Structure-based virtual screening and molecular docking for the identification of potential multi-targeted inhibitors against breast cancer

Studies of coronavirus disease 2019 (COVID-19) as a current global health problem shown the initial plasma levels of most pro-inflammatory cytokines increased during the infection, which leads to patient countless complications. Previous studies also demonstrated that the metronidazole (MTZ) administration reduced related cytokines and improved treatment in patients. However, the effect of this drug on cytokines has not been determined. In the present study, the interaction of MTZ with cytokines was investigated using molecular docking as one of the principal methods in drug discovery and design. According to the obtained results, the IL12-metronidazole complex is more stable than other cytokines, and an increase in the surface and volume leads to prevent to bind to receptors. Moreover, ligand-based virtual screening of several libraries showed metronidazole phosphate, metronidazole benzoate, 1-[1-(2-Hydroxyethyl)-5- nitroimidazol-2-yl]-N-methylmethanimine oxide, acyclovir, and tetrahydrobiopterin (THB or BH4) like MTZ by changing the surface and volume prevents binding IL-12 to the receptor. Finally, the inhibition of the active sites of IL-12 occurred by modifying the position of the methyl and hydroxyl functional groups in MTZ. <br>

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Identification of Novel Structurally Diverse Anaplastic Lymphoma Kinase Inhibitors Based on Pharmacophore Modeling, Virtual Screening and Molecular Docking

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207319666160801153455 ◽

2016 ◽

Vol 19 (9) ◽

pp. 691-704

Author(s):

Rong You ◽

Lu Zhou ◽

Liangliang Zhong ◽

Xiaoli Li ◽

Suwen Zhou ◽

...

Keyword(s):

Molecular Docking ◽

Virtual Screening ◽

Anaplastic Lymphoma Kinase ◽

Kinase Inhibitors ◽

Pharmacophore Modeling ◽

Anaplastic Lymphoma

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Discovery of Camptothecin Based Topoisomerase I Inhibitors: Identification Using an Atom Based 3D-QSAR, Pharmacophore Modeling, Virtual Screening and Molecular Docking Approach

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207319666160810154346 ◽

2016 ◽

Vol 19 (9) ◽

pp. 752-763 ◽

Cited By ~ 4

Author(s):

Sanal Dev ◽

Sunil Dhaneshwar ◽

Bijo Mathew

Keyword(s):

Molecular Docking ◽

Virtual Screening ◽

Topoisomerase I ◽

3D Qsar ◽

Pharmacophore Modeling ◽

Topoisomerase I Inhibitors ◽

Docking Approach

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Promising Anti-stroke Signature of Voglibose: Investigation through In- Silico Molecular Docking and Virtual Screening in In-Vivo Animal Studies

Current Gene Therapy ◽

10.2174/1566523220999200726225457 ◽

2020 ◽

Vol 20 (3) ◽

pp. 223-235

Author(s):

Pooja Shah ◽

Vishal Chavda ◽

Snehal Patel ◽

Shraddha Bhadada ◽

Ghulam Md. Ashraf

Keyword(s):

Molecular Docking ◽

Virtual Screening ◽

In Silico ◽

Reductase Activity ◽

Infarct Volume ◽

Docking Studies ◽

Serum Glucose ◽

In Vivo Studies ◽

In Silico Molecular Docking

Background: Postprandial hyperglycemia considered to be a major risk factor for cerebrovascular complications. Objective: The current study was designed to elucidate the beneficial role of voglibose via in-silico in vitro to in-vivo studies in improving the postprandial glycaemic state by protection against strokeprone type 2 diabetes. Material and Methods: In-Silico molecular docking and virtual screening were carried out with the help of iGEMDOCK+ Pymol+docking software and Protein Drug Bank database (PDB). Based on the results of docking studies, in-vivo investigation was carried out for possible neuroprotective action. T2DM was induced by a single injection of streptozotocin (90mg/kg, i.v.) to neonates. Six weeks after induction, voglibose was administered at the dose of 10mg/kg p.o. for two weeks. After eight weeks, diabetic rats were subjected to middle cerebral artery occlusion, and after 72 hours of surgery, neurological deficits were determined. The blood was collected for the determination of serum glucose, CK-MB, LDH and lipid levels. Brains were excised for determination of brain infarct volume, brain hemisphere weight difference, Na+-K+ ATPase activity, ROS parameters, NO levels, and aldose reductase activity. Results: In-silico docking studies showed good docking binding score for stroke associated proteins, which possibly hypotheses neuroprotective action of voglibose in stroke. In the present in-vivo study, pre-treatment with voglibose showed a significant decrease (p<0.05) in serum glucose and lipid levels. Voglibose has shown significant (p<0.05) reduction in neurological score, brain infarct volume, the difference in brain hemisphere weight. On biochemical evaluation, treatment with voglibose produced significant (p<0.05) decrease in CK-MB, LDH, and NO levels in blood and reduction in Na+-K+ ATPase, oxidative stress, and aldose reductase activity in brain homogenate. Conclusion: In-silico molecular docking and virtual screening studies and in-vivo studies in MCAo induced stroke, animal model outcomes support the strong anti-stroke signature for possible neuroprotective therapeutics.

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Machine Learning-based Virtual Screening Strategy Reveals Some Natural Compounds As Potential PAK4 Inhibitors In Triple Negative Breast Cancer

Current Proteomics ◽

10.2174/1570164618999201223092209 ◽

2020 ◽

Vol 18 ◽

Author(s):

Opeyemi Iwaloye ◽

Olusola Olalekan Elekofehinti ◽

Babatomiwa Kikiowo ◽

Emmanuel Ayo Oluwarotimi ◽

Toyin Mary Fadipe

Keyword(s):

Breast Cancer ◽

Virtual Screening ◽

Triple Negative Breast Cancer ◽

Triple Negative ◽

Binding Free Energy ◽

Natural Compounds ◽

Energy Calculation ◽

Reference Drug ◽

Predictive Quality

Background: P-21 activating kinase 4 (PAK4) is implicated in poor prognosis of many cancers, especially in the progression of Triple Negative Breast Cancer (TNBC). The present study was aimed at designing some potential drug candidates as PAK4 inhibitors for breast cancer therapy. Objective: This study aimed to finding novel inhibitors of PAK4 from natural compounds using computational approach. Methods: An e-pharmacophore model was developed from docked PAK4-coligand complex and used to screen over a thousand natural compounds downloaded from BIOFACQUIM and NPASS databases to match a minimum of 5 sites for selected (ADDDHRR) hypothesis. The robustness of the virtual screening method was accessed by well-established methods including EF, ROC, BEDROC, AUAC, and the RIE. Compounds with fitness score greater than one were filtered by applying molecular docking (HTVS, SP, XP and Induced fit docking) and ADME prediction. Using Machine learningbased approach QSAR model was generated using Automated QSAR. The computed top model kpls_des_17 (R2= 0.8028, RMSE = 0.4884 and Q2 = 0.7661) was used to predict the pIC50 of the lead compounds. Internal and external validations were accessed to determine the predictive quality of the model. Finally the binding free energy calculation was computed. Results: The robustness/predictive quality of the models were affirmed. The hits had better binding affinity than the reference drug and interacted with key amino acids for PAK4 inhibition. Overall, the present analysis yielded three potential inhibitors that are predicted to bind with PAK4 better than reference drug tamoxifen. The three potent novel inhibitors vitexin, emodin and ziganein recorded IFD score of -621.97 kcal/mol, -616.31 kcal/mol and -614.95 kcal/mol, respectively while showing moderation for ADME properties and inhibition constant. Conclusion: It is expected that the findings reported in this study may provide insight for designing effective and less toxic PAK4 inhibitors for triple negative breast cancer.

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