural similarities against Pubchem Covid19 library, of which 41 molecules were avans, 41 were avones, and 272 were iso avonoids. The comparison against clinical trials drug library yielded 14,689 natural products with more than 60% structure similarity consisting of 30 avans, 18 avones, and 78 iso avonoids.
The study was extended to compare the complete natural product library against the most promising investigational drugs, viz. Remdesivir, Arbidol, Lopinavir, and Ritonavir molecules yielded 35 natural product structures with considerable structural similarity ( Table 2). Molecular properties based PK/PD analysis: Molecular properties and Pharmacokinetics prediction of natural products were predicted using Osiris data warrior software and the admetSAR server. The druglikeness estimated based on the molecular properties of the selected structures indicated that out of 35 molecules, 23 molecules with positive scores indicated their potential drug-like effects. Gastrointestinal (GI) absorption is an important parameter to screen orally administered drugs. A positive value shown in Table 3A for gastrointestinal (GI) absorption suggests a high probability of success for absorption into the intestinal tract [85]. While the blood-brain barrier (BBB) penetration indicates the potentials of a drug to cross into the brain, it can bind to speci c receptors and activate speci c signaling pathways. Therefore, the prediction of BBB penetration is crucial in the drug development pipeline [86]. In the present study, 33 molecules were found to penetrate the human intestine barrier, 17 molecules penetrating the blood-brain barrier, and none of them being the substrate for Cytochromes P450 group of isozymes which regulates drug metabolism, indicating a high possibility of their bioavailability (Table 3A). Further, out of 35 molecules, 34 were predicted to be nonmutagenic and non-tumorigenic and non-irritant, with 10 molecules predicted to have reproductive effects (Table 3B). Among the 35 structures, 29 compounds were non-AMES toxic, 34 non-carcinogens, and 34 were not readily biodegradable.  The in-silico molecular interaction studies were used to predict the most effective natural product drug to bind to the appropriate target involved in the regulation of virus entry, replication, assembly and release, as well as host-speci c interactions. In the present study, the docking studies were carried for synthetic antiviral agents as well as their structurally similar natural products against different targets proteins of SARS-CoV-2 to deduce the structural insight of molecular interactions. The study yielded natural products being effectively bound to their respective targets ( Table 4). The results were expressed in terms of docking energy (kcal/mol). Many of the selected natural products have displayed docking energies higher than their structurally similar standard drug counterparts. The natural products structurally similar to Remdesivir interact with SARS-CoV NSP12 polymerase with docking energies comparably higher than the standard drug. The natural products tested as in uenza virus hemagglutinin inhibitors are also bound to the target with docking energies higher than the standard drug arbodol. The binding interactions of natural products tested as viral protease inhibitors were compared with standard drugs lopinavir and ritonavir. Further, their molecular interactions were found stabilized by the formation of many hydrogen bonds. The effectiveness of these binding of natural product with highest interaction energy in each group was selected for protein stability assessment using molecular dynamics simulations (Fig. 4). In the present study, united-atom MD simulations were performed to con rm the accuracy of binding resulted from docking studies. The result of the MD simulation displayed the conformational changes acquired by different target proteins of SARS-CoV-2 upon binding and inferred the structural insight on molecular stability ( g 4).
The RMSD analysis was done to understand the deviation of Cα atoms of the protein from its backbone, and RMSF analysis was done to study the uctuations associated with the amino acid residues of the protein during the simulation. The average RMS deviations and RMS uctuations were calculated from the MD trajectories of natural product, and synthetic drug bound HIV-1 protease (I50V isolate), In uenza virus haemagglutinin, SARS-CoV NSP 12 polymerase, and HIV-1 protease (A02 isolate) and were compared with their respective unbound structures. Lesser RMS deviations were observed in the bound structure of HIV-1 protease (I50V isolate) after the binding of Hexahydropyrrolo Derivative compared to Lopinavir standard drug. The protein SARS-CoV NSP 12 polymerase displayed lesser RMS deviations after the binding of HydroxyManzamin_A. In comparison, HIV-1 protease (A02 isolate) exhibited lesser RMS deviations after the binding of Bionectin_B compared to their respective chemical drug counterparts. RMS deviations were lower in Arbidol bound In uenza virus haemagglutinin than natural product Phellibaurin_A bound structure (Fig. 4a-d). Lesser RMS uctuations were observed in the natural product bound structures of HIV-1 protease, In uenza virus haemagglutinin, and HIV-1 protease than their respective chemical drug bound structures ( g.4e-h). From the RMDF plots, it can be inferred that, though the residues displayed higher uctuations at certain positions, the protein was able to retain its secondary structure's packability. This was inferred based on the Rg plots ( Fig.4i-l), where the structures were found to be very tightly packed, as the secondary structure elements like α-helix, β-sheet, and turn, were remodelled at each time step of the MD simulation. The SASA plots (Fig. 4m-p) also supported these ndings.
The binding free energy calculations performed using the g_mmpba module displayed better binding of natural products with their respective target proteins compared to their chemical drug counterparts. The binding free energies of 12_28_Oxa_8_Hydroxy_Manzamin_A (-56.19kJ/mol), Phellibaurin_A (-125.49kJ/mol), and Hexahydropyrrolo Derivative (-91.66kJ/mol) were found to be higher than their respective structurally similar standard drug counterparts; remdesivir (-48.74kJ/mol), arbidol (-102.17), and lopinavir (-81.19kJ/mol) indicating their rm binding with their respective targets. However, the standard drug ritonavir displayed a higher binding energy of -180.82kJ/mol compared to its structurally similar natural product bionectin B (-162.08kJ/mol. The associated terms for binding free energy calculations along with the calculated MD parameters for unbound and ligand-bound targets detailing RMSD, RMSF, Rg, SASA, Secondary structure, Coul-SR energy, and LJ-SR energy are detailed in table 5.  [1]. Despite the advancements in modern drug research, many viruses lack preventive vaccines or effective therapies. In addition, the constant mutations undergone by the virus made it highly [87] challenging for scientists. Further, the potential development of drug-resistant mutants, especially for viral enzyme-speci c inhibitors, have signi cantly hampered the drug e cacy [1,88,89]. Therefore, identifying e cacious and cost-effective antiviral drugs in the absence of potential vaccines or standard therapies is of utmost importance. Herbal medicines and puri ed natural products have been serving as an excellent source for modern drug research programs. The mechanistic elucidation of antiviral drug actions has shed light on the viral life cycle, including their entry, replication, assembly and release, and host-speci c interactions.
Due to the advancements in virology, molecular biology, and computational biology, we were quickly able to decipher the patho-physiology of Covid-19 infection [87]. This was followed by pharmacological investigations, drug repurposing and vaccine development. Enormous Covid-19 related publications and treatment strategies shows that scientists are trying every possible possibilities to nd cure for this infection [11].
The computational models have been designed to predict the interactions of potential human target proteins with speci c viral strains. By relying on the available interaction information, these models predict the novel host-virus interactions. These predictions have been reliable in the past in understanding the infection mechanism of SARS-CoV [90], MERS-CoV [90], Ebola virus [91], and Zika virus [92]. However, these computational methods play a signi cant role in modern drug research; the experimental veri cations of virus-host interactions are needed to substantiate the potential interactions. Along with this, the availability of veri ed interactions and relevant information is a prerequisite for computational drug discovery methods.
Natural products can be an important complementary medicine to combat against viral infections. Their origin, availability, safety, and cost-effectiveness make them a better choice than synthetic drugs [93]. The present study suggests natural products can exert their therapeutic effects similar to their synthetic drug counterparts. Molecular interaction studies suggests that natural products 12_28_Oxa_8_Hydroxy_Manzamin_A, Marineosin_A, Bis(Gorgiacerol)Amine, Methylstemofoline, Chetracin_B, Oxyprotostemonine, and Stemocurtisine can inhibit RNA-Dependent RNA Polymerase activity similar to remdesivir by binding with SARS-CoV NSP12 polymerase enzyme. Further, all the ten molecules identi ed to be structurally similar to arbidol displayed binding energies higher than arbidol, suggesting viral entry inhibitory effects. The interactions of natural products structurally similar to Lopinavir and Ritonavir can act as viral protease inhibitors.
The structural stability imposed by the selected natural products after binding to their respective targets supports their effective binding. Several studies have shown that some natural products can interact with key viral proteins associated with virulence [11,[94][95][96][97]. Nevertheless, the screening and selection methods that rely on the structural representations involving physiochemical properties, topological indices, molecular graphs, pharmacophore features, molecular shapes, molecular elds, or quantitative measures are expected to reduce false-positive results and yield more effective structures. In this avenue, the current research compares natural products with synthetic drugs and proposes the probable mechanism of action, suggesting a reliable option for rst-line treatment against Covid-19 infection.

Declarations
Ethics approval and consent to participate: Not applicable.
Consent for publication: Not applicable.
Availability of data and materials: All the data used during the current study are available from the corresponding author on reasonable request.
Competing interests: The authors declare that they have no con icts of interest.
Availability of data and materials: All the data used during the current study are available from the corresponding author on reasonable request.   The broad-spectrum antiviral drugs currently being investigated to treat the Covid-19 condition.