Bioinformatics; Learn Docking & Mol Dynamics Simulation

Learn three experimental techniques to determine the three dimensional structure of a protein: x ray crystallography, NMR spectroscopy, and cryo electron microscopy, and download structures from the protein data bank.

Predict a protein's 3d structure when no pdb entry exists using homology-based, threading-based, and Alphafold methods, with tutorials on modular and Alphafold CoLab for docking and dynamics.

Apply homology modeling with Modeller to predict a protein’s three-dimensional structure by installing Modeller, selecting templates from the protein data bank, and generating and optimizing multiple models.

Apply Newton's second law to compute an atom's acceleration from the force and mass, using the relation F = ma with the force derived from interaction energy.

Solvation and ionization involve placing a protein in a cubical box, solvating with water to reflect cytoplasmic conditions, and adding ions to neutralize the system for realistic simulations.

Equilibration relaxes macromolecules and surrounding solvent to a uniform temperature and pressure before the production phase. Production runs last from nanoseconds to microseconds to reflect protein half-life and computational resources.

Explore the Linux environment for molecular dynamics simulations and bioinformatics, compare Windows, iOS, and Linux, and learn why Gromacs relies on Linux.

Explore Linux as an open source, free operating system with strong security, rarely needing reboots, privacy, and broad hardware compatibility, and see why Ubuntu offers both command-line and graphical interfaces.

Perform energy minimization in Gromacs to relax the protein, using the minimum.mdp with coordinate and topology files to generate a .tpr, and verify negative potential energy and acceptable max force.

Calibrate pressure to achieve a homogeneous density by using a np.mdp file with gromacs, generating ztpr output, then run with verbose mode to define output names.

Calibrate a protein molecular dynamics run in GROMACS, estimating a speed of about 31.109 nanoseconds per day and confirming equilibration by density plots showing 1021.84 near 1000.

Learn to analyze molecular dynamics data using commands to center the protein in the box, compute radius of gyration, hydrogen bonds, and solvent accessible surface area, copy into ubuntu terminal.

Use the gyrate module in Gromacs to calculate the radius of gyration for the whole protein during a molecular dynamics simulation, producing an xvg output file.

Learn to calculate the solvent accessible surface area of a protein during molecular dynamics using gromacs, by supplying the tpr and md_0_1_center.cc files, and saving results to area.xvg.

Explore molecular docking in bioinformatics, predicting how a ligand or peptide binds to a protein using sampling and scoring algorithms to identify poses with the lowest binding energy.

Examine six sampling algorithms used in docking programs, including shape matching, incremental construction, multiple copies, simultaneous search, ludi Monte Carlo, and the genetic algorithm.

Explore fragment-based de novo ligand design and modification, selecting top binding groups to improve protein binding. Compare simultaneous search with ludi, focusing on de novo design via force sampling.

Master steps of molecular docking by obtaining or predicting a protein’s 3D structure, preparing it by removing non protein components and adding missing atoms and hydrogens, and starting ligand preparation.

Discover the installation of MGL Tools, Vina, AutoDock4, and Autogrid, and see practical docking demonstrations using these tools. Follow step-by-step download and installation guidance for Windows, Mac, and Linux.

Learn to download three-dimensional ligand structures from the zinc 15 database, using dopamine as an example, with similarity filtering and commercial availability for docking and virtual screening.

Learn to convert a ligand from SDF to PDB using Open Babel GUI, then prepare ligand and receptor for docking with AutoDock and Vina, noting the 32 rotatable-bond limit.

Learn how to predict ligand binding site residues using blind and specific docking, and use the couch server to predict active sites from 3D structures or sequences.

Set the grid box around the selected ligand binding site residues to guide docking, then adjust its dimensions and center before choosing between blind or specific docking.

Prepare receptor and ligand PDB files, create a vina configuration with center, grid, and exhaustiveness, and run vina to obtain docking energies such as -7.7 kcal/mol.

Learn to perform ligand protein docking with Autodock4 by configuring grid parameters, performing rigid docking with a genetic algorithm, and reading the docking log for best conformations.

Visualize Autodock four docking results by loading docking log file and macromolecule, then adjust representations to show the cartoon receptor and pink ball-and-stick ligand, and analyze hydrogen bonds across conformations.

Learn to perform automated AutoDock Vina docking on SwissDock by uploading ligand SMILES or PDB, preparing ligand and protein, setting the grid box, and reviewing docking results and affinities.

Restrict the ligand at the binding site during equilibration by creating a non-hydrogen ligand index and generating a position restraint topology with Gromacs. Integrate the restraint into the topology file.

Center the protein in the molecular dynamics trajectory and analyze the ligand-protein complex. Compute rmsd, rmsf, hydrogen bonds, radius of gyration, and binding energy, then plot results.

Highlight the role of virtual screening in rapidly accelerating drug discovery, offering a robust alternative to conventional methods, and recognizing its global use.

Prepare the protein receptor for docking by removing water, checking for missing atoms, repairing the structure, adding hydrogens and charges, then save as receptor.pdb in the docking two directory.