The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused over 1.4 million deaths worldwide. Repurposing existing drugs offers the fastest opportunity to identify new indications for existing drugs as a stable solution against coronavirus disease 2019 (COVID-19). The SARS-CoV-2 main protease (Mpro) is a critical target for designing potent antiviral agents against COVID-19. In this study, we identify potential inhibitors against COVID-19, using an amalgam of virtual screening, molecular dynamics (MD) simulations, and binding-free energy approaches from the Korea Chemical Bank drug repurposing (KCB-DR) database. The database screening of KCB-DR resulted in 149 binders. The dynamics of protein-drug complex formation for the seven top scoring drugs were investigated through MD simulations. Six drugs showed stable binding with active site of SARS-CoV-2 Mpro indicated by steady RMSD of protein backbone atoms and potential energy profiles. Furthermore, binding free energy calculations suggested the community-acquired bacterial pneumonia drug ceftaroline fosamil and the hepatitis C virus (HCV) protease inhibitor telaprevir are potent inhibitors against Mpro. Molecular dynamics and interaction analysis revealed that ceftaroline fosamil and telaprevir form hydrogen bonds with important active site residues such as Thr24, Thr25, His41, Thr45, Gly143, Ser144, Cys145, and Glu166 that is supported by crystallographic information of known inhibitors. Telaprevir has potential side effects, but its derivatives have good pharmacokinetic properties and are suggested to bind Mpro. We suggest the telaprevir derivatives and ceftaroline fosamil bind tightly with SARS-CoV-2 Mpro and should be validated through preclinical testing.

The novel coronavirus (SARS-CoV-2) outbreak has started taking away the millions of lives worldwide. Identification of known and approved drugs against novel coronavirus disease (COVID-19) seems to be an urgent need for the repurposing of the existing drugs. So, here we examined a safe strategy of using approved drugs of SuperDRUG2 database against modeled membrane protein (M-protein) of SARS-CoV-2 which is essential for virus assembly by using molecular docking-based virtual screening. A total of 3639 drugs from SuperDRUG2 database and additionally 14 potential drugs reported against COVID-19 proteins were selected. Molecular docking analyses revealed that nine drugs can bind the active site of M-protein with desirable molecular interactions. We therefore applied molecular dynamics simulations and binding free energy calculation using MM-PBSA to analyze the stability of the compounds. The complexes of M-protein with the selected drugs were simulated for 50 ns and ranked according to their binding free energies. The binding mode of the drugs with M-protein was analyzed and it was observed that Colchicine, Remdesivir, Bafilomycin A1 from COVID-19 suggested drugs and Temozolomide from SuperDRUG2 database displayed desirable molecular interactions and higher binding affinity towards M-protein. Interestingly, Colchicine was found as the top most binder among tested drugs against M-protein. We therefore additionally identified four Colchicine derivatives which can bind efficiently with M-protein and have better pharmacokinetic properties. We recommend that these drugs can be tested further through in vitro studies against SARS-CoV-2 M-protein.

Cervical cancer is the second most common cause of cancer deaths in women worldwide and remains the main reason of mortality among women of reproductive age in developing countries. Nitric oxide is involved in several physiological functions inclusive of inflammatory and immune responses. However, the function of NO in tumor biology is debatable. The inducible NOS (iNOS/NOS2) isoform is the one responsible to maintain the levels of NO, and it exhibits pleotropic effects in various cancers with concentration-dependent pro- and anti-tumor effects. iNOS triggers angiogenesis and endothelial cell migration in tumors by regulating the levels of vascular endothelial growth factor (VEGF). In drug discovery, drug repurposing involves investigations of approved drug candidates to treat various other diseases. In this study, we used anti-cancer drugs and small molecules to target iNOS and identify a potential selective iNOS inhibitor. The structures of ligands were geometrically optimized and energy minimized using Hyperchem software. Molecular docking was performed using Molegro virtual docker, and ligands were selected based on MolDock score, Rerank score, and H-bonding energy. In the study shown, venetoclax compound demonstrated excellent binding affinity to iNOS protein. This compound exhibited the lowest MolDock score and Rerank score with better H-bonding energy to iNOS. The binding efficacy of venetoclax was analyzed by performing molecular docking and molecular dynamic simulations. Multiple parameters were used to analyze the simulation trajectory, like root mean square deviation (RMSD), radius of gyration (Rg), and hydrogen bond interactions. Based on the results, venetoclax emerges to be a promising potential iNOS inhibitor to curtail cervical cancer progression.

Drug resistance is a core issue in cancer chemotherapy. A known folate antagonist, methotrexate (MTX) inhibits human dihydrofolate reductase (hDHFR), the enzyme responsible for the catalysis of 7,8-dihydrofolate reduction to 5,6,7,8-tetrahydrofolate, in biosynthesis and cell proliferation. Structural change in the DHFR enzyme is a significant cause of resistance and the subsequent loss of MTX. In the current study, wild type hDHFR and double mutant (engineered variant) F31R/Q35E (PDB ID: 3EIG) were subject to computational study. Structure-based pharmacophore modeling was carried out for wild type (WT) and mutant (MT) (variant F31R/Q35E) hDHFR structures by generating ten models for each. Two pharmacophore models, WT-pharma and MT-pharma, were selected for further computations, and showed excellent ROC curve quality. Additionally, the selected pharmacophore models were validated by the Guner-Henry decoy test method, which yielded high goodness of fit for WT-hDHFR and MT-hDHFR. Using a SMILES string of MTX in ZINC15 with the selections of 'clean', in vitro and in vivo options, 32 MTX-analogs were obtained. Eight analogs were filtered out due to their drug-like properties by applying absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessment tests and Lipinski's Rule of five. WT-pharma and MT-pharma were further employed as a 3D query in virtual screening with drug-like MTX analogs. Subsequently, seven screening hits along with a reference compound (MTX) were subjected to molecular docking in the active site of WT- and MT-hDHFR. Through a clustering analysis and examination of protein-ligand interactions, one compound was found with a ChemPLP fitness score greater than that of MTX (reference compound). Finally, a simulation of molecular dynamics (MD) identified an MTX analog which exhibited strong affinity for WT- and MT-hDHFR, with stable RMSD, hydrogen bonds (H-bonds) in the binding site and the lowest MM/PBSA binding free energy. In conclusion, we report on an MTX analog which is capable of inhibiting hDHFR in wild type form, as well as in cases where the enzyme acquires resistance to drugs during chemotherapy treatment.

Progeria is a rare genetic disorder characterized by premature aging that eventually leads to death and is noticed globally. Despite alarming conditions, this disease lacks effective medications; however, the farnesyltransferase inhibitors (FTIs) are a hope in the dark. Therefore, the objective of the present article is to identify new compounds from the databases employing pharmacophore based virtual screening. Utilizing nine training set compounds along with lonafarnib, a common feature pharmacophore was constructed consisting of four features. The validated Hypo1 was subsequently allowed to screen Maybridge, Chembridge, and Asinex databases to retrieve the novel lead candidates, which were then subjected to Lipinski's rule of 5 and ADMET for drug-like assessment. The obtained 3,372 compounds were forwarded to docking simulations and were manually examined for the key interactions with the crucial residues. Two compounds that have demonstrated a higher dock score than the reference compounds and showed interactions with the crucial residues were subjected to MD simulations and binding free energy calculations to assess the stability of docked conformation and to investigate the binding interactions in detail. Furthermore, this study suggests that the Hits may be more effective against progeria and further the DFT studies were executed to understand their orbital energies.

Breast cancer is one of the leading causes of death noticed in women across the world. Of late the most successful treatments rendered are the use of aromatase inhibitors (AIs). In the current study, a two-way approach for the identification of novel leads has been adapted. 81 chemical compounds were assessed to understand their potentiality against aromatase along with the four known drugs. Docking was performed employing the CDOCKER protocol available on the Discovery Studio (DS v4.5). Exemestane has displayed a higher dock score among the known drug candidates and is labeled as reference. Out of 81 ligands 14 have exhibited higher dock scores than the reference. In the second approach, these 14 compounds were utilized for the generation of the pharmacophore. The validated four-featured pharmacophore was then allowed to screen Chembridge database and the potential Hits were obtained after subjecting them to Lipinski's rule of five and the ADMET properties. Subsequently, the acquired 3,050 Hits were escalated to molecular docking utilizing GOLD v5.0. Finally, the obtained Hits were consequently represented to be ideal lead candidates that were escalated to the MD simulations and binding free energy calculations. Additionally, the gene-disease association was performed to delineate the associated disease caused by CYP19A1.

Raf kinase inhibitory protein (RKIP) is an essential regulator of the Ras/Raf-1/MEK/ERK signaling cascade and functions by directly interacting with the Raf-1 kinase. The abnormal expression of RKIP is linked with numerous diseases including cancers, Alzheimer's and diabetic nephropathy. Interestingly, RKIP also plays an indispensable role as a tumor suppressor, thus making it an attractive therapeutic target. To date, only a few small molecules have been reported to modulate the activity of RKIP, and there is a need to explore additional scaffolds. In order to achieve this objective, a pharmacophore model was generated that explores the features of locostatin, the most potent RKIP modulator. Correspondingly, the developed model was subjected to screening, and the mapped compounds from Marine Natural Products (MNP) library were retrieved. The mapped MNPs after ensuing drug-likeness filtration were escalated for molecular docking, where locostatin was regarded as a reference. The MNPs exhibiting higher docking scores than locostatin were considered for molecular dynamics simulations, and their binding affinity towards RKIP was computed via MM/PBSA. A total of five molecules revealed significantly better binding free energy scores than compared to locostatin and, therefore, were reckoned as hits. The hits from the present in silico investigation could act as potent RKIP modulators and disrupt interactions of RKIP with its binding proteins. Furthermore, the identification of potent modulators from marine natural habitat can act as a future drug-discovery source.

Non-small cell lung cancer (NSCLC) is a lethal non-immunogenic malignancy and proto-oncogene ROS-1 tyrosine kinase is one of its clinically relevant oncogenic markers. The ROS-1 inhibitor, crizotinib, demonstrated resistance due to the Gly2032Arg mutation. To curtail this resistance, researchers developed lorlatinib against the mutated kinase. In the present study, a receptor-ligand pharmacophore model exploiting the key features of lorlatinib binding with ROS-1 was exploited to identify inhibitors against the wild-type (WT) and the mutant (MT) kinase domain. The developed model was utilized to virtually screen the TimTec flavonoids database and the retrieved drug-like hits were subjected for docking with the WT and MT ROS-1 kinase. A total of 10 flavonoids displayed higher docking scores than lorlatinib. Subsequent molecular dynamics simulations of the acquired flavonoids with WT and MT ROS-1 revealed no steric clashes with the Arg2032 (MT ROS-1). The binding free energy calculations computed via molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) demonstrated one flavonoid (Hit) with better energy than lorlatinib in binding with WT and MT ROS-1. The Hit compound was observed to bind in the ROS-1 selectivity pocket comprised of residues from the β-3 sheet and DFG-motif. The identified Hit from this investigation could act as a potent WT and MT ROS-1 inhibitor.

The ability to identify the site of a protein that can bind with high affinity to small, drug-like compounds has been an important goal in drug design. Sirtuin 2 (SIRT2), histone deacetylase protein family, plays a central role in the regulation of various pathways. Hence, identification of drug for SIRT2 has attracted great interest in the drug discovery community. To elucidate the molecular basis of the small molecules interactions to inhibit the SIRT2 function we employed the molecular docking, molecular dynamics simulations, and the molecular mechanism Poisson-Boltzmann/surface area (MM-PBSA) calculations. Five well know inhibitors such as suramin, mol-6, sirtinol, 67, and nf675 were selected to establish the nature of the binding mode of the inhibitors in the SIRT2 active site. The molecular docking and dynamics simulations results revealed that the hydrogen bonds between Arg97 and Gln167 are crucial to inhibit the function of SIRT2. In addition, the MM-PBSA calculations revealed that binding of inhibitors to SIRT2 is mainly driven by van der Waals/non-polar interactions. Although the five inhibitors are very different in structure, shape, and electrostatic potential, they are able to fit in the same binding pocket. These findings from this study provide insights to elucidate the binding pattern of SIRT2 inhibitors and help in the rational structure-based design of novel SIRT2 inhibitors with improved potency and better resistance profile.

The rapid spread of COVID-19, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a worldwide health emergency. Unfortunately, to date, a very small number of remedies have been to be found effective against SARS-CoV-2 infection. Therefore, further research is required to achieve a lasting solution against this deadly disease. Repurposing available drugs and evaluating natural product inhibitors against target proteins of SARS-CoV-2 could be an effective approach to accelerate drug discovery and development. With this strategy in mind, we derived Marine Natural Products (MNP)-based drug-like small molecules and evaluated them against three major target proteins of the SARS-CoV-2 virus replication cycle. A drug-like database from MNP library was generated using Lipinski's rule of five and ADMET descriptors. A total of 2,033 compounds were obtained and were subsequently subjected to molecular docking with 3CLpro, PLpro, and RdRp. The docking analyses revealed that a total of 14 compounds displayed better docking scores than the reference compounds and have significant molecular interactions with the active site residues of SARS-CoV-2 virus targeted proteins. Furthermore, the stability of docking-derived complexes was analyzed using molecular dynamics simulations and binding free energy calculations. The analyses revealed two hit compounds against each targeted protein displaying stable behavior, binding affinity, and molecular interactions. Our investigation identified two hit compounds against each targeted proteins displaying stable behavior, higher binding affinity and key residual molecular interactions, with good in silico pharmacokinetic properties, therefore can be considered for further in vitro studies.

3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) is a rate-controlling enzyme in the mevalonate pathway which involved in biosynthesis of cholesterol and other isoprenoids. This enzyme catalyzes the conversion of HMG-CoA to mevalonate and is regarded as a drug target to treat hypercholesterolemia. In this study, ten qualitative pharmacophore models were generated based on chemical features in active inhibitors of HMGR. The generated models were validated using a test set. In a validation process, the best hypothesis was selected based on the statistical parameters and used for virtual screening of chemical databases to find novel lead candidates. The screened compounds were sorted by applying drug-like properties. The compounds that satisfied all drug-like properties were used for molecular docking study to identify their binding conformations at active site of HMGR. The final hit compounds were selected based on docking score and binding orientation. The HMGR structures in complex with the hit compounds were subjected to 10 ns molecular dynamics simulations to refine the binding orientation as well as to check the stability of the hits. After simulation, binding modes including hydrogen bonding patterns and molecular interactions with the active site residues were analyzed. In conclusion, four hit compounds with new structural scaffold were suggested as novel and potent HMGR inhibitors.

Progeria is a globally noticed rare genetic disorder manifested by premature aging with no effective treatment. Under these circumstances, farnesyltransferase inhibitors (FTIs) are marked as promising drug candidates. Correspondingly, a pharmacophore model was generated exploiting the features of lonafarnib. The selected pharmacophore model was allowed to screen the InterBioScreen natural compound database to retrieve the potential lead candidates. A series of filtering steps were applied to assess the drug-likeness of the compounds. The obtained compounds were advanced to molecular docking employing the CDOCKER module available with Discovery Studio (DS). Subsequently, three compounds (Hits) have displayed a higher dock score and demonstrated key residue interactions with stable molecular dynamics simulation results compared to the reference compound. Taken together, we therefore put forth three identified Hits as FTIs that may further serve as chemical spaces in designing new compounds.

The cyclin-dependent kinase 7 (CDK7) plays a crucial role in regulating the cell cycle and RNA polymerase-based transcription. Overexpression of this kinase is linked with various cancers in humans due to its dual involvement in cell development. Furthermore, emerging evidence has revealed that inhibiting CDK7 has anti-cancer effects, driving the development of novel and more cost-effective inhibitors with enhanced selectivity for CDK7 over other CDKs. In the present investigation, a pharmacophore-based approach was utilized to identify potential hit compounds against CDK7. The generated pharmacophore models were validated and used as 3D queries to screen 55,578 natural drug-like compounds. The obtained compounds were then subjected to molecular docking and molecular dynamics simulations to predict their binding mode with CDK7. The molecular dynamics simulation trajectories were subsequently used to calculate binding affinity, revealing four hits-ZINC20392430, SN00112175, SN00004718, and SN00262261-having a better binding affinity towards CDK7 than the reference inhibitors (CT7001 and THZ1). The binding mode analysis displayed hydrogen bond interactions with the hinge region residues Met94 and Glu95, DFG motif residue Asp155, ATP-binding site residues Thr96, Asp97, and Gln141, and quintessential residue outside the kinase domain, Cys312 of CDK7. The in silico selectivity of the hits was further checked by docking with CDK2, the close homolog structure of CDK7. Additionally, the detailed pharmacokinetic properties were predicted, revealing that our hits have better properties than established CDK7 inhibitors CT7001 and THZ1. Hence, we argue that proposed hits may be crucial against CDK7-related malignancies.

Inhibition of chymase is likely to divulge therapeutic ways for the treatment of cardiovascular diseases, and fibrotic disorders. To find novel and potent chymase inhibitors and to provide a new idea for drug design, we used both ligand-based and structure-based methods to perform the virtual screening(VS) of commercially available databases. Different pharmacophore models generated from various crystal structures of enzyme may depict diverse inhibitor binding modes. Therefore, multiple pharmacophore-based approach is applied in this study. X-ray crystallographic data of chymase in complex with different inhibitors were used to generate four structure-based pharmacophore models. One ligand-based pharmacophore model was also developed from experimentally known inhibitors. After successful validation, all pharmacophore models were employed in database screening to retrieve hits with novel chemical scaffolds. Drug-like hit compounds were subjected to molecular docking using GOLD and AutoDock. Finally four structurally diverse compounds with high GOLD score and binding affinity for several crystal structures of chymase were selected as final hits. Identification of final hits by three different pharmacophore models necessitates the use of multiple pharmacophore-based approach in VS process. Quantum mechanical calculation is also conducted for analysis of electrostatic characteristics of compounds which illustrates their significant role in driving the inhibitor to adopt a suitable bioactive conformation oriented in the active site of enzyme. In general, this study is used as example to illustrate how multiple pharmacophore approach can be useful in identifying structurally diverse hits which may bind to all possible bioactive conformations available in the active site of enzyme. The strategy used in the current study could be appropriate to design drugs for other enzymes as well.

Disruption of epigenetic processes to eradicate tumor cells is among the most promising interventions for cancer control. EZH2 (Enhancer of zeste homolog 2), a catalytic component of polycomb repressive complex 2 (PRC2), methylates lysine 27 of histone H3 to promote transcriptional silencing and is an important drug target for controlling cancer via epigenetic processes. In the present study, we have developed various predictive models for modeling the inhibitory activity of EZH2. Binary and multiclass models were built using SVM, random forest and XGBoost methods. Rigorous validation approaches including predictiveness curve, Y-randomization and applicability domain (AD) were employed for evaluation of the developed models. Eighteen descriptors selected from Boruta methods have been used for modeling. For binary classification, random forest and XGBoost achieved an accuracy of 0.80 and 0.82, respectively, on external test set. Contrastingly, for multiclass models, random forest and XGBoost achieved an accuracy of 0.73 and 0.75, respectively. 500 Y-randomization runs demonstrate that the models were robust and the correlations were not by chance. Evaluation metrics from predictiveness curve show that the selected eighteen descriptors predict active compounds with total gain (TG) of 0.79 and 0.59 for XGBoost and random forest, respectively. Validated models were further used for virtual screening and molecular docking in search of potential hits. A total of 221 compounds were commonly predicted as active with above the set probability threshold and also under the AD of training set. Molecular docking revealed that three compounds have reasonable binding energy and favorable interactions with critical residues in the active site of EZH2. In conclusion, we highlighted the potential of rigorously validated models for accurately predicting and ranking the activities of lead molecules against cancer epigenetic targets. The models presented in this study represent the platform for development of EZH2 inhibitors.

The polo-like kinase 1 (Plk1) is a critical regulator of cell division that is overexpressed in many types of tumors. Thus, a strategy in the treatment of cancer has been to target the kinase activity (ATPase domain) or substrate-binding domain (Polo-box Domain, PBD) of Plk1. However, only few synthetic small molecules have been identified that target the Plk1-PBD. Here, we have applied an integrative approach that combines pharmacophore modeling, molecular docking, virtual screening, and in vitro testing to discover novel Plk1-PBD inhibitors. Nine Plk1-PBD crystal structures were used to generate structure-based hypotheses. A common pharmacophore model (Hypo1) composed of five chemical features was selected from the 9 structure-based hypotheses and used for virtual screening of a drug-like database consisting of 159,757 compounds to identify novel Plk1-PBD inhibitors. The virtual screening technique revealed 9,327 compounds with a maximum fit value of 3 or greater, which were selected and subjected to molecular docking analyses. This approach yielded 93 compounds that made good interactions with critical residues within the Plk1-PBD active site. The testing of these 93 compounds in vitro for their ability to inhibit the Plk1-PBD, showed that many of these compounds had Plk1-PBD inhibitory activity and that compound Chemistry_28272 was the most potent Plk1-PBD inhibitor. Thus Chemistry_28272 and the other top compounds are novel Plk1-PBD inhibitors and could be used for the development of cancer therapeutics.

Malathion is an organophosphate chemical (OPC) and a toxic contaminant that adversely impacts food quality, human health, biodiversity, and the environment. Due to its small size and unavailability of sensitive sensors, detection of malathion remains a challenging task. Often chromatographic methods employed to analyze OPCs suffer from several shortcomings, including cost, immobility, laboriousness, and unsuitability for point-of-care settings. Hence, developing a specific and sensitive diagnostic sensor for quick and inexpensive food testing is essential. We discovered four unique malathion-specific ssDNA aptamers; designed two independent sensing strategies using fluorescence labeling and Thioflavin T (ThT) displacement. Selected aptamers formed the G4-quadruplex-like (G4Q) structure, which helped develop a label-free detection approach with a 2.01 ppb limit of detection. Additionally, 3D structures of aptamers were generated and validated using a series of computational modeling programs. Furthermore, we explored structural features using CD spectroscopy and molecular docking, probing ligands' binding mode, and revealed vital intermolecular interactions with aptamers. Subsequently, the novel sensors were optimized to detect malathion from food samples. The novel sensors could be further developed to meet the demands of sensing and quantifying toxic contaminants from real food samples in field conditions.

: Mechanistically, neurotoxic insults provoke Ca2+-mediated calpain activation, which cleaves the cytoplasmic region of membrane-embedded p35 and produces its truncated form p25. Upon physical interaction, cyclin-dependent kinase 5 (Cdk5) and p25 forms hyperactivated Cdk5/p25 complex and causes severe neuropathological aberrations including hyperphosphorylated tau-mediated neurofibrillary tangles formation, Alzheimer's symptoms, and neuronal death. Therefore, the inhibition of Cdk5/p25 complex may relieve p-tau-mediated Alzheimer's pathology. Herein, computational simulations have identified pyrrolidine-2,3-dione derivatives as novel inhibitors of Cdk5/p25 complex. A ligand-based pharmacophore was designed and employed as 3D query to retrieve drug-like molecules from chemical databases. By molecular docking, drug-like molecules obtaining dock score > 67.67 (Goldcore of the reference compound) were identified. Molecular dynamics simulation and binding free energy calculation retrieved four pyrrolidine-2,3-dione derivatives as novel candidate inhibitors of Cdk5/p25. The root means square deviation of Cdk5/p25 in complex with candidate inhibitors obtained an average value of ~2.15 Å during the 30 ns simulation period. Molecular interactions analysis suggested that each inhibitor occupied the ATP-binding site of Cdk5/p25 and formed stable interactions. Finally, the binding free energy estimation suggested that each inhibitor had lowest binding energy than the reference compound (-113.10 kJ/mol) to recapitulate their strong binding with Cdk5/p25. Overall, these inhibitors could mitigate tau-mediated Alzheimer's phenotype.

Prolyl oligopeptidase (POP) is a serine protease that is responsible for the maturation and degradation of short neuropeptides and peptide hormones. The inhibition of POP has been demonstrated in the treatment of α-synucleinopathies and several neurological conditions. Therefore, ligand-based and structure-based pharmacophore models were generated and validated in order to identify potent POP inhibitors. Pharmacophore-based and docking-based virtual screening of a drug-like database resulted in 20 compounds. The in vitro POP assays indicated that the top scoring compounds obtained from virtual screening, Hit 1 and Hit 2 inhibit POP activity at a wide range of concentrations from 0.1 to 10 µM. Moreover, treatment of the hit compounds significantly reduced the α-synuclein expression in SH-SY5Y human neuroblastoma cells, that is implicated in Parkinson's disease. Binding modes of Hit 1 and Hit 2 compounds were explored through molecular dynamics simulations. A detailed investigation of the binding interactions revealed that the hit compounds exhibited hydrogen bond interactions with important active site residues and greater electrostatic and hydrophobic interactions compared to those of the reference inhibitors. Finally, our findings indicated the potential of the identified compounds for the treatment of synucleinopathies and CNS related disorders.

Garlic (Allium sativum L.), is a predominant spice, which is used as an herbal medicine and flavoring agent, since ancient times. It has a rich source of various secondary metabolites such as flavonoids, terpenoids and alkaloids, which have various pharmacological properties. Garlic is used in the treatment of various ailments such as cancer, diabetes and cardiovascular diseases. The present study aims to explore the plausible mechanisms of the selected phytocompounds as potential inhibitors against the known drug targets of non-small-cell lung cancer (NSCLC). The phytocompounds of garlic were identified by gas chromatography-mass spectrometry (GC-MS) technique. Subsequently, the identified phytocompounds were subjected to molecular docking to predict the binding with the drug targets, epidermal growth factor receptor (EGFR), human epidermal growth factor receptor 2 (HER2), echinoderm microtubule-associated protein-like 4-anaplastic lymphoma kinase (EML4-ALK) and group IIa secretory phospholipase A2 (sPLA2-IIA). Molecular dynamics is used to predict the stability of the identified phytocompounds against NSCLC drug targets by refining the intermolecular interactions formed between them. Among the 12 phytocompounds of garlic, three compounds[1,4-dimethyl-7-(1-methylethyl)-2-azulenyl]phenylmethanone, 2,4-bis(1-phenylethyl)-phenol and 4,5-2 h-oxazole-5-one,4-[3,5-di-t-butyl-4-methoxyphenyl] methylene-2-phenyl were identified as potential inhibitors, which might be suitable for targeting the different clinical forms of EGFR and dual inhibition of the studied drug targets to combat NSCLC. The result of this study suggest that these identified phytocompounds from garlic would serve as promising leads for the development of lead molecules to design new multi-targeting drugs to address the different clinical forms of NSCLC.