Whole proteome screening and identification of potential epitopes of SARS-CoV-2 for vaccine design-an immunoinformatic, molecular docking and molecular dynamics simulation accelerated robust strategy

The coronavirus disease (COVID-19) pandemic has rapidly extended globally and killed approximately 5.83 million people all over the world. But, to date, no effective therapeutic against the disease has been developed. The disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and enters the host cell through the spike glycoprotein (S protein) of the virus. Subsequently, RNA-dependent RNA polymerase (RdRp) and main protease (Mpro) of the virus mediate viral transcription and replication. Mechanistically inhibition of these proteins can hinder the transcription as well as replication of the virus. Recently oxysterols and its derivative, such as 25 (S)-hydroxycholesterol (25-HC) has shown antiviral activity against SARS-CoV-2. But the exact mechanisms and their impact on RdRp and Mpro have not been explored yet. Therefore, the study aimed to identify the inhibitory activity of 25-HC against the viral enzymes RdRp and Mpro simultaneously. Initially, a molecular docking simulation was carried out to evaluate the binding activity of the compound against the two proteins. The pharmacokinetics (PK) and toxicity parameters were analyzed to observe the ‘drug-likeness’ properties of the compound. Additionally, molecular dynamics (MD) simulation was performed to confirm the binding stability of the compound to the targeted protein. Furthermore, molecular mechanics generalized Born surface area (MM-GBSA) was used to predict the binding free energies of the compound to the targeted protein. Molecular docking simulation identified low glide energy −51.0 kcal/mol and −35.0 kcal/mol score against the RdRp and Mpro, respectively, where MD simulation found good binding stability of the compound to the targeted proteins. In addition, the MM/GBSA approach identified a good value of binding free energies (ΔG bind) of the compound to the targeted proteins. Therefore, the study concludes that the compound 25-HC could be developed as a treatment and/or prevention option for SARS-CoV-2 disease-related complications. Although, experimental validation is suggested for further evaluation of the work. Communicated by Ramaswamy H. Sarma

The advent of Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of the Coronavirus Disease 2019 (COVID-19) pandemic, has impacted physical and mental health worldwide. The lack of effective antiviral drugs necessitates a robust therapeutic approach to develop anti-SARS-CoV-2 drugs. Various investigations have recognized ACE2 as the primary receptor of SARS-CoV-2, and this amalgamation of ACE2 with the spike protein of the coronavirus is paramount for viral entry into the host cells and inducing infection. Consequently, restricting the virus's accessibility to ACE2 offers an alternative therapeutic approach to averting this illness. The study aimed to identify potent inhibitors with enhanced affinity for the ACE2 protein and validate their stability and efficacy against established inhibitors via molecular docking, machine learning, and MD simulations. 202 ACE2 inhibitors (PDB ID and 6LZG), comprising repurposed antiviral compounds and specific ACE2 inhibitors, were selected for molecular docking. The two most effective compounds obtained from docking were further analyzed using machine learning to identify potential compounds with enhanced ACE2-binding affinity. To refine the dataset, molecular decoys were generated through the Database of Useful Decoys: Enhanced (DUD-E) server, and Singular Value Decomposition (SVD) was applied for data preprocessing. The Tree-based Pipeline Optimization Tool (TPOT) was then utilized to optimize the machine learning pipeline. The most promising ML-predicted compounds were re-evaluated through docking and subjected to Molecular Dynamics (MD) simulations to evaluate their structural stability and interactions with ACE2. Finally, these compounds were evaluated against the top two pre-established inhibitors using various computational tools. The two best pre-established inhibitors were identified as Birinapant and Elbasvir, while the best machine-learning-predicted compounds were PubChem ID: 23658468 and PubChem ID: 117637105. Pharmacophore studies were conducted on the most effective machine-learning-predicted compounds, followed by a comparative ADME/T analysis between the best ML-screened and pre-established inhibitors. The results indicated that the top ML compound (PubChem ID: 23658468) demonstrated favorable BBB permeability and a high HIA index, highlighting its potential for therapeutic applications. The ML-screened ligand demonstrated structural stability with an RMSD (0.24 nm) and greater global stability (Rg: 2.08 nm) than Birinapant. Hydrogen bonding interactions further validated their strong binding affinity. MM/PBSA analysis confirmed the ML-screened compound's stronger binding affinity, with a binding free energy of - 132.90 kcal/mol, indicating enhanced stability in complex formation. The results emphasize the efficacy of integrating molecular docking, machine learning, and molecular dynamics simulations in facilitating the rapid identification of novel inhibitors. PubChem ID: 23658468 demonstrates robust binding affinity to ACE2 and favorable pharmacokinetic properties, establishing it as a promising candidate for further investigation.

The RNA-dependent RNA polymerase (RdRp) is one of the crucial enzymes in severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) catalysing the replication of RNA, therefore acts as a potential target for antiviral drug design. The fixation of a ligand in the active site of RdRp may alter the SARS-CoV-2 life cycle. Present work aimed at identifying novel inhibitors of the SARS-CoV-2 RdRp enzyme by performing pharmacophore-based virtual screening, molecular docking and molecular dynamics simulation (MDS). Initially, the pharmacophore model of SARS-CoV-2 RdRp was constructed and the resulting model was used to screen compounds from ChEMBL, ZINC and PubChem databases. During the investigation, 180 compounds were screened using the above model and subjected to molecular docking with RdRp. Two compounds viz. ChEMBL1276156 and PubChem135548348 showed a strong binding affinity with RdRp than its standard inhibitor, Remdesivir. Toxicity prediction of these two compounds reveals their non-toxic nature. These compounds were further subjected to MDS for 100 ns to check their stability after binding with RdRp. The MDS of RdRp-ChEMBL1276156 and RdRp-PubChem135548348 complexes show enhanced stability in comparison to the RdRp-Remdesivir complex. The average interaction energy calculated after 100 ns of MDS was −146.56 and −172.68 KJ mol−1 for RdRp-CHEMBL1276156 complex and RdRp-PubChem135548348 complex, respectively, while −59.90 KJ mol−1 for RdRp-Remdesivir complex. The current investigation reveals that these two compounds are potent inhibitors of SARS-CoV-2 RdRp and they could be tested in the experimental condition to evaluate their efficacy against SARS-CoV-2. Communicated by Ramaswamy H. Sarma

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) encodes small envelope protein (E) that plays a major role in viral assembly, release, pathogenesis, and host inflammation. Previous studies demonstrated that pyrazine ring containing amiloride analogs inhibit this protein in different types of coronavirus including SARS-CoV-1 small envelope protein E (SARS-CoV-1 E). SARS-CoV-1 E has 93.42% sequence identity with SARS-CoV-2 E and shared a conserved domain NS3/small envelope protein (NS3_envE). Amiloride analog hexamethylene amiloride (HMA) can inhibit SARS-CoV-1 E. Therefore, we performed molecular docking and dynamics simulations to explore whether amiloride analogs are effective in inhibiting SARS-CoV-2 E. To do so, SARS-CoV-1 E and SARS-CoV-2 E proteins were taken as receptors while HMA and 3-amino-5-(azepan-1-yl)-N-(diaminomethylidene)-6-pyrimidin-5-ylpyrazine-2-carboxamide (3A5NP2C) were selected as ligands. Molecular docking simulation showed higher binding affinity scores of HMA and 3A5NP2C for SARS-CoV-2 E than SARS-CoV-1 E. Moreover, HMA and 3A5NP2C engaged more amino acids in SARS-CoV-2 E. Molecular dynamics simulation for 1 μs (1,000 ns) revealed that these ligands could alter the native structure of the proteins and their flexibility. Our study suggests that suitable amiloride analogs might yield a prospective drug against coronavirus disease 2019.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide has increased the importance of computational tools to design a drug or vaccine in reduced time with minimum risk. Earlier studies have emphasized the important role of RNA-dependent RNA polymerase (RdRp) in SARS-CoV-2 replication as a potential drug target. In our study, comprehensive computational approaches were applied to identify potential compounds targeting RdRp of SARS-CoV-2. To study the binding affinity and stability of the phytocompounds from Phyllanthus emblica and Aegel marmelos within the defined binding site of SARS-CoV-2 RdRp, they were subjected to molecular docking, 100 ns molecular dynamics (MD) simulation followed by post-simulation analysis. Furthermore, to assess the importance of features involved in the strong binding affinity, molecular field-based similarity analysis was performed. Based on comparative molecular docking and simulation studies of the selected phytocompounds with SARS-CoV-2 RdRp revealed that EBDGp possesses a stronger binding affinity (−23.32 kcal/mol) and stability than other phytocompounds and reference compound, Remdesivir (−19.36 kcal/mol). Molecular field-based similarity profiling has supported our study in the validation of the importance of the presence of hydroxyl groups in EBDGp, involved in increasing its binding affinity toward SARS-CoV-2 RdRp. Molecular docking and dynamic simulation results confirmed that EBDGp has better inhibitory potential than Remdesivir and can be an effective novel drug for SARS-CoV-2 RdRp. Furthermore, binding free energy calculations confirmed the higher stability of the SARS-CoV-2 RdRp-EBDGp complex. These results suggest that the EBDGp compound may emerge as a promising drug against SARS-CoV-2 and hence requires further experimental validation.

Respiratory infections, like the current COVID‐19 pandemic, target epithelial cells in the respiratory tract. Alveolar macrophages (AMs) are tissue‐resident macrophages located within the lung. They play a key role in the early phases of an immune response to respiratory viruses. AMs are likely the first immune cells to encounter SARS‐CoV‐2 during an infection, and their reaction to the virus will have a profound impact on the outcome of the infection. Interferons (IFNs) are antiviral cytokines and among the first cytokines produced upon viral infection. In this study, AMs from non‐infectious donors are challenged with SARS‐CoV‐2. We demonstrate that challenged AMs are incapable of sensing SARS‐CoV‐2 and of producing an IFN response in contrast to other respiratory viruses, like influenza A virus and Sendai virus, which trigger a robust IFN response. The absence of IFN production in AMs upon challenge with SARS‐CoV‐2 could explain the initial asymptotic phase observed during COVID‐19 and argues against AMs being the sources of pro‐inflammatory cytokines later during infection.

COVID-19 (Coronavirus disease 2019) is a transmissible disease initiated and propagated through a new virus strain SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) since 31st December 2019 in Wuhan city of China and the infection has outspread globally influencing millions of people. Here, an attempt was made to recognize natural phytochemicals from medicinal plants, in order to reutilize them against COVID-19 by the virtue of molecular docking and molecular dynamics (MD) simulation study. Molecular docking study showed six probable inhibitors against SARS-CoV-2 Mpro (Main protease), two from Withania somnifera (Ashwagandha) (Withanoside V [10.32 kcal/mol] and Somniferine [9.62 kcal/mol]), one from Tinospora cordifolia (Giloy) (Tinocordiside [8.10 kcal/mol]) and three from Ocimum sanctum (Tulsi) (Vicenin [8.97 kcal/mol], Isorientin 4′-O-glucoside 2″-O-p-hydroxybenzoagte [8.55 kcal/mol] and Ursolic acid [8.52 kcal/mol]). ADMET profile prediction showed that the best docked phytochemicals from present work were safe and possesses drug-like properties. Further MD simulation study was performed to assess the constancy of docked complexes and found stable. Hence from present study it could be suggested that active phytochemicals from medicinal plants could potentially inhibit Mpro of SARS-CoV-2 and further equip the management strategy against COVID-19-a global contagion. Highlights Holistic approach of Ayurvedic medicinal plants to avenge against COVID-19 pandemic. Active phytoconstituents of Ayurvedic medicinal plants Withania somnifera (Ashwagandha), Tinospora cordifolia (Giloy) and Ocimum sanctum (Tulsi) predicted to significantly hinder main protease (Mpro or 3Clpro) of SARS-CoV-2. Through molecular docking and molecular dynamic simulation study, Withanoside V, Somniferine, Tinocordiside, Vicenin, Ursolic acid and Isorientin 4′-O-glucoside 2″-O-p-hydroxybenzoagte were anticipated to impede the activity of SARS-CoV-2 Mpro. Drug-likeness and ADMET profile prediction of best docked compounds from present study were predicted to be safe, drug-like compounds with no toxicity. Communicated by Ramaswamy H. Sarma

Human coronavirus diseases, particularly severe acute respiratory syndrome coronavirus 2, still remain a persistent public health issue, and many recent studies are focusing on the quest for new leads against coronaviruses. To contribute to this growing pool of knowledge and explore the available marine natural products against coronaviruses, this study investigated the antiviral effects of fucoxanthin isolated from Sargassum siliquastrum—a brown alga found on Jeju Island, South Korea. The antiviral effects of fucoxanthin were confirmed in severe acute respiratory syndrome coronavirus 2-infected Vero cells, and its structural characteristics were verified in silico using molecular docking and molecular dynamic simulations and in vitro colorimetric method. Fucoxanthin inhibited the infection in a concentration-dependent manner, without showing cytotoxicity. Molecular docking simulations revealed that fucoxanthin binds to the angiotensinconverting enzyme 2-spike protein (binding energy -318.306 kcal mol<sup>-1</sup>) and main protease (binding energy -205.118 kcal mol<sup>-1</sup>). Moreover, molecular dynamic simulations showed that fucoxanthin remains docked to angiotensin-converting enzyme 2-spike protein for 20 ns, whereas it breaks away from main protease after 3 ns. Also, the in silico prediction of the fucoxanthin was verified through the in vitro colorimetric method by inhibiting the binding between angiotensinconverting enzyme 2 and spike protein in a concentration-dependent manner. These results indicate that fucoxanthin exhibits antiviral effects against severe acute respiratory syndrome coronavirus 2 by blocking the entry of the virus. Therefore, fucoxanthin from S. siliquastrum can be a potential candidate for treating coronavirus infection.

This study aims to explore the screening and mechanisms of action of traditional Chinese medicine(TCM) monomer compounds targeting transient receptor potential vanilloid 4(TRPV4) against severe acute respiratory syndrome coronavirus 2(SARS-CoV-2). Based on a machine learning method using the pre-trained protein language model ConPLex to predict drug-target binding properties, the study rapidly screened TRPV4-targeting TCM monomer compounds and ranked them by algorithm scores from highest to lowest. The cytotoxicity of candidate compounds was evaluated via cell counting kit-8(CCK-8), and the effects of glycycoumarin(GCM) on SARS-CoV-2 replication in African green monkey kidney cell line(Vero-E6) were analyzed through indirect immunofluorescence assay(IFA) and Western blot. A BALB/c mouse infection model with SARS-CoV-2/C57MA14 mouse-adapted strain was employed to assess the in vivo antiviral efficacy of GCM by examining the survival rate, pulmonary viral load, and pathological damage. To elucidate the molecular mechanism, Western blot was used to detect the protein expression of key signaling pathways, and enzyme-linked immunosorbent assay(ELISA) was applied to quantify concentrations of cytokines including interleu-kin-6(IL-6), tumor necrosis factor-alpha(TNF-α), C-X-C motif chemokine ligand 10(CXCL10), and monocyte chemoattractant protein-1(MCP-1) in serum. Molecular docking and molecular dynamics simulation techniques were employed to resolve the binding mode of GCM with the TRPV4 protein. In vitro experiments demonstrated that among 15 candidate compounds, GCM exhibited significant dose-dependent inhibition of SARS-CoV-2. In the animal model, the compound prolonged the survival time of infected mice and significantly alleviated virus-induced pulmonary pathological damage. Mechanistic studies revealed that GCM suppressed the TRPV4 expression, blocked nuclear translocation of nuclear factor kappa-B(NF-κB) triggered by SARS-CoV-2 infection, and subsequently downregulated the transcriptional level of pro-inflammatory factors such as IL-6 and TNF-α. Concurrently, the expression of IL-6, TNF-α, CXCL10, and MCP-1 in serum was markedly reduced after GCM intervention. The molecular docking and dynamics simulation confirmed that the GCM-TRPV4 compound exhibited excellent stability in both binding conformation and dynamic interactions. The study verified that GCM demonstrated potent anti-SARS-CoV-2 activity in both in vitro and in vivo models, effectively inhibiting viral replication while suppressing infection-induced cytokine storms. The results indicate that GCM is a highly promising anti-SARS-CoV-2 TCM monomer compound, which is worthy of further in-depth research and development.

The anti-SARS-CoV-2 activity of novel 9, 10-dihydrophenanthrene derivatives: an insight into molecular docking, ADMET analysis, and molecular dynamics simulation

Simple SummaryMolecular docking in conjunction with molecular dynamics simulation was accomplished as they extend an ample opportunity to screen plausible inhibitors of the main protease from Leucas zeylanica. The preferential phytochemicals were identified from L. zeylanica through gas chromatography–mass spectrometry (GC-MS). The pre-eminent three identified phytochemicals exhibited toxicity by no means during the scrutinization of ADME/T prominences. Moreover, pharmacologically distinguishing characteristics and the biological activity of the lead phytochemicals were satisfying as an antiviral drug contender. Additionally, the molecular dynamics simulation exhibited thermal stability and a stable binding affinity of the protein–compound complex that referred to the appreciable efficacy of lead optimization. Therefore, the preferable phytochemicals are worth substantial evaluation in the biological laboratory to recommend plausible antiviral drug candidates.Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a contemporary coronavirus, has impacted global economic activity and has a high transmission rate. As a result of the virus’s severe medical effects, developing effective vaccinations is vital. Plant-derived metabolites have been discovered as potential SARS-CoV-2 inhibitors. The SARS-CoV-2 main protease (Mpro) is a target for therapeutic research because of its highly conserved protein sequence. Gas chromatography–mass spectrometry (GC-MS) and molecular docking were used to screen 34 compounds identified from Leucas zeylanica for potential inhibitory activity against the SARS-CoV-2 Mpro. In addition, prime molecular mechanics–generalized Born surface area (MM-GBSA) was used to screen the compound dataset using a molecular dynamics simulation. From molecular docking analysis, 26 compounds were capable of interaction with the SARS-CoV-2 Mpro, while three compounds, namely 11-oxa-dispiro[4.0.4.1]undecan-1-ol (−5.755 kcal/mol), azetidin-2-one 3,3-dimethyl-4-(1-aminoethyl) (−5.39 kcal/mol), and lorazepam, 2TMS derivative (−5.246 kcal/mol), exhibited the highest docking scores. These three ligands were assessed by MM-GBSA, which revealed that they bind with the necessary Mpro amino acids in the catalytic groove to cause protein inhibition, including Ser144, Cys145, and His41. The molecular dynamics simulation confirmed the complex rigidity and stability of the docked ligand–Mpro complexes based on the analysis of mean radical variations, root-mean-square fluctuations, solvent-accessible surface area, radius of gyration, and hydrogen bond formation. The study of the postmolecular dynamics confirmation also confirmed that lorazepam, 11-oxa-dispiro[4.0.4.1]undecan-1-ol, and azetidin-2-one-3, 3-dimethyl-4-(1-aminoethyl) interact with similar Mpro binding pockets. The results of our computerized drug design approach may assist in the fight against SARS-CoV-2.

A novel coronavirus, known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), enters into the host cells through an interaction between its surface spike protein (S-protein) and the angiotensin-converting enzyme 2 receptors, leading to coronavirus disease 2019 (COVID-19). Using effective S-protein inhibitors may reduce the virulence of the virus. Molecular docking was performed to evaluate the binding affinity of 97 phenolic compounds (phenolics) with the SARS-CoV-2 S-protein receptor-binding domain (RBD). Molecular dynamics (MD) simulation was carried out to assess the stability of interactions between top-ranked compounds and S-protein RBD. Pharmacokinetics and toxicity of top-ranked inhibitors were also studied. Furthermore, the essential residues involved in ligand binding, based on the degree of each amino acid in the ligand-amino acid interaction (LAI) network for S-protein, were identified. Molecular docking and MD simulations were performed utilizing the AutoDock and Discovery Studio Client version, respectively. The LAI network was analyzed using the Cytoscape software. Pharmacokinetics and toxicity of top-ranked compounds were studied using bioinformatics webservers. It was estimated that nine of the studied phenolics can bind to the SARS-CoV-2 S-protein at the nanomolar scale with a considerable estimated energy of binding (∆G binding Keywords: COVID-19; drug; molecular docking; molecular dynamics; SARS-CoV-2; spike protein.

Background and objective: To recognize natural phytochemicals from medicinal plants, in order to reutilize them against COVID-19 by the virtue of molecular dynamics (MD) simulation study and molecular docking study COVID-19 is a transmissible disease that is initiated and propagated through a new virus strain SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2). Since 31st December 2019 in Wuhan city of China and the infection has outspread globally infecting many countries. Methods: Molecular dynamics MD simulation interaction analysis, Salt bridge analysis, Flexibility analysis, Ace-2- rbd complex electrostatic component of binding energy calculation method. Results: Molecular docking studies has shown to be having two inhibitors against SARS-CoV-2 Mpro (Main protease), from Withania somnifera (Ashwagandha) (Withanoside V [10.32 kcal/mol] and Somniferine [9.62 kcal/mol]). Inconsolably, SARS-CoV-2 infection in patients with pre-existing disease conditions (e.g., hypertension and diabetes) can cause severe complications and, as a result, mortality. Conclusion: Hence from the present study it could be suggested that, the active phytochemicals from medicinal plants could potentially inhibit Mpro of SARS-CoV-2 and further equip the management strategy against COVID-19-a global contagion. Active phytoconstituents of Ayurvedic medicinal plants Withania somnifera (Ashwagandha) predicted to significantly hinder main protease (Mpro or 3Clpro) of SARS-CoV-2.Through molecular docking and molecular dynamic simulation study, Withanoside V, Somniferine were observed to impede the activity of SARS-CoV-2 Mpro.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which causes COVID-19 disease has been exponentially increasing throughout the world. The mortality rate is increasing gradually as effective treatment is unavailable to date. In silico based screening for novel testable hypotheses on SARS-CoV-2 Mpro protein to discover the potential lead drug candidate is an emerging area along with the discovery of a vaccine. Administration of NO-releasing agents, NO inducers or the NO gas itself may be useful as therapeutics in the treatment of SARS-CoV-2. In the present study, a 3D structure of SARS-CoV-2 Mpro protein was used for the rational setting of inhibitors to the binding pocket of enzyme which proposed that phenyl furoxan derivative gets efficiently dock in the target pocket. Molecular docking and molecular dynamics simulations helped to investigate possible effective inhibitor candidates bound to SARS-CoV-2 Mpro substrate binding pocket. Molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) calculations revealed energetic contributions of active site residues of Mpro in binding with most stable proposed NO donor heterocyclic vasodilator inhibitor molecules. Furthermore, principal component analysis (PCA) showed that the NO donor heterocyclic inhibitor molecules 14, 16, 18 and 19 was strongly bound to catalytic core of SARS-CoV-2 Mpro protein, limiting its movement to form stable complex as like control. Thus, overall in silico investigations revealed that 5-oxopiperazine-2-carboxylic acid coupled furoxan derivatives was found to be key pharmacophore in drug design for the treatment of SARS-CoV-2, a global pandemic disease with a dual mechanism of action as NO donor and a worthwhile ligand to act as SARS-CoV-2 Mpro protein inhibitor. Communicated by Ramaswamy H. Sarma

Background: A significant worry for global public health is the international spread of the coronavirus disease-19 triggered through the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Herein, an attempt was performed to qualitative and quantitative analysis of a series of compounds against SARS-CoV-2 main protease (M<[pro]) by in silico studies. Methods: About one hundred anti-viral compounds were collected from DrugBank database. In the second stage, molecular docking simulation was carried out to identify interactions of the molecules with the key residues in the M<[pro] active site. Finally, the molecular dynamics simulation of four top-ranked compounds and X77 as Co-crystal ligand were investigated. Results:Based on molecular docking studies, four compounds DB00224, DB00220, DB01232 and DB08873 exhibited the best results among compounds against M<[pro] enzyme. Additionally, molecular dynamic simulation and free binding energy were accomplished to compute the interaction energies and stability of the top-ranked compounds at the active site. The binding energy portions of the compounds into the enzyme active site exposed that Van der Waals and non-polar interactions were fundamental factors in the molecule binding. The ligand connections were steadied via hydrophobic interactions and several key hydrogen bonds especially with Glu166 and His41 residues into the active site. Conclusion: According to calculations of docking and MD, it was observed that the active site is mostly hydrophobic, where the value of the ∆Evdw is higher than that of the ∆Eele. Additionally, the results showed the steady of selected ligands binding with SARS-CoV-2 M<[pro] active site.