Here is the top lead compund obtained in the secondary screening with a binding energy of -10.6.That drug was preveiously known. (comercially available)
Here are the different amino acids that are interacting with the drug.
Model of the drug with the chemical featuresThis was other drug, it wasn’t that different.
Grupo 4 ppt
Secondary Screening: Vina Docking and Ranking by Binding Energy Juan C. Torres Carolina Montanez Gretel Montanez Luzmarie Reyes
ObjectiveTo perform a secondary screening to identify theusing AutoDock Vina.
Drug Discovery Strategy Biological Problem (Biomedically Relevant Condition or Process) Primary Sequence Optimal target (s) Analysis; degree for drug development conservationTherapeutically (NCBI/Swiss-Prot) FTmap Target Analysis Chemical probes Number, qualityrelevant protein cluster and distance of targets number & quality “hot spots’ Pharmacophore . 3D Structure identification and www.pdb.org PyMol Pharmacophore Model Generation (LigandScout) Primary Screening: Pharmacophore Drug-like Databases Model (≈ 9.5 million drugs) (Ligand Scout) Lead-like Database Further refinement (≈ 1.3 million drugs) of Pharmacophore Model Identification of Top Hits Secondary Screening (AutoDock) Identification of High Affinity Lead Compounds. BioAssay Lead (Ranking of binding Compounds energies)
Part 1: Run the Docking Screening (AutoDock Vina)
Part 2: Obtain the Results/ Ranking of Top Hits
Part 3: Analyze Interactions using Auto Dock tools