Deciphering the interaction of puerarin with cancer macromolecules: An in silico investigation

Virtual screening and molecular dynamics simulations of phytochemicals targeting cofactor-independent phosphoglycerate mutase in antimicrobial-resistant Mycoplasma genitalium

Mycoplasma genitalium (M. genitalium) poses a significant challenge in clinical treatment due to its increasing antimicrobial resistance. This study investigates alternative therapeutic approaches by targeting the cofactor-independent phosphoglycerate mutase (iPGM) enzyme with phytochemicals derived from ethnobotanical plants. In silico screening identified several promising inhibitors, with 2-carboxy-D-arabinitol demonstrating the highest binding affinity (- 9.77 kcal/mol), followed by gluconic acid (- 9.03 kcal/mol) and citric acid (- 8.68 kcal/mol). Further analysis through molecular dynamics (MD) simulations revealed insights into the binding mechanisms and stability of these phytochemicals within the iPGM active site. The MD simulations indicated initial fluctuations followed by stability, with intermittent spikes in RMSD values. The lowest RMSF values confirmed the stability of the ligand-protein complexes. Key residues, including Ser-61, Arg-188, Glu-62, Asp-397, and Arg-260, were found to play crucial roles in the binding and retention of inhibitors within the active pocket. These findings suggest that the identified phytochemicals could serve as novel antimicrobial agents against M. genitalium by effectively inhibiting iPGM activity.

Puerarin Decreases the Expression of FUS-Dependent MAPK4 to Inhibit the Development of Triple-Negative Breast Cancer

Puerarin has been reported to have anticancer properties; however, its mechanism in regulating triple-negative breast cancer (TNBC) remains unclear. Cell function was assessed using a cell counting kit-8 assay, 5-ethynyl-2'-deoxyuridine assay, flow cytometry, and transwell assay. Additionally, the glucose assay kit, lactate assay kit, and ADP/ATP ratio assay kit were used to analyze glucose metabolism. mRNA and protein expression levels were analyzed using qRT-PCR and western blotting assays, respectively. The relationship between FUS RNA binding protein (FUS) and mitogen-activated protein kinase 4 (MAPK4) was determined using an RNA immunoprecipitation assay. TNBC cell malignancy in vitro was validated using a xenograft mouse model assay. Puerarin treatment or MAPK4 knockdown effectively inhibited TNBC cell proliferation, invasion, and glucose metabolism, and induced cell apoptosis. Additionally, puerarin treatment downregulated MAPK4 and FUS expression. Conversely, MAPK4 overexpression attenuated the effects of puerarin in TNBC cells. FUS stabilized MAPK4 mRNA expression in TNBC cells. Furthermore, puerarin decreased MAPK4 expression by downregulating FUS in TNBC cells. Finally, puerarin inhibited tumor formation in vivo. Puerarin inhibited TNBC development by decreasing the expression of FUS-dependent MAPK4, indicating that puerarin may serve as a promising therapeutic agent to hind TNBC.

Unveiling G-protein coupled receptor kinase-5 inhibitors for chronic degenerative diseases: Multilayered prioritization employing explainable machine learning-driven multi-class QSAR, ligand-based pharmacophore and free energy-inspired molecular simulation

GRK5 holds a pivotal role in cellular signaling pathways, with its overexpression in cardiomyocytes, neuronal cells, and tumor cells strongly associated with various chronic degenerative diseases, which highlights the urgent need for potential inhibitors. In this study, multiclass classification-based QSAR models were developed using diverse machine learning algorithms. These models were built from curated compounds with experimentally derived GRK5 inhibitory activity. Additionally, a pharmacophore model was constructed using active compounds from the dataset. Among the models, the SVM-based approach proved most effective and was initially used to screen DrugBank compounds within the applicability domain. Compounds showing significant GRK5 inhibitory potential underwent evaluation for key pharmacophoric features. Prospective compounds were subjected to molecular docking to assess binding affinity towards GRK5's key active site amino acid residues. Stability at the binding site was analyzed through 200 ns molecular dynamics simulations. MM-GBSA analysis quantified individual free energy components contributing to the total binding energy with respect to binding site residues. Metadynamics analysis, including PCA, FEL, and PDF, provided crucial insights into conformational changes of both apo and holo forms of GRK5 at defined energy states. The study identifies DB02844 (S-Adenosyl-1,8-Diamino-3-Thiooctane) and DB13155 (Esculin) as promising GRK5 inhibitors, warranting further in vitro and in vivo validation studies.

Virtual screening of FOXO3a activators from natural product-like compound library

FOXO3a is an inevitable transcription factor, which is involved in the regulation of biological processes such as proliferation, DNA damage repair, cell cycle arrest and cell death. Previous studies confirmed that FOXO3a is an excellent tumor suppressor and in cancer cells, it gets phosphorylated followed by proteasomal degradation. FOXO3a is found to be inactivated in cancer cells, whereas in normal cells it gets activated and upregulates its downstream targets, which induces apoptotic pathways. Hence, activation of FOXO3a can be implicated in cancer prevention and treatment. A variety of commercially available FOXO3a activators such as doxorubicin and metformin possess undesirable adverse effects to normal cells and tissues, which are their major limitations. Natural bioactive compounds, eliminating the limitations of such compounds, become an excellent choice for the treatment and prevention of cancer. In this study, a library of natural product-like compounds was screened for their FOXO3a activation potential through in silico approach, which included the use of several bioinformatics tools and processes. Other molecular interaction studies as well as binding and specificity studies were carried out with the help of molecular dynamics simulation. Virtual screening of 7700 small molecules from the Natural Products-like Compound Library revealed the top three FOXO3a activators F3385-6269, F2183-0033 and F3351-0330. Further validation studies are warranted to confirm these findings.

Based on Virtual Screening and Simulation Exploring the Mechanism of Plant-Derived Compounds with PINK1 to Postherpetic Neuralgia

Accumulating evidence strongly supports that PINK1 mutation can mediate mitochondrial autophagy dysfunction in dopaminergic neurons. This study was conducted to determine the role of PINK1 in the pathogenesis of postherpetic neuralgia (PHN) and find new targets for its treatment. A rigorous literature review was conducted to identify 2801 compounds from more than 200 plants in Asia. Virtual screening was used to shortlist the compounds into 20 groups based on their binding energies. MM/PBSA was used to further screen the compound dataset, and vitexin, luteoloside, and 2'-deoxyadenosine-5'-monophosphate were found to have a score of - 59.439, - 52.421, and - 47.544 kcal/mol, respectively. Pain behavioral quantification, enzyme-linked immunosorbent assay, quantitative polymerase chain reaction, western blotting, and transmission electron microscopy were used to confirm the effective mechanism. Vitexin had the most significant therapeutic effect on rats with PHN followed by luteoloside; 2'-deoxyadenosine-5'-monophosphate had no significant effect. Our findings suggested that vitexin could alleviate PHN by regulating mitochondrial autophagy through PINK1.

Beet leaf (beta vulgaris L.) extract attenuates iron-induced testicular toxicity: Experimental and computational approach

The purpose of this study was to investigate the protective effect of Beta vulgaris leaf extract (BVLE) on Fe2+-induced oxidative testicular damage via experimental and computational models. Oxidative testicular damage was induced via incubation of testicular tissue supernatant with 0.1 mM FeSO4 for 30 min at 37 °C. Treatment was achieved by incubating the testicular tissues with BVLE under the same conditions. The catalase (CAT), superoxide dismutase (SOD), glutathione (GSH), malondialdehyde (MDA), and nitric oxide (NO) levels, acetylcholinesterase (AChE), sodium-potassium adenosine triphosphatase (Na+/K + ATPase), ecto-nucleoside triphosphate diphosphohydrolase (ENTPDase), glucose-6-phosphatase (G6Pase), and fructose-1,6-bisphosphatase (F-1,6-BPase) were all measured in the tissues. We identified the bioactive compounds present using high-performance liquid chromatography (HPLC). Molecular docking and dynamic simulations were done on all identified compounds using a computational approach. The induction of testicular damage (p < 0.05) decreased the activities of GSH, SOD, CAT, and ENTPDase. In contrast, induction of testicular damage also resulted in a significant increase in MDA and NO levels and an increase in ATPase, G6Pase, and F-1,6-BPase activities. BVLE treatment (p < 0.05) reduced these levels and activities compared to control levels. An HPLC investigation revealed fifteen compounds in BVLE, with quercetin being the most abundant. The molecular docking and MDS analysis of the present study suggest that schaftoside may be an effective allosteric inhibitor of fructose 1,6-bisphosphatase based on the interacting residues and the subsequent effect on the dynamic loop conformation. These findings indicate that B. vulgaris can protect against Fe2+-induced testicular injury by suppressing oxidative stress, acetylcholinesterase, and purinergic activities while regulating carbohydrate dysmetabolism.

In-silico studies of Momordica charantia extracts as potential candidates against SARS-CoV-2 targeting human main protease enzyme (Mpro)

Momordica charintia, a well-known plant called bitter melon, has been shown to have antibacterial, anti-diabetic, and antiviral properties against HIV infection. The goal of this work was to investigate the inhibitory effect of phytocompounds found in Momordica charintia leaf extracts on SARS-CoV-2 3CL protease (also known as the Main protease, Mpro) utilizing GC-MS analysis and molecular docking studies. The Crystal Structure of the SARS-CoV-2 3CL protease in complex with an inhibitor N3 was downloaded from RCSB using PDB ID 6LU7 with resolution: 2.16 Å. In the present study, in silico molecular docking analysis of phytoconstituents present in M. charantia methanolic leaf extract detected by GC-MS was studied against SARS-CoV-2 Mpro. The results revealed 13 phytochemical constituents derived from the GC-MS analysis. Quercetin 3-galactopyranoside, Rutin, and Hyperin were ranked the highest with binding scores ranging from -8.9 kcal/mol to -8.5 kcal/mol compared with the standard, Nirmatrelvir, with a binding score of -7.7 kcal/mol. From the results obtained, it can be concluded that Quercetin 3-galactopyranoside, Rutin, and Hyperin act against Covid-19 by inhibiting the SARS-COV-2 Mpro and therefore can be further developed into potent drugs for Covid-19 treatment.

Synthesis, spectral characterization of pyrazole derived Schiff base analogs: molecular dynamic simulation, antibacterial and DNA binding studies

We have synthesized the pyrazole-bearing Schiff base derivatives (5a-5e) and (6a-6h) then the structural confirmation was supported by various spectral analyses. The antibacterial activity of all analogs was screened against bacterial strains Staphylococcus aureus, Bacillus subtilis, Enterococcus faecalis, Escherichia coli, Klebsiella pneumonieae and Pseudomonas aeruginosa. In comparison to the reference drug ciprofloxacin, the lead analogs 5c and 6c showed potent activity, with MIC values of 64 µg/mL against E. coli and B. subtilis. Compound 5c showed a moderate effect with a MIC value of 128 µg/mL against B. subtilis, P. aeruginosa and K. pneumonieae, while compound 6c was against E. coli and P. aeruginosa. Furthermore, the compounds 5c and 6c displayed groove binding mode towards CT-DNA by absorption, emission, competitive fluorescence studies using EtBr, CD and time-resolved fluorescence studies. Thermodynamic parameters of analogs 5c and 6c with CT-DNA were also calculated at 298, 303 and 308K temperatures by UV-visible spectroscopy. The molecular docking studies give the docking score for all compounds with PDB codes: 1BNA and 2XCT. The MD simulation study of analogs 5c and 6c was also carried out. The pharmacokinetic and ADME properties were calculated for all of the synthesized analogs (5a-5e) and (6a-6h).Communicated by Ramaswamy H. Sarma.

Computational and Preclinical Prediction of the Antimicrobial Properties of an Agent Isolated from Monodora myristica: A Novel DNA Gyrase Inhibitor

The African nutmeg (Monodora myristica) is a medically useful plant. We, herein, aimed to critically examine whether bioactive compounds identified in the extracted oil of Monodora myristica could act as antimicrobial agents. To this end, we employed the Schrödinger platform as the computational tool to screen bioactive compounds identified in the oil of Monodora myristica. Our lead compound displayed the highest potency when compared with levofloxacin based on its binding affinity. The hit molecule was further subjected to an Absorption, Distribution, Metabolism, Excretion (ADME) prediction, and a Molecular Dynamics (MD) simulation was carried out on molecules with PubChem IDs 529885 and 175002 and on three standards (levofloxacin, cephalexin, and novobiocin). The MD analysis results demonstrated that two molecules are highly compact when compared to the native protein; thereby, this suggests that they could affect the protein on a structural and a functional level. The employed computational approach demonstrates that conformational changes occur in DNA gyrase after the binding of inhibitors; thereby, this resulted in structural and functional changes. These findings expand our knowledge on the inhibition of bacterial DNA gyrase and could pave the way for the discovery of new drugs for the treatment of multi-resistant bacterial infections.

A Computational Approach to Elucidate the Interactions of Chemicals From Artemisia annua Targeted Toward SARS-CoV-2 Main Protease Inhibition for COVID-19 Treatment

The inhibitory potential of Artemisia annua, a well-known antimalarial herb, against several viruses, including the coronavirus, is increasingly gaining recognition. The plant extract has shown significant activity against both the Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and the novel SARS-CoV-2 that is currently ravaging the world. It is therefore necessary to evaluate individual chemicals of the plant for inhibitory potential against SARS-CoV-2 for the purpose of designing drugs for the treatment of COVID-19. In this study, we employed computational techniques comprising molecular docking, binding free energy calculations, pharmacophore modeling, induced-fit docking, molecular dynamics simulation, and ADMET predictions to identify potential inhibitors of the SARS-CoV-2 main protease (M^pro) from 168 bioactive compounds of Artemisia annua. Rhamnocitrin, isokaempferide, kaempferol, quercimeritrin, apigenin, penduletin, isoquercitrin, astragalin, luteolin-7-glucoside, and isorhamnetin were ranked the highest, with docking scores ranging from −7.84 to −7.15 kcal/mol compared with the −6.59 kcal/mol demonstrated by the standard ligand. Rhamnocitrin, Isokaempferide, and kaempferol, like the standard ligand, interacted with important active site amino acid residues like HIS 41, CYS 145, ASN 142, and GLU 166, among others. Rhamnocitrin demonstrated good stability in the active site of the protein as there were no significant conformational changes during the simulation process. These compounds also possess acceptable druglike properties and a good safety profile. Hence, they could be considered for experimental studies and further development of drugs against COVID-19.

Puerarin Attenuates Obesity-Induced Inflammation and Dyslipidemia by Regulating Macrophages and TNF-Alpha in Obese Mice

Obesity causes low-grade inflammation that results in dyslipidemia and insulin resistance. We evaluated the effect of puerarin on obesity and metabolic complications both in silico and in vivo and investigated the underlying immunological mechanisms. Twenty C57BL/6 mice were divided into four groups: normal chow, control (HFD), HFD + puerarin (PUE) 200 mg/kg, and HFD + atorvastatin (ATO) 10 mg/kg groups. We examined bodyweight, oral glucose tolerance test, serum insulin, oral fat tolerance test, serum lipids, and adipocyte size. We also analyzed the percentage of total, M1, and M2 adipose tissue macrophages (ATMs) and the expression of F4/80, tumor necrosis factor-α (TNF-α), C-C motif chemokine ligand 2 (CCL2), CCL4, CCL5, and C-X-C motif chemokine receptor 4. In silico, we identified the treatment-targeted genes of puerarin and simulated molecular docking with puerarin and TNF, M1, and M2 macrophages based on functionally enriched pathways. Puerarin did not significantly change bodyweight but significantly improved fat pad weight, adipocyte size, fat area in the liver, free fatty acids, triglycerides, total cholesterol, and HDL-cholesterol in vivo. In addition, puerarin significantly decreased the ATM population and TNF-α expression. Therefore, puerarin is a potential anti-obesity treatment based on its anti-inflammatory effects in adipose tissue.

Immunoinformatics design of a novel epitope-based vaccine candidate against dengue virus

Dengue poses a global health threat, which will persist without therapeutic intervention. Immunity induced by exposure to one serotype does not confer long-term protection against secondary infection with other serotypes and is potentially capable of enhancing this infection. Although vaccination is believed to induce durable and protective responses against all the dengue virus (DENV) serotypes in order to reduce the burden posed by this virus, the development of a safe and efficacious vaccine remains a challenge. Immunoinformatics and computational vaccinology have been utilized in studies of infectious diseases to provide insight into the host-pathogen interactions thus justifying their use in vaccine development. Since vaccination is the best bet to reduce the burden posed by DENV, this study is aimed at developing a multi-epitope based vaccines for dengue control. Combined approaches of reverse vaccinology and immunoinformatics were utilized to design multi-epitope based vaccine from the sequence of DENV. Specifically, BCPreds and IEDB servers were used to predict the B-cell and T-cell epitopes, respectively. Molecular docking was carried out using Schrödinger, PATCHDOCK and FIREDOCK. Codon optimization and in silico cloning were done using JCAT and SnapGene respectively. Finally, the efficiency and stability of the designed vaccines were assessed by an in silico immune simulation and molecular dynamic simulation, respectively. The predicted epitopes were prioritized using in-house criteria. Four candidate vaccines (DV-1-4) were designed using suitable adjuvant and linkers in addition to the shortlisted epitopes. The binding interactions of these vaccines against the receptors TLR-2, TLR-4, MHC-1 and MHC-2 show that these candidate vaccines perfectly fit into the binding domains of the receptors. In addition, DV-1 has a better binding energies of - 60.07, - 63.40, - 69.89 kcal/mol against MHC-1, TLR-2, and TLR-4, with respect to the other vaccines. All the designed vaccines were highly antigenic, soluble, non-allergenic, non-toxic, flexible, and topologically assessable. The immune simulation analysis showed that DV-1 may elicit specific immune response against dengue virus. Moreover, codon optimization and in silico cloning validated the expressions of all the designed vaccines in E. coli. Finally, the molecular dynamic study shows that DV-1 is stable with minimum RMSF against TLR4. Immunoinformatics tools are now applied to screen genomes of interest for possible vaccine target. The designed vaccine candidates may be further experimentally investigated as potential vaccines capable of providing definitive preventive measure against dengue virus infection.

Evaluation of selected carotenoids of Lycopersicon esculentum variants as therapeutic targets for 'Alzheimer's disease: an in silico approach

The seriousness and menace of the worldwide weight of 'Alzheimer's disease have been related to a few factors, which incorporate antioxidant system depletion, mutation of proteins, and high expression of cholinesterases due to aging, environmental influence, diet, infectious agents, and hormonal imbalance. Overexpression of cholinesterases has been emphatically connected to 'Alzheimer's disease because of the unreasonable hydrolysis of acetylcholine and butyrylcholine. Certain plant phytochemicals, for example, beta-carotenoids, lutein, neoxanthin, and viola-xanthine from Lycopersicon esculentum Mill. Var. esculentum (ESC) and Lycopersicon esculentum Mill. Var. cerasiforme (CER) has been utilized altogether as a therapeutic candidate for the treatment of 'Alzheimer's disease. Therefore, this research sought to investigate the drug-likeness of the individual carotenoids as detailed for cholinesterase inhibition in the treatment of 'Alzheimer's disease. Four potential cholinesterase inhibitors from ESC and CER were retrieved from the PubChem database. Investigation of their drug-likeness, toxicity prediction, molecular docking, and dynamic simulations were carried out using Molinspiration, PreADMET V.2.0, Patchdock server, and Schrodinger Maestro software respectively. Neoxanthin was ranked the safest with a greater tendency to inhibit the cholinesterases with high binding affinity. In addition, its stability after simulation in a mimicked biological environment suggests its relevance as a potential drug candidate for the treatment of 'Alzheimer's disease through the inhibition of cholinesterases.

Development of Effective Therapeutic Molecule from Natural Sources against Coronavirus Protease

The SARS-CoV-2 main protease (M^pro) is one of the molecular targets for drug design. Effective vaccines have been identified as a long-term solution but the rate at which they are being administered is slow in several countries, and mutations of SARS-CoV-2 could render them less effective. Moreover, remdesivir seems to work only with some types of COVID-19 patients. Hence, the continuous investigation of new treatments for this disease is pivotal. This study investigated the inhibitory role of natural products against SARS-CoV-2 M^pro as repurposable agents in the treatment of coronavirus disease 2019 (COVID-19). Through in silico approach, selected flavonoids were docked into the active site of M^pro. The free energies of the ligands complexed with M^pro were computationally estimated using the molecular mechanics-generalized Born surface area (MM/GBSA) method. In addition, the inhibition process of SARS-CoV-2 Mpro with these ligands was simulated at 100 ns in order to uncover the dynamic behavior and complex stability. The docking results showed that the selected flavonoids exhibited good poses in the binding domain of M^pro. The amino acid residues involved in the binding of the selected ligands correlated well with the residues involved with the mechanism-based inhibitor (N3) and the docking score of Quercetin-3-O-Neohesperidoside (−16.8 Kcal/mol) ranked efficiently with this inhibitor (−16.5 Kcal/mol). In addition, single-structure MM/GBSA rescoring method showed that Quercetin-3-O-Neohesperidoside (−87.60 Kcal/mol) is more energetically favored than N3 (−80.88 Kcal/mol) and other ligands (Myricetin 3-Rutinoside (−87.50 Kcal/mol), Quercetin 3-Rhamnoside (−80.17 Kcal/mol), Rutin (−58.98 Kcal/mol), and Myricitrin (−49.22 Kcal/mol). The molecular dynamics simulation (MDs) pinpointed the stability of these complexes over the course of 100 ns with reduced RMSD and RMSF. Based on the docking results and energy calculation, together with the RMSD of 1.98 ± 0.19 Å and RMSF of 1.00 ± 0.51 Å, Quercetin-3-O-Neohesperidoside is a better inhibitor of M^pro compared to N3 and other selected ligands and can be repurposed as a drug candidate for the treatment of COVID-19. In addition, this study demonstrated that in silico docking, free energy calculations, and MDs, respectively, are applicable to estimating the interaction, energetics, and dynamic behavior of molecular targets by natural products and can be used to direct the development of novel target function modulators.

Deciphering the Interactions of Bioactive Compounds in Selected Traditional Medicinal Plants against Alzheimer's Diseases via Pharmacophore Modeling, Auto-QSAR, and Molecular Docking Approaches

Neurodegenerative diseases, for example Alzheimer’s, are perceived as driven by hereditary, cellular, and multifaceted biochemical actions. Numerous plant products, for example flavonoids, are documented in studies for having the ability to pass the blood-brain barrier and moderate the development of such illnesses. Computer-aided drug design (CADD) has achieved importance in the drug discovery world; innovative developments in the aspects of structure identification and characterization, bio-computational science, and molecular biology have added to the preparation of new medications towards these ailments. In this study we evaluated nine flavonoid compounds identified from three medicinal plants, namely T. diversifolia, B. sapida, and I. gabonensis for their inhibitory role on acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and monoamine oxidase (MAO) activity, using pharmacophore modeling, auto-QSAR prediction, and molecular studies, in comparison with standard drugs. The results indicated that the pharmacophore models produced from structures of AChE, BChE and MAO could identify the active compounds, with a recuperation rate of the actives found near 100% in the complete ranked decoy database. Moreso, the robustness of the virtual screening method was accessed by well-established methods including enrichment factor (EF), receiver operating characteristic curve (ROC), Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC), and area under accumulation curve (AUAC). Most notably, the compounds’ pIC₅₀ values were predicted by a machine learning-based model generated by the AutoQSAR algorithm. The generated model was validated to affirm its predictive model. The best models achieved for AChE, BChE and MAO were models kpls_radial_17 (R² = 0.86 and Q² = 0.73), pls_38 (R² = 0.77 and Q² = 0.72), kpls_desc_44 (R² = 0.81 and Q² = 0.81) and these externally validated models were utilized to predict the bioactivities of the lead compounds. The binding affinity results of the ligands against the three selected targets revealed that luteolin displayed the highest affinity score of −9.60 kcal/mol, closely followed by apigenin and ellagic acid with docking scores of −9.60 and −9.53 kcal/mol, respectively. The least binding affinity was attained by gallic acid (−6.30 kcal/mol). The docking scores of our standards were −10.40 and −7.93 kcal/mol for donepezil and galanthamine, respectively. The toxicity prediction revealed that none of the flavonoids presented toxicity and they all had good absorption parameters for the analyzed targets. Hence, these compounds can be considered as likely leads for drug improvement against the same.

Inhibitory potential of repurposed drugs against the SARS-CoV-2 main protease: a computational-aided approach

The exponential increase in cases and mortality of coronavirus disease (COVID-19) has called for a need to develop drugs to treat this infection. Using in silico and molecular docking approaches, this study investigated the inhibitory effects of Pradimicin A, Lamivudine, Plerixafor and Lopinavir against SARS-CoV-2 M^pro. ADME/Tox of the ligands, pharmacophore hypothesis of the co-crystalized ligand and the receptor, and docking studies were carried out on different modules of Schrodinger (2019-4) Maestro v12.2. Among the ligands subjected to ADME/Tox by QikProp, Lamivudine demonstrated drug-like physico-chemical properties. A total of five pharmacophore binding sites (A3, A4, R9, R10, and R11) were predicted from the co-crystalized ligand and the binding cavity of the SARS-CoV-2 M^pro. The docking result showed that Lopinavir and Lamivudine bind with a higher affinity and lower free energy than the standard ligand having a glide score of -9.2 kcal/mol and -5.3 kcal/mol, respectively. Plerixafor and Pradimicin A have a glide score of -3.7 kcal/mol and -2.4 kcal/mol, respectively, which is lower than the co-crystallized ligand with a glide score of -5.3 kcal/mol. Molecular dynamics confirmed that the ligands maintained their interaction with the protein with lower RMSD fluctuations over the trajectory period of 100 nsecs and that GLU166 residue is pivotal for binding. On the whole, present study specifies the repurposing aptitude of these molecules as inhibitors of SARS-CoV-2 M^pro with higher binding scores and forms energetically stable complexes with M^pro.Communicated by Ramaswamy H. Sarma.