SARS-CoV-2 and Angiotensin-Converting Enzyme-2 Receptor Interaction Blocker –an In-Silico Approach

The global COVID-19 pandemic, instigated by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has led to substantial morbidity and mortality on a worldwide scale. While COVID-19 vaccines offer hope, the emergence of mutated viral strains necessitates the development of FDA-approved drugs to address future outbreaks. Objective: To examine prospective antiviral medications through an analysis of the interaction between the spike protein of SARS-CoV-2 and Angiotensin-converting enzyme-2 (ACE-2) receptors, which play a pivotal role in facilitating viral entry into host cells. Methods: Molecular docking was employed to assess the binding a�nities of various protease inhibitors with ACE-2 receptors. Natural proteases, including Furin and Transmembrane serine protease 2 (TMPRSS2), cleave viral spike proteins into S1 and S2 subunits, facilitating fusion with ACE-2 receptors. We assessed the binding energies of Indinavir, Nafamostat, Fosamprenavir, Lopinavir, and Boceprevir to inhibit this interaction with a sense of optimism for their potential therapeutic applications. Results: Our �ndings suggest potential treatments for COVID-19, with Indinavir, Nafamostat, Fosamprenavir, Lopinavir, and Boceprevir displaying promising binding energies of -9.6 kcal/mol, -8.4 kcal/mol, -7.7 kcal/mol, and -7.5 kcal/mol, respectively. Conclusions: While promising, further clinical trials are important to potentially evaluate the e�cacy and safety of these proposed drugs in combating COVID-19 and its variants.

literally based on investigation of molecular interactions between the host cell and a pathogen system.The virus comes to the host cells, just like the rest of the spike proteins on SARS-CoV-2 take the main focus in vaccine development [4].Accordingly, these spike proteins, which are three dimensional in nature, facilitate the binding to and entry of the virus into the target cells by attaching to de nite host cell receptors.Among the sensors the Angiotensin-converting enzyme 2 (ACE-2) receptor has been discovered as the most suitable one which is responsible for the viral entrance to begin with.The lungs, heart, kidney and the intestinal tract being only few examples of the tissues and organs of which ACE-2 receptors are highly expressed [5].The virus life cycle of course is not complete without the interaction of the spike protein with the cellular receptor ACE-2 which was the initiator of the internal processes that lead to virus replication.The spike protein helps the virus link with ACE-2 and as a result, the cell membrane is fused with the virus, which then penetrates inside the cell.The toxinicity of the virus may be further emphasized by these ne-tuned molecular interactions that also serve as potential points of intervention for the therapeutic process [6].The advancements in the treatment options focusing on breaking the spike protein-ACE-2 resulting bridge has largely been made possible through the acquired understanding of the processes behind the connection.This task can be achieved by way of employing protease inhibitors to interrupt the cleavage of spike protein and consequently suppress its contact with the ACE-2 receptors.These inhibitors act through speci c processing proteases like Furin and Transmembrane serine protease 2 (TMPRSS2) and thus, they can be considered as potential antiviral drugs that can prevent the virus entering and reproducing inside the human [7].However, ligand-target protein interaction prediction is also an important method to be used in the drug development at this stage since it can predict the binding a nity between small molecules, or ligands, and target proteins [8].Using molecular docking we assess the a nity and speci city of possible drug candidates by imitating how protease chain inhibitors bind to the spike protein-ACE-2 association.Peptidase inhibitors are purposely evaluated, such as Indinavir, Nafamostat, and Fosamprenavir.They may also include Lopinavir and Boceprevir.These compounds could eventually restrict the inhibition of COVID-19 and thus minimize its severity.Meanwhile, the development of COVID-19 vaccinations brings a new chapter in its attack containment, with a possibility of reduced transmission and stable herd immunity.Variations of the virus, apart from their emergence, can overpower the established vaccine's e cacy in due course of time, and with it a timely

M E T H O D S
Computer-aided drug design tools were used to check the interaction of target protein (ACE-2 receptors) with ligands (protease inhibitors) after their retrieval from the protein data bank (PDB) and Pub-chem, as shown in a owchart in gure 2.

R E S U L T S Homology Modeling and Stability Validation
Protein with PDB id 6M0J was retrieved from Protein data dank.Figure 1 shows the 2D and 3D structures of protein.
Homology modeling was done to build accurate structural models of proteins.A Ramachandran plot generated to visualize energetically favorable regions for the backbone dihedral angles Phi against Psi of amino acid residues within the protein structure.The Ramachandran plot revealed that 96.80% of residues resided within the favored region.Additionally, the MolProbity score, a key indicator of protein quality statistics, was determined to be 2.62, representing the central MolProbity score (Figure 3)

Protein Retrieval
Protein Data Bank is a database for 3D structural data of proteins.These structures can be easily downloaded in PDB format and used wherever required.For the current study, the protein was retrieved from the Protein data bank with PDB id 6M0J, a crystal structure of spike proteins of the SARS-CoV-2 domain bound with ACE2 as it gains entry into the cell through ACE2 receptors.

Homology Modeling
An atomic resolution model of the target protein is made from an amino acid sequence and an experimental 3D structure of a related homologous protein through SWISS MODEL [13].

Domain Prediction
InterproScan was used for domain prediction of protein.
Inter-Pro Scan provides the functional analysis of proteins by their classi cation into families and prediction of domains and important sites.Ligand Retrieval Ligand was retrieved from PubChem.It is an open database of chemical molecules and their activities against biological assays, managed by the National Center for Biotechnology Information (NCBI).It contains small and larger molecules such as nucleotides, carbohydrates, lipids and chemically modi ed macromolecules.Camostat was used for SARS and MERS, but it caused some diseases.So, in the current study, we use different protease inhibitors belonging to different drug families.

Toxicity Prediction
Toxicity prediction of the drug was conducted through ADMET analysis to assess potential adverse effects during its action.This analysis evaluates the drug's absorption, distribution, metabolism, and excretion rates, as well as establishes quantitative structure-toxicity relationships.

Target Prediction
Target prediction was made to nd phenotypical side effects and cross-reactivity caused by small molecules.SWISS target prediction was used to estimate a small molecule's most probable molecular targets so it gets easier to predict which molecule would mostly act on it.

Molecular Docking
In order to identify the essential amino acid interactions between the protein and ligands, molecular docking is employed.The interactions of the ligands were characterized by scoring functions to predict the binding a nity with the receptor.Molecular docking was utilized to examine the interactions between drugs and SARS-CoV-2 spike proteins which are protease inhibitors.These protease inhibitors act as ligands in molecular docking.The binding energy values depict the best candidate for COVID-19.Before docking, the ligands and water molecules were eliminated from the protein utilizing Discovery Studio Visualizer.Protein-ligand interactions were assessed through docking employing AutoDock Vina.Polar hydrogens were incorporated into the protein, and a grid box was positioned at coordinates: Center_X = -26.873,Center_Y = 18.465, and Center_Z = -14.035,with dimensions Size_X, Y, Z = 26.Ligand torsions were set to 6, and both protein and ligand les were saved in PDBQT format.Docking was executed, and outcomes were visualized and presented using Discovery Studio Visualizer.Binding poses were evaluated based on binding energy in kcal/mol.-235, 242-263, 351-367, 379-399, 421-446, 456-483, 484-512 resemble the Peptidyldipeptidase A (M2) metalloprotease family.Residues from 1-598 resemble the Angiotensin-Converting Enzyme by PANTHER, and from 3-588 show resemblance with PEPTIDASE M2 by Pfam.It resembles Metallo-proteases ("zincins"), catalytic domain Superfamily from and with ANGIOTENSIN-CONVERTING ENZYME 2 by PANTHER from Ligand Retrieval Indinavir, Nafamostat, Fosamprenavir, Lopinavir and Boceprevir were retrieved from PubChem.The PubChem ID of these drugs with their 2D structures is given in Table 2.These are all protease inhibitors belonging to different families.

Target prediction
Swiss Target Prediction by (https://www.swisstargetprediction.ch) was logged on, and Canonical Smiles of Nafamostat were inserted for target prediction.The piechart for Nafamostat predicts 66.7% Proteases, the piechart for Indinavir 13.3 % for proteases, that for Fosamprenavir and Lopinavir 26.7% for proteases and that for Boceprivir 80.0% (Figure 4).

Figure
Figure Flow Chart of Steps for CADD COVID-19

Figure 3 :
Figure 3: 3D Structure of a Protein by Discovery StudioDomain Prediction of ProteinThe residues 1-598 resemble the Peptidase-M2 family by t h e I n te P ro fa m i l y.Re s i d u e s f ro m 1 0 -5 81 s h ow

Figure 4 :
Figure 4: Pie-charts for Target Prediction of DrugsMolecular DockingMolecular docking was conducted to assess the interactions between the protein and ligand.Polar hydrogens were added to the protein, and a grid box was positioned with the following coordinates: Center_X = -26.873,Center_Y = 18.465, and Center_Z = -14.035,with dimensions Size_X, Y, Z = 26.Ligand torsions were set to 6, and les of both the protein and ligand were saved in PDBQT format.Subsequently, docking was performed, and the results were visualized and analyzed using Discovery Studio Visualizer.The binding poses were evaluated based on the binding energy in kcal/mol.The ligand with the lowest energy score represented the most favorable interaction with the protein (shown in Figure5).

Figure 5 :
Figure 5: Docking Views Of Lowest Energy Ligands With Protein Are Shown, And Discovery Studio Shows A 2d View Of These Interactions

Table 1 :
Retrieved Ligand Information from PubChem