Screening of potential inhibitors for COVID-19 main protease from phytoconstituents of Tectona grandis Linn: application of molecular modeling studies

The recent outbreak of novel coronavirus disease, COVID ‐ 19 has created a threat to human population across the world. The unavailability of specic therapeutics and vaccines, demands the sincere efforts in this direction. Main Proteases of this novel Coronavirus (SARS ‐ CoV ‐ 2) play critical role during the disease propagation, and hence represents a crucial target for the drug discovery. Reported phytoconstituents of T. grandis Linn were prepared for docking evaluation. The current objective of the study is to identify some naturally occurring product from Tectona grandis Linn. and evaluate its binding activity against COVID ‐ 19 Major protease as novel Coronavirus (SARS ‐ CoV ‐ 2) target through in silico docking studies. The study results showed that all the selected phytoconstituents showed binding energy ranging between -7.723 to -1.524 kcal/mol. Barleriaquinone-I exhibited highest binding anity ‐ 7.723 Kcal/mol and strong, stable interactions with the amino acid residues present on the active site of COVID ‐ 19 Main Protease. Our ndings suggest that these phytoconstituents molecules can be used as potential inhibitors against COVID ‐ 19 Main Protease. However, further investigation and validation of these inhibitors against SARS ‐ CoV ‐ 2 are needed to claim their candidacy for clinical trials


Introduction
Medicinal plants have been widely used to treat a wide variety of infectious as well as non-infectious ailments. Many of the plant derived compounds exhibit antiviral properties and are found to be effective against various viral infections. Due to their low toxicity and possible multi-step mechanism, which means, lesser selective pressure for the emergence of resistant strains, natural products have been encouraged for searching new drugs. In addition, the majority of the compounds used for the clinical Organization has declared global public health emergency on 4 March 2020 as there are more than 90,000 con rmed cases reported, and the death toll is over 3000. In the height of the crisis, this virus is spreading at a rate and scale far worse than previous coronaviral epidemics. Coronaviruses possess extraordinarily large single-stranded RNA genomes-approximately 26 to 32 kilo bases in length. This genome acts just like a messenger RNA when it infects a cell, and directs the synthesis of two long polyproteins that include the machinery that the virus needs to replicate new viruses. These proteins include a replication/transcription complex that makes more RNA, several structural proteins that construct new virions, and two proteases. The proteases play essential roles in cutting the polyproteins into all of these functional pieces. It is a dimer of two identical subunits that together form two active sites. The protein fold is similar to serine proteases like trypsin, but a cysteine amino acid and a nearby Tectona grandis Linn (Teak), is locally known as Sagwan, belongs to Lamiaceae family. It is one of the most valuable timber in the world, due to its beautiful surface and its resistance to termite and fungal damage. The main active ingredient compounds that are responsible for these action are tectoquinone, lapachol and deoxylapachol. Naphthoquinones, anthraquinones and isoprenoid quinones are abundant metabolites in teak. In addition to these, teak contains several other phytochemicals such as triterpenoids, steroids, lignans, fatty esters and phenolic compounds. Pharmacologically, the plant has been investigated for antioxidant, anti-in ammatory, anti-pyretic, cytotoxic, analgesic, hypoglycemic, wound healing and antiplasmodial activities. Based on the above view, the aim of our study is to identify some naturally occurring product and evaluate its binding activity against against COVID-19 major protease through in silico molecular docking studies.

Methods
Glide docking uses the hypothesis of a rigid receptor although scaling of van der Waals radii of nonpolar atoms, which decreases penalties for close contacts, can be used to model a slight "give" in the receptor and/or ligand. Docking studies of designed compounds were carried out using grid-based ligand docking with energetics (GLIDE) module version 5.9. Schrödinger, LLC, New York, NY, 2013. The software package running on multiprocessor Linux PC. GLIDE has previously been validated and applied successfully to predict the binding orientation of many ligands.

Data sources
In this study, a dataset of active phytochemicals were obtained from FDA and Indian Medicinal Plants, Phytochemistry, and Therapeutics and pubchem database.
Protein structure preparation The X-ray crystal structures of COVID-19 major protease (PDB: 6LU7) (Prajapat et al., 2020) retrieved from the RCSB Protein Data Bank (https://www.rcsb.org/structure/6LU7) PDB is an archive for the crystal structures of biological macromolecules, worldwide (Jayaprakasha et al., 2002). Water molecules of crystallization were removed from the complex, and the protein was optimized for docking using the protein grounding and re nement utility provided by Schrödinger LLC.

Determination of Active Sites
The amino acids in the active site of a protein were determined using the Computed Atlas for Surface Topography of Proteins (CASTp) (http://sts.bioe.uic.edu/castp/index.html?201l) and Biovia Discovery Studio 4.5. The determination of the amino acids in the active site was used to analyze the Grid box and docking evaluation results. Discovery Studio is an o ine life sciences software that provides tools for protein, ligand, and pharmacophore modelling (Gopal Samy and Xavier, 2015).

Target protein and ligand preparation
The structures of energetic constituents of T. Grandis were constructed by means of the splinter dictionary of Maestro 9.3 (Schrodinger, LLC) using the optimized potentials for liquid simulations-all atom force eld with the steepest descent followed by curtailed Newton conjugate gradient protocol. The crystal structure of the above-mentioned targets was downloaded from the Protein Data Bank (PDB) and Pubchem databases. The selected protein targets were prepared for docking studies using the protein preparation wizard module in Schrodinger program (Maestro 9.3.). The preparation includes force eld parameters assignment, energy minimization and H-bond assignment. The energy minimized models of ligands obtained after molecular modeling studies were then prepared using ligprep module. Geometries of ligands was optimized using OPLS-2005 force eld and ionization generates possible states at target pH 7.0 ± 2.0

Receptor Grid preparation and Molecular Docking
All docking calculations were performed using the "extra precision" mode of GLIDE program. A receptor grid that de nes the speci c area of the protein to which the interaction of ligand has to be tested was de ned by the receptor grid generation module. The position of the co-crystal ligand de nes the Centre of the grid For the binding site, an assortment of energy grids was premeditated and stored, is distinct in terms of two concentric cubes: The bounding box, which must contain the center of any satisfactory ligand pose, and the enclosing box, which must contain all ligand atoms of an satisfactory pose, with a root mean square deviation of <0.5 Å and a maximum atomic displacement of <1.3 Å were eliminated as unneeded to increase assortment in the retained ligand poses. The scale factor for van der Waals radii was applied to those atoms with absolute partial charges ≤0.15 (scale factor of 0.8) and 0.25 (scale factor of 1.0) electrons for ligand and protein, respectively. Energy minimization protocol includes dielectric constant of 4.0 and 1000 steps of conjugate gradient. Upon end of each docking calculation, for the most part, 100 poses per ligand were generated. The most excellent docked structure be preferred using a GLIDE score (G-score) function (

ADME analysis
On the basis of canonical SMILES of the selected ligands obtained from pubchem, ADME properties of the studied compound were calculated using online Swiss ADME program. The major parameters for ADME associated properties such as Lipinski's rule of ve, the solubility of the drug, pharmacokinetic properties and drug likeliness were considered. The values of the observe properties are presented in Table 3.

Results And Discussion
Coronaviruses (CoVs) are the family of viruses containing single-stranded RNA (positivesense) which is encapsulated by a membrane envelope. They are classi ed in the Nidovirales order, Coronaviridae family, which is comprised of two sub-families and about 40 known species. These species are divided and characterized into four gene era (alpha, beta, gamma and delta), and only the alpha and beta-strains are identi ed to be pathogenic to human and other mammals. Bioinformatics is one of the most important and innovative approaches in the design and manufacture of new drugs. Due to the high cost of clinical and laboratory trials, the time consuming and the possibility of error, various bioinformatics techniques are nowadays used in the design of new drugs. Molecular docking, simulation, target point determination and chemical stability studies are the most important bioinformatics methods used in drug design. In the meantime, molecular docking of a special place in the process of designing new drugs, examining and comparing their e cacy enjoyable (Grinter and Zou, 2014; Mukesh and Rakesh, 2011). One of the novel therapeutic strategies for virus infection apart from the design and chemical synthesis of protease inhibitors is the search for inhibitors of this enzyme among natural compounds in order to obtain drugs with minimal side effects. T. grandis has variety of medicinal properties and traditional uses. Virtually every part of the teak tree has medicinal properties. The decoction of bark is used in bronchitis, hyperacidity, dysentery, verminosis, burning sensation, diabetes, di cult labor, leprosy and skin diseases (Vyas et al., 2019). It is important to know that, which secondary plant metabolites are found in plant as it may provide a basis for its traditional uses. During more than 100 years of intensive research on the chemistry of T. grandis, various compounds have been detected from different parts of the plant includes Quinones are major secondary metabolites and other common phytochemicals ( Table 1). The gure 1-7 shows the structures of the compounds that identi ed from the plant and selected for the in silico studies.  Heartwood (Rudman, 1960) 15. Anthraquinone-2carbaldehyde (C15H8O3) Heartwood (Rudman, 1960) 16. Anthraquinone-2-carboxylic acid (C15H8O4) Heartwood (Rudman, 1960) 17 Mpro, all the ligands were docked into the active site of COVID-19 Mpro. The docking result of these ligands is prearranged in Table 2. The interaction energy includes van der Waals energy, electrostatic energy, as well as intermolecular hydrogen bonding were calculated for each minimized complex. The docking score by means of GLIDE varied from -7.723 to -1.524 against COVID-19 major protease.
From the docking studies it is clear that all the compounds that are interacted at the active site of the COVID-19 Mpro ( gure 10). All the compounds are thermodynamically feasible and shows signi cant glide score and they bind the hydrophobic pocket of the active site. The molecular docking analysis in the present study showed the inhibitory potential of 10 selected compounds, ranked by a nity (ΔG); Barleriaquinone-I > Tectoquinone > Deoxylapachol > Quercitin > Evofolin B > Quinizarine > Munjistin > Grandiquinone A > Lapachol > 4-Methylquinoline.
Lipinski's rule of ve is a major criterion to evaluate drug likeliness and if a particular chemical compound with a certain biological and pharmacological activity has physical and chemical properties that would make it a likely orally active drug in humans. Lipinski's rule determines the molecular properties which are important for a drug's pharmacokinetics in the human body such as absorption, distribution, metabolism, and excretion (ADME). Lipinski's rule of ve criteria for an ideal drug are (i) a molecular mass less than 500 Daltons, (ii) no more than 5 hydrogen bond donors, (iii) no more than 10 hydrogen bond acceptors, (iv) an octanol-water partition coe cient log P not greater than 5. Three or more than 3 violations do not t into the criteria of drug likeliness and it is not considered in order to proceed with drug discovery. ADME studies of selected 27 compounds showed that out of 20 virtual hits were successful at passing through these ADME test lters (Table 3). This preliminary screening of potential molecules would help in providing the fast in-silico analysis towards development of therapeutics for COVID-19.
Due to technical limitations, Table 3 is provided in the Supplementary Files section.
The other targets for the selected compounds was done using SwissTargetPrediction method and it is based on the observation that similar bioactive molecules are more likely to share similar targets. Here the compounds showed high glide score for COVID-19 Mpro and also obeys the Lipinskis rule of ve was selected for the prediction of other targets. From the analysis of Barleriaquinone-I it has an 30% probability with proteases enzyme target class among them most predicted target was Leukocyte elastase ( gure 11) the other predicted targets with probability was given in the table 4. Table 5,6 and gure 11,12 shows the predicted targets for Tectoquinone and Deoxylapachol respectively. Tectoquinone targets phosphatases class and the most predicted target was dual speci city phosphatase Cdc25B were as Deoxylapachol targets Oxidoreductase class and predicted target was Monoamine oxidase B.

Conclusion
The rate of COVID-19 infection in China is declining and new shocking outbreaks are emerging in Italy, Indonesia, South Korea, India, middle east and Europe, with a major risk for a pandemic situation. The scienti c community is hence called for a collaborative and extraordinary effort for a rapid identi cation of an effective anti-COVID-19 drug. In this matter, we hope that our contribution through drug repurposing against target COVID-19 major protease of novel coronavirus (COVID-19) can be of great help in such a worldwide endeavor. In conclusion, we have a notorious molecules Barleriaquinone-I, Tectoquinone, Deoxylapachol, and Quercitin, an inventive drug candidate that was docked against COVID-19 major protease in a premeditated attempt to ascertain a new drug candidate, which is able to obstruct the diverse key target points of COVID-19 in treating novel corona virus. This compound Barleriaquinone-I, Tectoquinone, Deoxylapachol, and Quercitin well calculated as a best (lead) molecule and we necessitate design analogs, synthesis and evaluate its effectiveness against viral disease caused by COVID-19 through the molecular level and in vivo studies.  Chemical structures of terpenoids.

Figure 7
Chemical structures of apocarotenoids.   Molecular docking analysis between 6LU7 top 10 selected compounds from table 2.

Figure 10
Interaction of selected compounds at the active site of COVID-19 Mpro Figure 11 Predicted target group for Barleriaquinone-I Predicted target group for Tectoquinone Predicted target group for Deoxylapachol

Supplementary Files
This is a list of supplementary les associated with this preprint. Click to download. Table3.docx