Revealing Potential Binding Affinity of FDA Approved Therapeutics Targeting Main Protease ( 3 CLpro ) in Impairing Novel Coronavirus ( SARS-CoV-2 ) Replication that Causes COVID-19

Department of Pharmacology and Toxicology, Centre for Laboratory Animal Technology and Research, Sathyabama Institute of Science and Technology, Jeppiaar Nagar, Rajiv Gandhi Road, Chennai, Tamil Nadu 600119, India; School of Technology, Pandit Deendayal Petroleum University, Gandhi Nagar, Gujarat 382007, India; Department of Pharmacology, Government Kilpauk Medical College, Chennai, Tamil Nadu 600010, India; Department of Microbiology, SRM Medical College hospital and Research Centre, Tamil Nadu 603211, India; Department of Internal Medicine, Sundaram Health Centre, Sholinghur, Tamil Nadu 632102, India


INTRODUCTION
Proteases group of enzyme operates at different paradigm in viral replication. A similar mechanism may be extended *Address correspondence to this author at the Department of Pharmacology and Toxicology, Centre for Laboratory Animal Technology and Research, Sathyabama Institute of Science and Technology, Jeppiaar Nagar, Rajiv Gandhi Road, Chennai, Tamil Nadu 600119, India; E-mail: sivaramand83@gmail.com for the prognosis of Severe Acute respiratory syndrome coronavirus (SARS-CoV) and for Middle-East respiratory syndrome coronavirus (MERS-CoV) [1]. Clinical features of COVID-19 demand minimum requirements for new drug entity that includes: minimization on viral load, effective control on cytokine storms, immune-boosting, stabilization of oxidative stress, etc. [2], [3].
It is well known that the SARS-CoV-2 virus exerts its pathogenicity by binding with the Angiotensin-converting enzyme 2 (ACE2) receptor. The outcome of several research has clearly implicated that S1 (trimeric protein) portion of the spike glycoprotein categorized as class I viral fusion protein actually initiates the process of ACE2 recognition and binding [4]. Sequential residual amino acids on S1 protein involved in mediating this anchoring procedure are known as receptor binding motif (RBM); either carboxyl or aminoterminal chains of S1 domain manage to bind with the recognition site of the receptor. In the next level, membrane fusion predominantly anchored by the S2 sub-unit present on the ectodomain part of spike glycoprotein [5].
Dissociation of the viral membrane unveils the pathogenic RNA into the host cytoplasm that propagates the sequence of a serious chain of the replication process. SARS-CoV-2 speculatively consists of an open reading frame (ORF) region genetically encoded with the gene responsible for nucleocapsid and spikes formation. Host cell ribosomes start the translation mechanism of converting ORF1a and ORF1ab into the respective polyprotein replicase (pp1a and pp1ab) [6]. Here, it comes to the role of 3-chymotrypsin-like protease (3CL pro), which catalyzes the cleavage of polyprotein to get16 nonstructural proteins (called nsp1-nsp16) [7]. These proteins are highly essential for viral replication and hence become a primary target for enzyme inhibitors. 3CL pro is considered to be the potential target for the researchers as it is responsible for processing the majority of the cleavage sites, proving that it is essential in the replication of coronavirus.
3CLpro shares a common sequential homology with the majority of human coronaviruses with respect to its architecture and functional groups. In perspective, the active site mediating the enzyme activity seems deeply buried inside the S1 pocket [8]. It is construed that the enzyme protein chain having a cohort of active sites, which include His 41, Phe 140, Gly 143, Cys 144, Cys 145, His 163, Glu 166 and His 172 assist the polyprotein that necessitates the replication process [9]. The paramount challenge, therefore, is to engage all the active sites in the helical chain in order to delay the replicating process. In-Silico molecular docking analysis provides reliable information pertaining to the binding tendency of the ligand on the core amino acid residue spread over the protein receptors. Molecular docking plays a vital role in the process of lead identification and optimization [10]. Hence, the present investigation is aimed at evaluating the enzyme inhibition potential of known FDA approved therapeutic molecules such as Emtricitabine, Oseltamivir, Ganciclovir, Chloroquine, Baricitinib, Favipiravir, Lopinavir, Ritonavir, Remdesivir, Ribavirin, Tenofovir, Umifenovir, Carbapenam, Ertapenem and Imipenam with respect to the significance on binding with core amino acid residue involved in mediating the viral polyprotein synthesis by SARS-CoV-2.

Protein-ligand Docking
The computational molecular investigation was performed using Auto Dock version 4 which predicts interaction binding affinity between selected therapeutic lead with that of the protein target COVID-19 main protease (3chymotrypsin-like protease (3CL pro)) -PDB-6LU7.

Protein Preparation
Three dimensional (3D) structure of COVID-19 main protease (3-chymotrypsin-like protease 3CL pro with protein data bank (PDB)-6LU7 (Fig. 1A) retrieved from Research Collaboratory for Structural Bioinformatics (RCSB). The protein structure was cleaned by removing the existing lead components, water molecules cleaved, Gasteiger charges computed with the inclusion of polar hydrogens, merging of non-polar and rotatable bonds, which were defined using Auto Dock4 [11].

Active Site Prediction on the Target Protein
Biologically active amino acid residues, which are primarily involved in cleavage and production of nonstructural proteins essential for viral replication were predicted using the Ramachandran plot, indicating localization of the residues on the target enzyme. Prediction by MolProbity server and also through literature survey [12] is shown in Fig. (1B).

Docking Simulations
Molecular docking analysis was performed using the licensed version of Auto Dock 4, which predicts interactions between FDA approved drug molecules with that of the selected protein target (Novel coronavirus 3-chymotrypsin-like protease (3CL pro). 3D structure of the main protease that is 3-chymotrypsin-like protease (3CL pro) with protein data bank (PDB)-6LU7 retrieved from Research Collaboratory for Structural Bioinformatics (RCSB). 3D componential structure of lead molecules and protein were docked using AutoDock analytical tool version 4. Affinity (grid) maps of 60×60×60 Å grid points and 0.375 Å spacing were generated using the Autogrid program. AutoDock parameter set-and distance-dependent dielectric functions were used in the calculation of the van der Waals and the electrostatic terms, respectively. Docking simulations were performed using the programmed algorithm inbuilt with pre automation in the software. Initial position, orientation, and torsions of the ligand molecules were set randomly. All rotatable torsions were released during docking. Each docking experiment was derived from 2 different runs that were set to terminate after a maximum of 250000 energy evaluations. The population size was set to 150. During the search, a translational step of 0.2 Å, and quaternion and torsion steps of 5 were applied [13,14].

ADME and Drug Likeness
Absorption, distribution, metabolism and elimination properties of all the lead molecules were investigated using Swiss ADMET (absorption, distribution, metabolism, excretion, and toxicity) web tool [15]. Druglikeness properties of all the leads subjected to Lipinski, Ghose rule of druglikeness. (http://www.swissadme.ch/index.php).

RESULTS AND DISCUSSION
Repurposing of drugs gains paramount importance in recent times as it accelerates the discovery of novel therapeutic applications of the existing drug molecules. It also reduces the latency of time required in driving the drug to the market since most of the approved drugs satisfies the demanding regulatory safety requirements. Authorities like the FDA already initiated the key process of repurposing programs to elucidate the new clinical significance of already approved drugs [15].
The computational analysis benefits the researcher in a screening library of compounds with suitable pharmacophore that offers significant interaction with the expected target. Virtual screening improves the understanding of orientation behavior of the ligand over selected protein in a lesser time period. Some of the significant investigational outcome from in-silico screening greatly helps in the transformation of leads to the next level of In-vitro studies and also on subsequent clinical evaluations. SARS and MERS-CoVs possess most pathogenic RNA that becomes a high epidemic in the recent health care crisis, which causes potential economic instability. These viruses are typically fond of certain nonstructural proteins for their survival and replication. 3CLpro is a class of proteases majorly involved in the release of sixteen nonstructural proteins [25]. Interaction sequential analy-sis proves that the amino acid Glu 166 possesses three potential functional groups, His 41 as a proton acceptor, His 163 and His 172 potentially determine the enzymatic action of 3CLpro, thereby binding of drugs with any of these potential amino acids has higher chances of enzyme inhibition [26].
Significant clinical investigations on repurposed drugs now shifted the COVID-19 therapy to the next level. The open-label trial involves 199 COVID-19 patients, in which, 99 were allocated for treatment with HIV protease inhibitors (lopinavir-ritonavir). Results of the study signify that a combination of lopinavir-ritonavir fails to provide an adequate cure in patients [27]. Whereas other trial involving 80 SARS-CoV-2 infected patients to compare the efficacy of favipiravir (RdRp inhibitor) and lopinavir-ritonavir reveals higher positive response in favipiravir treated group when compared to lopinavir-ritonavir treatment [28]. A retrospective comparative investigation between monotherapy (lopinavir-ritonavir) and combinational therapy (umifenovir + lopinavir-ritonavir) justifies that 75% of the cases under combinational therapy reveal favorable clinical response when compared to that of the monotherapy group with 35% of clinical response [29]. Another open labelled randomized trial involving 240 COVID-19 patients to ensure the efficacy of favipiravir (RdRp inhibitor) and umifenovir (antiinfluenza) reveals a higher level of clinical recovery in favipiravir (71.43%) when compared to that of the umifenovir (55.86%) treated patients [30].A versatile comparative invitro analysis made between hydroxychloroquine and chloroquine in SARS-CoV-2 infected cell lines witnessed a higher percentage of inhibition potential of hydroxychloroquine with an EC50 value of 0.72 μM in comparison with chloroquine with an EC50 value of 5.47 μM [31].
Docking calculations were carried out for an array of FDA approved molecules such as Emtricitabine, Oseltamivir, Ganciclovir, Chloroquine, Baricitinib, Favipiravir, Lopinavir, Ritonavir, Remdesivir, Ribavirin, Tenofovir, Umifenovir, Carbapenam, Ertapenem and Imipenam which have both specificity and selectivity in terms of binding efficiency against 3CL proenzyme. Comparatively, the compound Remdesivir ranks first in the series with a total of 8 strong molecular interactions with the amino acids on the active sites, followed by Tenofovir, Umifenovir, Ertapenem and Imipenam with a total of 7 interactions. Docking analysis further exemplifies the binding capacity of other molecules like Chloroquine, Lopinavir and Ritonavir with a total of 6 to 5 active interactions. Reports of present computational analysis clearly signify the efficiency of the selected ligands in the increasing order of binding capacity; Remde-sivir> Ertapenem>Imipenam>Tenofovir> Umifenovir> Chloroquine> Lopinavir>Ritonavir>Emtricitabine> Ganci-clovir> Baricitinib> Ribavirin>Oseltamivir>Favipiravir> Carbapenam, as shown in Table 1 and represented in Figs. (4 and 5).
Docking calculations were carried out for an array of FDA approved molecules such as Emtricitabine, Oseltamivir, Ganciclovir, Chloroquine, Baricitinib, Favipiravir, Lopinavir, Ritonavir, Remdesivir, Ribavirin, Tenofovir, Umifenovir, Carbapenam, Ertapenem and Imipenam, which have both specificity and selectivity in terms of binding efficiency against 3CL proenzyme. Comparatively, the compound Remdesivir ranks first in the series with a total of 9 strong molecular interactions with the amino acids on the active sites, followed by Tenofovir, Umifenovir, Ertapenem and Imipenam with a total of 7 interactions. Docking analysis further exemplifies the binding capacity of other molecules like Chloroquine, Lopinavir and Ritonavir with a total of 6 to 5 active interactions.
Results of the kinetic predictions clearly signify that most of the leads are not permeant through BBB, which denotes the level of safety index and also obeys the Lipinski rule of drug-likeness with not more than 2 violations. Further, most of the molecules are indicated with high GI absorption in elaborating the kinetic property of approved molecules, as shown in Table 2.

CONCLUSION
Emerging SARS-CoV-2 infection rates urge the need for a dynamic therapeutic strategy that has a tendency to halt the progression and adequately lowers the viral replication at the cellular level. Virtual screening offers a tremendous opportunity for the researcher in the process of lead identification and optimization. Molecular dynamic simulation models attain greater importance due to a high degree of reliability and confidence in revealing affinity on selective target. Further, simulation models reduce the actual time involved in the event of drug discovery. Results of the present investigation clearly depict that the FDA approved lead molecules such as Remdesivir, Ertapenem, Imipenam, Tenofovir Umifenovir and Chloroquine occupies a high priority in the scale of increasing binding affinity against the target enzyme 3CLpro. In conclusion, lead molecules from already approved sources provoke promising potential, which grabs the attention of the clinicians in availing potential therapeutic candidates as a drug of choice in the clinical management of COVID-19 time-dependently.

ETHICS APPROVAL AND CONSENT TO PARTICI-PATE
Not applicable.

HUMAN AND ANIMAL RIGHTS
No Animals/Humans were used for studies that are basis of this research.

CONSENT FOR PUBLICATION
Not applicable.

AVAILABILITY OF DATA AND MATERIALS
Not applicable.