
Explore how structural bioinformatics studies three-dimensional biomolecule structures to deduce function and mechanism of action, visualize protein structures, and cover structure prediction, validation, alignment, and docking.
Link the three-dimensional structure to protein function by examining active sites, electrostatic potential, solvent accessibility, and functional residues revealed by conservation across alignments.
Protein folding begins in the cytosol, where secondary structural elements interact with the solvent, entropy loss drives folding from disorderly state toward a molten globule state and defined tertiary structure.
Explore the SCOP database and its manually curated protein structure classification by class, fold, super-family, and family, including seven major classes and the concept of domains.
Explore CATH, a manually curated structural database that classifies proteins using class, architecture, topology, and homologous super-family based on secondary structure content.
Predict protein structures from known homologues using protein homology modeling, a structural bioinformatics technique that links structure to function and complements experimental methods like X-ray crystallography, NMR, and electron microscopy.
Explore protein molecular dynamics by simulating motion with newtonian equations, using initial coordinates from x-ray crystallography, nmr, or electron microscopy, and evolving trajectories to reveal equilibrium behavior in biophysical environments.
Protein molecular docking is a bioinformatics technique in structure-based drug design, where known target and ligand structures are examined for binding, with binding energy calculations evaluating interaction strength.
In this course you will learn what is structural bioinformatics all about and get an introduction of all the major areas of structural bioinformatics. Structural Bioinformatics is an interdisciplinary field that deals with the three dimensional structures of bio-molecules. It attempts to model and discover the basic principles underlying biological machinery at the molecular level. It is based on the assumption that 3D structural information of a biological system is the core to understanding its mechanism of action and function. Structural bioinformatics combines applications of physical and chemical principles with algorithms from computational science.