key: cord-0873335-vel09q6p
authors: Adelusi, Temitope Isaac; Oyedele, Abdul-Quddus Kehinde; Monday, Ojo Emmanuel; Boyenle, Ibrahim Damilare; Idris, Mukhtar Oluwaseun; Ogunlana, Abdeen Tunde; Ayoola, Ashiru Mojeed; Fatoki, John Olabode; Kolawole, Oladipo Elijah; David, Kehinde Busuyi; Olayemi, Akintola Adebola
title: Dietary polyphenols mitigate SARS-CoV-2 main protease (Mpro) – Molecular Dynamics, Molecular Mechanics, and Density Functional Theory Investigations.
date: 2021-11-11
journal: J Mol Struct
DOI: 10.1016/j.molstruc.2021.131879
sha: 5a4da55016eb29bb36a158a3535539ae38b4fefd
doc_id: 873335
cord_uid: vel09q6p

The recent evolution of SARS-like Corona virus has ravaged the world. The deadly virus has claimed over millions of lives across the world and hence highlights the need to develop effective therapeutic drugs to contain the disease posed by this parasite. In this study, the inhibitory potential of fifty (50) dietary polyphenols against Coronavirus (SARS-CoV-2) main protease (Mpro) was conducted using Autodock Vina Molecular docking tool. In the virtual screening process, the binding affinity of Remdesivir (-7.7kcal/mol) currently used to treat COVID-19 patients was set as the cut-off value to screen out less probable inhibitors. Ellagic acid, Kievitone and Punicalin were the only promising ligands with binding affinity (-8.9kcal/mol, -8.0kcal/mol and -7.9kcal/mol respectively) lower than the set cut-off value. Furthermore, we validated Ellagic acid and Kievitone efficacy by subjecting them to molecular dynamics simulation and further stability was assessed at the molecular mechanics and quantum levels. The overall analysis indicates both compounds demonstrate higher stability and inhibitory potential to bind to the crucial His41 and Cys145 catalytic dyad of Mpro than the standard drug. However, further analysis of punicalin after evaluating its docking score was not conducted as the ligand pharmacokinetics properties suggests it could pose serious adverse effect to the health of participants in clinical trials. Hence, we employed a more safety approach by filtering out the compound during this study. Conclusively, while Ellagic acid and kievitone polyphenolic compounds have demonstrated to be promising under this in silico research, further studies are needed to substantiate their clinical relevance.

In this in silico-based research, we used ADMET profile, physicochemical properties analysis and molecular docking simulation to investigate some class of dietary polyphenols that could inhibit the viral growth of SAR-CoV-2 through the blocking of SARS-CoV-2 main protease 3CL (Mpro). We further subjected the selected compounds to 20ns all atoms molecular dynamics simulation to investigate their stability at the Mpro active pocket. Molecular mechanics MMPBSA method was used to calculate the free energy of the residues involved in the interaction of the selected compounds with Mpro while Quantum mechanical-Density Functional Theory (HOMO and LUMO) was exploited to calculate the energy donating and accepting potential of these compounds. Our aim is to investigate the compounds that could emerge and developed as potent nutraceuticals for the management/treatment of SARS-CoV-2 mediated Several reports of respiratory illness have been reported from Wuhan, Hubei province of China in December 2019, with confirmed evidence that the infections were caused by a novel coronavirus which was subsequently named SARS-COV-2 by World Health Organization (Huang et al.,2020; Guan et al., 2020; Dey et al., 2020; Wang et al., 2020) . The pathogenesis of SARS-COV-2 leads to a medical complication named COVID-19. This pathogen is a positivesense single-stranded RNA virus from the genus β-coronavirus. The outbreak of this disease has become a pandemic to the world and a serious health challenge to the public health organization, owing to an historical record of about two million death cases. It was primarily believed to have been the first host to infect human, thorough investigation has established SARS-COV-2 to be closely related to SARS-CoV which occurs in 2003 and MERS-CoV in 2012 (Guan et al., 2003; Ki, 2015; Azhar et al., 2014; Beigel et al., 2020) . Out of the different therapeutic drugs and vaccines that have been proposed to reduce high increase or spread of this coronavirus disease, only the broad spectrum nucleotide analogue prodrug remdesivir (Velour) was the first and only approved drug by the FDA for the treatment of SAR-CoV-2-induced COVID-19 for hospitalized adults and children of age 12 years and above weighing at least 40kg. In a research where 541 patients were assigned to Remdesivir and 521 to placebo, it was reported that Remdesivir was superior to placebo through the shortening of recovery time in COVID-19 infected hospitalized adults with evidence of lower respiratory tract infection (Beigel et al., 2020) , therefore, an urgent need to find effective natural anti-SARS-CoV-2 measures for the treatment/management of COVID-19 to alleviate the current global public health threat is the order of the day in the scientific world.

Persistent investigation of SARS-COV-2 genomics organization reveals that the viral genome has approximately 30kb with at least 14 open reading frames which is released into the cytoplasm (Kim et al., 2020; Hillen et al., 2020) . The ORF1a and ORF1ab encodes all nonstructural proteins, the remnant genes encode for the structural proteins; spike (S) protein, envelope (E) protein, membrane (M) protein and nucleocapsid (N) protein, and nine accessory factors which together function in the virion formation. Mostly, the nonstructural proteins are important for the replication and transcriptions of the virus and it has been observed that a slippery sequence UUUAAAC is present at the junction between ORF1a and ORF1ab in all coronaviruses. Translation begins at the end of the slippery sequence through a RNA-mediated ribosome frame shift. The ORF1a encodes the papain-like (PLpro) and which cleaves the replicates polypeptide to encode 16 non-structural proteins (NSPs) (Grum-Tokars et al., 2007) . It has been reported that 3CL-protease proteolytic activity is greater than the Papain-like protease by cleaving larger number (11) of sites within the polyprotein, hence it is regarded as the major proteolytic enzyme of SARS-COVs (Thiel et al., 2003; Harcourt et al., 2004) . The individual homo-dimeric protomers of SARS-COV2 Cysteine-like protease (Mpro) consist of three different domains: domain I consist of sequences between 8-101 amino acid residues, domain II is found at the region of 102-184 residues and sequence between 201-303 is made up of domain III . The domain I and II which contains the catalytic dyad (His41 and Cys145) at the formed cleft (Dai et al., 2020; Jin et al., 2020; Osman et al., 2020) are made up of β-sheet while the dominant structural motifs of domain III is α-helix . Crucially, Cys145 residue act as a nucleophile and has been identified as the major key player in the proteolytic activity of Mpro . Hence, targeting this residue has been identified as a major therapeutic strategy in the prevention of polyprotein processing and Viral maturation exhibited by the Mpro (Yan et al., 2003) . Interestingly, we have recently reported the essence of targeting relevant amino acid residue on protein targets in computer-aided drug discovery . In 2020, Jin and collaborators employed the use of Computeraided drug design (CADD) and X-ray crystallographic technique to elucidate the structure of Mpro bound with a mechanism-based inhibitor (N3) . This discovery as thus paves the way for researchers to investigate potential Mpro inhibitors from natural products/phytochemicals and clinically approved unrelated COVID-19 on Mpro (for drug repurposing) and other protein targets using in silico approach (Mazzini et al., 2020; Gurung et al., 2020; Das et al., 2020; Adelusi et al., 2021) .

Polyphenols majorly synthesized from phenylpropanoid pathways by plants are one of the phytochemicals which has been scientifically supported by nutritional and medicinal evidences as established functional foods or nutraceutical that makes the lines between foods and drugs to fade. They are polymeric unit of phenyl with more than a double phenyl rings with single or additional hydroxyl substituents. Food sources such as black tea, walnut, apples, blueberries, vegetables, almonds, spinach, tomatoes, parsley, leguminous plants, soy beans, cummoet, pomegranate, cherries, persimmons, rooibus tea, flex-seed etc., housed different subclasses of polyphenols in different proportions (Corcoran et al., 2012; Basheer and Kerem, 2015) . Long consumption of diet rich in polyphenol potentially prevent against infections and noncommunicable diseases such as lungs damage, neurodegenerative diseases, osteoporosis, pancreatitis and type-2 diabetes. Several scientific examinations have established that various polyphenol have anti-inflammatory, antioxidant, antiviral activities and also have effect in numerous cellular processes. Ellagitannins possess antiviral activities in particular against HIV infections (Martino et al., 2004) and manifest inhibitory effects on Epstein-Barr virus, HSV-1 and HSV-2. Ellagic acid and Kievitone have been found to possess antioxidant, anti-cancer and antiviral activities (Hoffman, 1995; Hayes et al., 2011; Park et al., 2014) . Pre-existing drugs have been used by scientist in both ligand-based and structural-based method to control the spread of COVID-19, however some of these drugs have been thus far had inappreciable effects on SARS-COV-2 which could be due to the suggestion that the viral proteins may have actively acquire mutations by single nucleotide polymorphisms (SNPs) and thus escape for being targeted by antiviral drugs. However, the use of natural product such as polyphenols may leverage this insurgence and could be a promiscuous therapeutic target against SARS-COV-2 proteins (Vankadari, 2020) .

The crystal structure of the SARS-COV-2 Main protease PDB ID: 6lu7 was harvested from the RCSB Protein Data Bank (http://www.rcsb.org). We validated the protein by checking the presence of missing hydrogens, side-chain abnormalities, iMproper bonds etc. The mechanism-based inhibitor (N3) which was co-crystallized with Mpro was removed from the protein before executing our docking protocols. The protein structures were inserted in Autodock Vina and the pdbqt format for each protein was generated (Trott and Olson, 2010) .

Binding pocket, ligands interactions and all amino acid residues in the active site of SARS-CoV-2 Mpro were determined with Computed Atlas for Surface Topography of Proteins (CASTp) (http://sts.bioe.uic.edu/castp/index.html?2011) and Biovia Discovery Studio (2019). Obtained data were compared and validated with previously reported experimental data for SARS-CoV-2 proteins.

We retrieve the canonical smiles for 3-hydroxyflavone, Apigenin, Baicelin, Caffeic acid, 

Further analyses were carried out using Autodock 4.2 for identifying specific interaction involved in binding of molecules to the target receptor. Subsequently, all the proteins were preprocessed and Gesteiger charges were added to it using AutoDock MGL tools 1.5.6. A receptor grid box was generated after the active sites had been defined. Grid box dimension of 60

x 60 x 60 for 3cl Mpro with spacing of 0.375Å centering on residue Cys145 and His41 was defined. The protein-ligand interactions were visualized by Discovery Studio and Pymol (Delano, 2002) .

An efficient and widely used computational server-Admetsar2

(https://lmmd.ecust.edu.cn/admetsar2/) was entrusted to perform ligand-based studies of the selected phytochemicals to ascertain the compound that may have the potential of qualifying to be a druggable lead compounds with the aim to reduce the viral pathogenesis. Diverse parameters under numerous rules were used to screen the pharmacokinetics and drug-likeness of these compounds (Pires et al., 2015; Yang et al., 2019) .

Prior to the 20ns production run of the three complexes (including the standard), GROMACS (GROningen MAchine for Chemical Simulations) Molecular dynamics operating environment (Van Der Spoel et al., 2005) was used to prepare the files for the simple dynamics normal control group "6LU7" and for the complexes which include 6LU7-Ela, 6LU7-Kie, and 6LU7-Rem. We used CHARMS-36 force field and TIP3P GROMACS recommended water model for the protein topology. CGENFF web server tool was used to prepare the ".str" file for the ligand topology after which the topology files of the complexes were appropriately updated using appropriate python codes to manually include ligands topology. We ionized and neutralized the systems and then solvated them using the simple point charge-216 explicit water model (spc216.gro). Energy minimization was run for 100ps (picoseconds) using steepest descent algorithm to establish a stable conformation for the system after which we equilibrated the system using Verlet algorithm from 0-310K at 100ps, 2fs (femtoseconds) time step for NVT, while Berenson algorithm at 2fs time step for 100ps was used for NPT equilibration. The system was treated using the "trjconv" module to centralize and compact the protein while we also made sure the atoms does not jump out of the PBC (Periodic Boundary Condition). RMSD (Root Mean Square Deviation) was calculated and reported as mean ± SD using the 2004 frames for each 20ns production step run for each complex using "gmx analyze" GROMACS module after which the H-bonds were also calculated using "xmgrace" module.

The Molecular Mechanics Poisson-Boltzmann surface area (MM-PBSA) method (Kollman et al., 2000) , implemented in the g_mmpbsa module (Kumari, 2014) of GROMACS, was used to compute the relative binding free energy of each complexes for the last 5ns trajectories. Xmgrace was then used to plot the graph spectrum of the individual contributing energy of the residues for the three complexes.

The Binding energies consist of the van der Waal forces, electrostatic interactions and the solvation energy while this solvation energy comprises of both polar and non-polar energies. The equation is defined below as:

Where BE = Binding Energy, VDW =Van Der Waal, PSE = Polar Solvation Energy, and SASA=Solvent Accessible Surface Area Energy

The top two compounds (hits) from the docking screening and the standard (Remdesivir) were subjected to quantum mechanical calculation using density functional theory. The Gaussian 09W

program (Frisch et al., 2009 ) was used for the calculations by optimizing the compounds' geometries at DFT/B3LYP/6-31G(d'p') levels. The frontiers orbital energies, the highest occupied molecular orbital (HOMO), the lowest occupied molecular orbital (LUMO), energy gap, and the molecular electrostatic potential were computed in order to understand the electron acceptor and electron donor properties of the compounds. These also provide information about the chemical reactivity and stability of the compounds.

Right here for the first time, we report the anti-SARS-CoV-2 potential of two polyphenols (Simon et al., 2016) , Ellagic acid could be considered as the best docked compound in this study.

Moreover, our result of conformational sampling of Ellagic acid and Kievitone against the Mpro molecular target also indicates that the phytocompounds binds efficiently with domain I and II of the receptor active site including the His41 and Cys145 catalytic dyad (Figure 1) . Although

Punicalin only interacts with Cys145, however, the ligand depicted similar mode of binding when docked with the receptor. Interestingly, similar mode of binding of these phytochemicals was also observed in the standard drug (Remdesivir) which was also found interacting with the crucial catalytic dyad of Mpro (Figure 1) . Several investigations which support our findings have been reported in the studies of Gurung and collaborators, Das and colleagues, Joshi and Coauthors and Islam et al (Gurung et al., 2020; Das et al., 2020; Joshi et al., 2020; Islam et al., 2021) . We believe the competitive binding of our hit compounds with His41 and Cys145 could be a potent therapeutic measure that could inhibit the SARS-COV2 Mpro catalytic activity. 

Computational drug-likeness test is done to facilitate the creation of new drug molecules, the molecules of which must comply with the criteria of the following five Lipinski's rule: molecular weight must not be greater than 500, number of hydrogen bond donors must not be greater than 5, number of hydrogen bond acceptors must not be more than 10 and lipophilicity (expressed in LogP) must not be greater than 5 (Lipinski et al., 2001) . Potential inhibitors with more than one violation of these rules are considered as molecules with poor absorption and low permeation properties (Benet et al., 2016) . The result of this study shown in table 2 In silico ADMET analysis is used to assess the pharmacokinetic and toxicological properties of hit compounds before experimental procedures (Jayaraj et al., 2020) . ADMET evaluation of compounds is crucial in determining whether a potential lead candidate is capable of passing through the clinical trials stage. Hence, it is imperative to perform ADMET test early during the drug discovery process in order to filter out small molecule inhibitors with unacceptable and poor pharmacological profile. Our result of pharmacokinetic predictions of Ellagic acid, Kievitone, Punicalin and the standard drug is represented in table 3.

Human intestinal absorption (HIA), substrate of P-glycoprotein and permeation through the blood-brain barrier (BBB) have been identified for the prediction of absorption and distribution properties of our drug candidates ( However, Kievitone and Remdesivir could act as substrate of p-glycoprotein and hence their distribution may be limited by the mediation of p-glycoprotein efflux (Prachayasittikul and Prachayasittikul, 2016) .

In the metabolism part, the families of Cytp450 have been identified as an important pharmacological parameter. According to Lynch, the inhibition of these protein families may result in drug-drug interaction and bio-accumulation (Lynch and Price, 2007) . According to our result, the only compound found inhibiting one or more of these metabolic enzymes is Kievitone.

The excretion of all drug candidates was also assessed in our ADMET study by carrying out the biodegradation test. Interestingly, all compounds including the standard could be easily excreted as they return a negative value for biodegradation.

Finally, the pharmacodynamic profile of the selected drug candidates was also assessed. It is important to note that the failure of drugs to pass through the clinical trials is majorly because of their non-acceptable toxicological profile and hence we have put into consideration the Ames mutagenicity, Acute oral toxicity, hERG inhibition, carcinogenicity and hepatotoxicity testing in this study ( 

Molecular dynamic is an in silico approach which is used to monitor the behavior and dynamics of binary protein-ligand complex at the atomistic level. Unlike molecular docking, MD simulation represents a more realistic delineation of the complex biological system by putting the flexibility of proteins, neutralizing ions and water environment into consideration. In this study, Ellagic acid (Ela), Kievitone (Kie) and Remdesivir (Rem) behaviour with the Mpro target (6LU7) was simulated by subjecting them in Molecular dynamics environment. The reason for dropping Punicalin (the 3 rd ranked inhibitor) for MD simulation is based on its poor pharmacodynamics and non-compliance with the rule of five (see table 3 and table 2 respectively) which could be detrimental to the health of clinical trial volunteers. In order to investigate and compare the stability of 6LU7-Ela, 6LU7-Kie with the standard (6LU7-Rem), the graph spectrums of the RMSD, RMSF, H-bond and ROG of the complexes have been superimposed as depicted in Figure 2 -5.

The RMSD backbone is used to assess the structural stability of protein-ligand complex and lower value of the ligand bound protein compared to the unbound form indicates a stable system (Liu et al., 2017) . The average RMSD values for 6LU7 (Apoprotein), 6LU7-Ela, 6LU7-Kie and 6LU7-Rem are 0.2981 ± 0.0552nm, 0.2171 ± 0.0267nm, 0.3230 ± 0.1366and 0.2692 ± 0.0433 respectively. From this result, the RMSD value of 6LU7-Ela is lower than the apoprotein and the standard (6LU7-Rem) hence it could be regarded as the most stable complex. The spectrum of the RMSD graph also suggests minimal perturbation in the dynamical conformation of the 6LU7-Ela complex (Figure 2 ). This finding may explain why Ellagic acid could not deviate away from its initial docked pose and the ruggedness to consistently bind to Mpro catalytic dyad residues. In the case of Kievitone dynamics with Mpro receptor, there is abrupt fluctuation of the RMSD spectrum between 0-10ns. However, after 10ns, stability of the complex was noticed as equilibrium was attained till the end of the 20ns production run (Figure 2 ). 

RMSF graph of the individual residues of the unbound and bound protein were also plotted to assess the flexibility of the amino acids. It is known that regions with very high RMSF values correspond mostly to the loop region which could also be involved in ligand binding and conformational alterations (Lee et al., 2012) . Interestingly, His41 (0.0787nm) and Cys145

(0.0546nm) catalytic dyad which are found at the loop region and believe to be critical for inhibition of Mpro were among the most stable residues of the apoprotein. Moreover, the binding of Ellagic acid, Kievitone and Remdesivir with 6LU7 return RMSF score of 0.1010 nm, 0.1141 nm and 0.0770 nm respectively for His41. The RMSF score of Cys145 for 6LU7-Ela, 6LU7-Kie and 6LU7-Rem are 0.0632 nm, 0.0583 nm and 0.0738 nm respectively (Figure 3 ). Since there were no significant variations in the RMSF values of these complexes when compared with apoprotein, we conclude that the catalytic dyad residues remain stabilized. Also, the average RMSF score of 6LU7-Ela (0.1147 ± 0.0501 nm) is lower than the apoprotein, 6LU7-Kie (0.10301 ± 0.1012nm) and 6LU7-Rem (0.1417 ± 0.0621) (see Figure 3) . Hence, it could be regarded as complex with the most stable residues. 

It is well known that intermolecular H-bond is important for maintaining the stability of proteinligand interaction. The higher the number of H-bond formed between a complex, the stronger their interaction (Menéndez et al., 2014) . In this research, 6LU7-Ela averaged intermolecular Hbond formation of 1.81 for the entire 20ns simulation run which is higher than 6LU7-Kie (1.04) and the standard (1.501) (Figure 4) . The H-bond result may explain why Ellagic acid demonstrate higher binding affinity and better stability with Mpro than both the standard (Remdesivir) and Kievitone.

The compactness of protein in a dynamical system can be monitored by computing their ROG values. A stably folded system could be measured by equilibration of its ROG spectrum throughout the simulation period while a non-compact system may be identified when there is abrupt fluctuation of ROG spectrum (Khoutoul et al., 2016) .

The low mean ROG values of 6LU7, 6LU7-Ela, 6LU7-Kie and 6LU7-Rem (2.2267 -2544 nm)

indicate minimal fluctuation of the complexes ( Figure 5) . Although, the unbound 6LU7 protein is the most compact structure according to its ROG spectrum, the minimum and maximum values of 6LU7-Ela (2.21002 nm-2.3001 nm) and 6LU7-Kie (2.20016 nm-2.23816 nm) may explain a reasonable well folded system. Importantly, the RMSD spectrum of both complexes suggest a better compact structure when compared with the standard which shows minimum and maximum ROG values of 2.2116 nm and 2.3913nm respectively. 

The individual decomposition energy of the residues and overall binding energies of the complexes have been represented in figure 6 and 

The molecular frontier orbitals are well-established parameters to provide information about the compounds' reactivity and stability. The highest occupied molecular orbital (HOMO) and the lowest occupied molecular orbital (LUMO) depict the electrons donating and receiving the compounds' ability. The energy gap, which is the difference between the LUMO and the HOMO, describes the kinetic stability and the intramolecular charge transfer. Also, compounds with significant energy gaps are referred to have low chemical reactivity and high kinetic stability. In contrast, compounds with low energy gaps are more reactive with low stability (Khoutoul et al., 2016) . The energy gap of the lead compounds increase accordingly: Ellagic acid (0.149 a.u) < Kevitone (0.161 a.u) < Remdesivir (0.175 a.u) ( Table 4 and Figure 6 ). Notwithstanding, the chemical hardness and softness were also computed from the frontier orbitals. Compounds with high chemical reactivity and low stability are considered to be soft (σ) (Gázquez, 1993) , and compounds with low reactivity and high stability are referred to as hard (η) (Kaya and Kaya, 2015 

In this study, we employed a computational approach with the use of molecular docking, molecular dynamics and Quantum mechanics to investigate the inhibitory potential of dietary polyphenols against SARS-COV-2 Mpro at the molecular and atomistic level. What we noticed from our findings is that, two of the screened ligands (Ellagic acid and Kievitone) could be potent competitive inhibitors of the coronavirus main protease. It is apparent from molecular dynamics and MMPBSA analysis that the binding of Ellagic acid to His41 and Cys145 catalytic dyad of the receptor (from the docked pose) forms a more stable system when compared to the standard drug. Our findings also revealed that Kievitone is capable of disrupting the proteolytic activity of Mpro and the analysis of MMPBSA and molecular orbital theory suggest that the drug candidate is slightly stable than Ellagic acid. We therefore propose that Ellagic acid and Kievitone be further developed as drug candidate for the treatment of COVID-19. Nonetheless, while these findings may be appreciable and appealing under in silico research, further experimental and clinical studies are needed to buttress their preclinical and clinical relevance respectively. In addition, functional foods endowed with kievitone and ellagic acid might be functional in the management/treatment of COVID-19 disease. Although, a global concern about making polyphenols functional foods is their high susceptibility towards metabolism which may impede their bioavailability index, this could be addressed by packing them into nanocarriers or through encapsulation mechanism for efficient delivery to their target site.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Authors declare no area of competing interest

Authors declare no area of interest 

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