Basics of Computer Aided Drug Discovery Part-I

Discover computer aided drug discovery by using genomics and proteomics for target identification, pharmacophore-based virtual screening, molecular dynamics, homology modeling, AI-driven lead design, and ADMET optimization.

Explore how to access and search the PDB database for protein structures using basic, advanced, and sequence-based filters; visualize, download PDB or FASTA files, and explore ligand targets.

Explore the PubChem database to retrieve chemical structures, view 2D/3D and crystal structures, download SDF files, and access ADME, toxicity, patents, clinical trials, and related data for paracetamol.

Access the Zinc database to obtain commercially purchasable compounds ready for docking, search by smiles, structure, or Zinc id, and explore subsets for virtual screening.

Download and install mgltools for the autodock on Windows, run as administrator, accept the licensing, and access the Python Molecular Viewer (PMV). Explore installation prompts and upcoming options in PMV.

Learn to download Biovia Discovery Studio Visualizer by submitting a download request with professional details, select Windows or Linux versions, and complete the admin installation.

Visualize the protein in Biovia Discovery Studio with dynamic display styles, residue and atom details, multiple representations, and color and surface options to reveal structure and function.

Explore visualizing a ligand in Biovia Discovery Studio by opening the compound, viewing data tables, atomic and residue information, bonds and lengths, and adjusting display styles and color by element.

Explore visualizing proteins and ligands in MGLTools using line, ball-and-stick, CPK, and ribbon representations. Label residues and color by secondary structure, polarity, hydrophobicity, and residue type.

Explore the rationale for molecular docking and compare blind and targeted docking, then explain flexible, semi-flexible, and rigid docking with a focus on binding site recognition and scoring.

Learn to prepare a ligand for docking by configuring the startup directory, loading a PDB file, converting to PDBQT, and enabling rotatable bonds to identify core moieties.

Prepare a protein for docking by cleaning structure: delete waters, add missing hydrogens, merge non-polar hydrogens, assign charges, apply Kollman and gastiger charges, set neutral pH, and save as pdbqt.

Prepare the grid parameter file (GPF) by selecting the macromolecule, setting grid boundaries, and saving the Autodock parameter library and affinity maps.

Prepare a docking parameter file for autodock using a Lamarckian genetic algorithm, set ligand details and center coordinates, generate random population, use default medium evaluation, save as protein_ligand.dpf.

Visualize and edit the autodock dpf to review atom types, affinity maps, electrostatic and desolution maps, move ligand, and torsional degrees of freedom, with ten GA runs and clustering analysis.

Execute autogrid by loading a GPF file to generate affinity maps for a protein–ligand pair, after downloading and extracting the autogrid tools and running the program in a working folder.

Execute the docking parameter file by launching autodock with the DPF file after completing auto grid, run the autodock in background, and note warnings while awaiting docking completion.

Analyze docking outputs from Autodock with MGLtools PMV, interpreting the DLG log, binding energies, RMSD rankings, and IC50 values, then visualize protein-ligand interactions to identify top conformations.

Learn to analyze docking outputs from mgltools in Biovia Discovery Studio, view 2D and 3D protein–ligand interactions, and save publication-ready visualizations.