Virtual Screening Strategy Combined Bayesian Classification Model, Molecular Docking for Acetyl-CoA Carboxylases Inhibitors

2019 ◽  
Vol 15 (3) ◽  
pp. 193-205 ◽  
Author(s):  
Wei-Neng Zhou ◽  
Yan-Min Zhang ◽  
Xin Qiao ◽  
Jing Pan ◽  
Ling-Feng Yin ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Bayesian Model ◽  
High Efficiency ◽  
Screening Strategy ◽  
Classification Model ◽  
Acetyl Coa ◽  
Ligand Interaction ◽  
Alcoholic Fatty Liver ◽  
Molecule Docking

Introduction: Acetyl-CoA Carboxylases (ACC) have been an important target for the therapy of metabolic syndrome, such as obesity, hepatic steatosis, insulin resistance, dyslipidemia, non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), type 2 diabetes (T2DM), and some other diseases. Methods: In this study, virtual screening strategy combined with Bayesian categorization modeling, molecular docking and binding site analysis with protein ligand interaction fingerprint (PLIF) was adopted to validate some potent ACC inhibitors. First, the best Bayesian model with an excellent value of Area Under Curve (AUC) value (training set AUC: 0.972, test set AUC: 0.955) was used to screen compounds of validation library. Then the compounds screened by best Bayesian model were further screened by molecule docking again. Results: Finally, the hit compounds evaluated with four percentages (1%, 2%, 5%, 10%) were verified to reveal enrichment rates for the compounds. The combination of the ligandbased Bayesian model and structure-based virtual screening resulted in the identification of top four compounds which exhibited excellent IC 50 values against ACC in top 1% of the validation library. Conclusion: In summary, the whole strategy is of high efficiency, and would be helpful for the discovery of ACC inhibitors and some other target inhibitors.</P>

scholarly journals In silicoidentification of putativeTrypanosoma cruzienolase inhibitors

2019 ◽  
Author(s):  
Edward A. Valera-Vera ◽  
Melisa Sayé ◽  
Chantal Reigada ◽  
Mariana R. Miranda ◽  
Claudio A. Pereira
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Active Site ◽  
Screening Strategy ◽  
Glycolytic Enzyme ◽  
Docking Simulations ◽  
Enzyme Active Site ◽  
Key Enzyme

AbstractEnolase is a glycolytic enzyme that catalyzes the interconversion between 2-phosphoglycerate and phosphoenolpyruvate. In trypanosomatids enolase was proposed as a key enzyme afterin silicoandin vivoanalysis and it was validated as a protein essential for the survival of the parasite. Therefore, enolase constitutes an interesting enzyme target for the identification of drugs against Chagas disease. In this work, a combined virtual screening strategy was implemented, employing similarity virtual screening, molecular docking and molecular dynamics. First, two known enolase inhibitors and the enzyme substrates were used as queries for the similarity screening on the Sweetlead database using five different algorithms. Compounds retrieved in the top 10 of at least three search algorithms were selected for further analysis, resulting in six compounds of medical use (etidronate, pamidronate, fosfomycin, acetohydroximate, triclofos, and aminohydroxybutyrate). Molecular docking simulations predicted acetohydroxamate and triclofos would not bind to the active site of the enzyme, and a re-scoring of the obtained poses signaled fosfomycin and aminohydroxybutyrate as bad enzyme binders. Docking poses obtained for etidronate, pamidronate, and PEP, were used for molecular dynamics calculations to describe their mode of binding. From the obtained results, we propose etidronate as a possibleTcENO inhibitor, and describe desirable and undesirable molecular motifs to be taken into account in the repurposing or design of drugs aiming this enzyme active site.

Virtual Screening Based on Pharmacophore to Discover Host ER Alpha-Glucosidase II Inhibitor for Dengue Therapy

2020 ◽  
Vol 840 ◽  
pp. 221-229
Author(s):  
Elsafira Ariavianti ◽  
Filia Stephanie ◽  
Usman Sumo Friend Tambunan
Keyword(s):  
Endoplasmic Reticulum ◽  
Natural Products ◽  
Molecular Docking ◽  
Drug Discovery ◽  
Virtual Screening ◽  
Host Protein ◽  
Binding Interaction ◽  
Ligand Interaction ◽  
Docking Simulations ◽  
Glucosidase Ii

Dengue is one of the crucial diseases in human-caused by dengue virus (DENV) infection. However, the development of DENV antiviral is often facing a problem because no effective drug to treat infection caused by all DENV serotypes. The inhibition of host protein involved in DENV life cycle can be a potential approach in dengue drug discovery, and also avoiding antiviral resistance. Endoplasmic Reticulum (ER) α-glucosidase II is one of the target host protein in DENV endoplasmic reticulum that plays an important role in the maturation process of DENV envelope glycoprotein. Natural products have been known as an essential source of a lead compound for drug discovery due to their therapeutic potency. In this research, pharmacophore-based virtual screening and molecular docking simulations were performed to find ligand that has potential to inhibit α-glucosidase II activity. About 67,609 natural products from InterBioScreen (IBS) database were used in the simulation as ligands with α-glucosidase II as the protein target. After subjected to Lipinski’s Rule of Five, druglikeness, nasty functions, and toxicity screening using DataWarrior software, 17,462 ligands were obtained. The pharmacophore features for molecular docking simulation was obtained from Protein-Ligand Interaction Fingerprint (PLIF) analysis using eight α-glucosidase II protein with different ligands. Based on virtual screening, rigid, and flexible docking simulations using Molecular Operating Environment (MOE) software, 32 ligands have lower Gibbs free binding energy (ΔGbinding) compared to the standards. Two best ligands, namely STOCK1N-85545 and STOCK1N-86400 which belong alkaloid derivatives, showed the exceptional ligand interaction and had the lowest ΔGbinding of-11.204 and-10.276 kcal/mol, respectively. The ligands were identified to have a binding interaction with amino acid Asp564 and Asp640 in α-glucosidase II catalytic site. STOCK1N-85545 and STOCK1N-86400 were also identified to have a good pharmacological properties after subjected to ADME-tox test using Toxtree, SwissADME, admetSAR, and pkCSM software.

scholarly journals PHARMACOINFORMATICS APPROACH OF IDENTIFIED BIOLOGICAL COMPOUNDS FROM SELECTED PLECTRANTHUS (L.) SPECIES IN TAMIL NADU, INDIA: AN IN-SILICO APPROACH

2021 ◽  
Vol 12 (7) ◽  
pp. 14-21
Author(s):  
Selvarasuvasuki Manikandan ◽  
Sabeerali Ansarali ◽  
Manikandan Priyadharshini ◽  
Ganapathy Murugan Alagu Lakshmanan
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Tamil Nadu ◽  
Biological Activities ◽  
Ligand Interaction ◽  
Docking Analysis ◽  
Biological Compounds ◽  
Low Toxicity ◽  
Plectranthus Amboinicus ◽  
Molecular Docking Analysis

Aim: Plectranthus (Linn) is a typical genus of the Indian flora. It had been used in the folk medicines for its several medicinal properties. In this study, there are twenty-five major biological compounds were selected from Plectranthus forskohlii, Plectranthus coleoides, Plectranthus rotundifolius and Plectranthus vettiveroides for molecular docking analysis and find out the active compounds against Diabetic, Cancer and Tuberculosis diseases. Materials and methods: Biological compounds of Plectranthus Species were identifying and investigated by GC-MS and the biological activities of these compounds were studied with virtual screening, ADMET analysis, Protein ligand interaction through molecular docking analysis. Results: Twenty-five major biological compounds were selected for virtual screening analysis to find out the drug likeness activity. Out of these twenty-five compounds nine compounds are drug likeness in nature. Based on the ADMET analysis, Thymol beta D-Glucoside showed the low toxicity level and it represent Lipinski rule of five. The molecular docking results of Thymol beta D-Glucoside interact with different target proteins used in the study showed the maximum docking energy was obtained against tuberculosis protein -10.1846kcal/mol followed by diabetic protein -10.8736kcal/mol and cancer protein -11.4109kcal/mol. Conclusion: Plectranthus amboinicus leaves showed significant anti-diabetic, anti-cancer, anti-tuberculosis activity when compared to other studied species such as Plectranthus forskohlii, Plectranthus coleoides, Plectranthus rotundifolius and Plectranthus vettiveroides.

Identification of dual Acetyl-CoA carboxylases 1 and 2 inhibitors by pharmacophore based virtual screening and molecular docking approach

2013 ◽  
Vol 17 (1) ◽  
pp. 139-149 ◽  
Author(s):  
Anuseema Bhadauriya ◽  
Gaurao V. Dhoke ◽  
Rahul P. Gangwal ◽  
Mangesh V. Damre ◽  
Abhay T. Sangamwar
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Acetyl Coa ◽  
Docking Approach

Identification of New Inhibitors of Mutant Isocitrate Dehydrogenase 2 through Molecular Similarity-based Virtual Screening

2019 ◽  
Vol 16 (8) ◽  
pp. 861-867 ◽  
Author(s):  
Lijun Yang ◽  
Stefan Pusch ◽  
Victoria Jennings ◽  
Tianfang Ma ◽  
Qihua Zhu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Isocitrate Dehydrogenase ◽  
Similarity Search ◽  
Molecular Similarity ◽  
Tricarboxylic Acid ◽  
Screening Strategy ◽  
Oxidative Decarboxylation ◽  
Isocitrate Dehydrogenase 2 ◽  
Growth And Reproduction

Background: Isocitrate dehydrogenase 2 (IDH2) is an enzyme catalyzing the oxidative decarboxylation of isocitrate to α-ketoglutarate (α-KG) in the tricarboxylic acid (TCA). Evidences suggest that the specific mutations in IDH2 are critical to the growth and reproduction of severe tumors especially leukemia and glioblastoma. It is found that the inhibitors of mutant IDH2 are promising anti-tumor therapeutics. Methods: A virtual screening strategy combining molecular similarity search and molecular docking was performed in the binding site of AGI-6780. YL-16, YL-17 and YL-18 were identified as novel mutant IDH2 inhibitors for the reduction of (D)-2-hydroxyglutarate in cellular evaluation. In addition, all the three compounds showed inhibition against IDH2-R172K mutated HEK-293T cells, while weak inhibition against wide-type IDH2 (WT-IDH2) HEK-293T cells. Results: Significantly, YL-17 showed 84.55% inhibitory activity against IDH2-R172K at 1 µM and weak cytotoxicity to wide-type IDH2 at 50 µM. Conclusion: YL-17 was highlighted as a new mutant IDH2 inhibitor that could be further developed for therapeutic applications.

InstaDock: A single-click graphical user interface for molecular docking-based virtual high-throughput screening

2020 ◽  
Author(s):  
Taj Mohammad ◽  
Yash Mathur ◽  
Md Imtaiyaz Hassan
Keyword(s):  
Molecular Docking ◽  
User Interface ◽  
Virtual Screening ◽  
High Throughput ◽  
Graphical User Interface ◽  
High Throughput Screening ◽  
Computational Method ◽  
Recognition Mechanism ◽  
Ligand Interaction ◽  
High Throughput Virtual Screening

Abstract Exploring protein–ligand interactions is a subject of immense interest, as it provides deeper insights into molecular recognition, mechanism of interaction and subsequent functions. Predicting an accurate model for a protein–ligand interaction is a challenging task. Molecular docking is a computational method used for predicting the preferred orientation, binding conformations and the binding affinity of a ligand to a macromolecular target, especially protein. It has been applied in ‘virtual high-throughput screening’ of chemical libraries containing millions of compounds to find potential leads in drug design and discovery. Here, we have developed InstaDock, a free and open access Graphical User Interface (GUI) program that performs molecular docking and high-throughput virtual screening efficiently. InstaDock is a single-click GUI that uses QuickVina-W, a modified version of AutoDock Vina for docking calculations, made especially for the convenience of non-bioinformaticians and for people who are not experts in using computers. InstaDock facilitates onboard analysis of docking and visual results in just a single click. To sum up, InstaDock is the easiest and more interactive interface than ever existing GUIs for molecular docking and high-throughput virtual screening. InstaDock is freely available for academic and industrial research purposes via https://hassanlab.org/instadock.

Homology Modeling of Mus Musculus CDK5 and Molecular Docking Studies with Flavonoids

2017 ◽  
Vol 9 (6) ◽  
Author(s):  
Sowmya Suri ◽  
Rumana Waseem ◽  
Seshagiri Bandi ◽  
Sania Shaik
Keyword(s):  
Molecular Docking ◽  
3D Model ◽  
Structural Features ◽  
Docking Studies ◽  
Amino Acid Residues ◽  
Cyclin Dependent Kinase ◽  
Ligand Complex ◽  
Ligand Interaction ◽  
Molecular Docking Studies ◽  
Cyclin Dependent Kinase 5

A 3D model of Cyclin-dependent kinase 5 (CDK5) (Accession Number: Q543f6) is generated based on crystal structure of P. falciparum PFPK5-indirubin-5-sulphonate ligand complex (PDB ID: 1V0O) at 2.30 Å resolution was used as template. Protein-ligand interaction studies were performed with flavonoids to explore structural features and binding mechanism of flavonoids as CDK5 (Cyclin-dependent kinase 5) inhibitors. The modelled structure was selected on the basis of least modeler objective function. The model was validated by PROCHECK. The predicted 3D model is reliable with 93.0% of amino acid residues in core region of the Ramachandran plot. Molecular docking studies with flavonoids viz., Diosmetin, Eriodictyol, Fortuneletin, Apigenin, Ayanin, Baicalein, Chrysoeriol and Chrysosplenol-D with modelled protein indicate that Diosmetin is the best inhibitor containing docking score of -8.23 kcal/mol. Cys83, Lys89, Asp84. The compound Diosmetin shows interactions with Cys83, Lys89, and Asp84.

Dose COVID-19 Uncovered a New Feature of Metronidazole Drug?

2020 ◽  
Author(s):  
Mohammad Seyedhamzeh ◽  
Bahareh Farasati Far ◽  
Mehdi Shafiee Ardestani ◽  
Shahrzad Javanshir ◽  
Fatemeh Aliabadi ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Drug Discovery ◽  
Virtual Screening ◽  
Active Sites ◽  
Initial Plasma ◽  
New Feature ◽  
Metronidazole Benzoate ◽  
Global Health Problem ◽  
A Current ◽  
Pro Inflammatory Cytokines

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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