Structure Visualization First & Last Name June X, 2005 Structure Visualization Boris Steipe University of Toronto boris.steipe@utoronto.ca 3.4 (c) 2005 CGDN

Visualizations: abstractions to aid understanding First & Last Name June X, 2005 Visualizations: abstractions to aid understanding Where are we with respect to our objectives ? CPK Line Trace Cartoon 3.4 (c) 2005 CGDN

Visualization of 3D relationships requires stereo vision First & Last Name June X, 2005 Visualization of 3D relationships requires stereo vision 1CDL.PDB Practice regularily Increase image size Increase viewing distance Increase complexity set stereo -5 select protein color chain select *.ca and hetero color [0,180,255] select within (3.0, (*.ca and hetero)) and *.O* color red 3.4 (c) 2005 CGDN

Global features of structure First & Last Name June X, 2005 Global features of structure quarternary structure global fold  machine metaphore, mimicry residues that participate in ligand binding interfaces surprising structural similarity  homology unusual surface and core residues location of SNPs or sites and context of mutations, PTM sites shape  clefts, pockets, protrusions conformational changes  molecular mechanisms 3.4 (c) 2005 CGDN

Distances in protein structure First & Last Name June X, 2005 Distances in protein structure Hydrogen bonds Size Bond-lengths Where are we with respect to our objectives ? Binding sites Salt-bridges Rasmol: set picking distance 3.4 (c) 2005 CGDN

Distances from coordinates First & Last Name June X, 2005 Distances from coordinates XYZ coordinates are vectors in an orthogonal coordinate system, in Å. All the rules of analytical geometry apply. [...] ATOM 687 OH TYR 86 7.415 62.584 32.900 1.00 3.37 ATOM 651 O ASP 82 9.996 62.571 32.488 1.00 5.18 Where are we with respect to our objectives ? d = [(9.996-7.415)2 + (62.571-62.584)2 + (32.488-32.900)2]0.5 = [(2.581)2 + (-0.013)2 + (-0.412)2]0.5 = [6.661561 + 0.0000169 + 0.169744]0.5 = [6.831474]0.5 = 2.614 Å = 0.2614 nm = 2.614 . 10-10 m 3.4 (c) 2005 CGDN

Distances and angles: Ligand binding First & Last Name June X, 2005 Distances and angles: Ligand binding H-bonds have specific geometric requirements with respect to distance and angles. They confer conformational specificity to proteins. More than 90% of H-bond "valences" are usually satisfied and geometries cluster closely around consensus distances and angles. ±30° ±70° Chelation: Calcium bound in Calmodulin (1CLL.PDB) Where are we with respect to our objectives ? D H A 2.85±0.25 Å (Hydrogen coordinates are usually inferred !) 3.4 (c) 2005 CGDN

Dihedral angles +f i+3 i i+2 i+1 Single bonds: First & Last Name June X, 2005 Dihedral angles i+3 Single bonds: Freely rotable, but constrained by steric overlap. i Double bonds: Constrained to planar geometry. Large energetic barrier to isomerization. i+2 Where are we with respect to our objectives ? +f i+1 Rasmol: set picking torsion 3.4 (c) 2005 CGDN

Backbone dihedral angles: Ramachandran plots First & Last Name June X, 2005 Backbone dihedral angles: Ramachandran plots    Where are we with respect to our objectives ? 3.4 (c) 2005 CGDN

Sidechain rotamers 3 2  First & Last Name June X, 2005 Sidechain rotamers 100 randomly chosen Phe-residues superimposed. 3 2  Where are we with respect to our objectives ? Ponder & Richards (1987) J. Mol. Biol. 193, 775-791 http://www.fccc.edu/research/labs/dunbrack/sidechain.html 3.4 (c) 2005 CGDN

First & Last Name June X, 2005 B-factors B-factors are isotropic temperature factors, i.e. they model the relation-ship between observed and theoreti-cal electron density of an atom at rest by applying a spherically symmetrical thermal distribution to the density until it best matches the experiment. "Real" devitions from ideality are neither isotropic nor ther-mally distributed, they can corres-pond to discrete disorder, dynamic mobility and will be influenced by experimental error of measurement and refinement problems. 2IMM.PDB: Rasmol, CPK, color by temperature, slab mode. 3.4 (c) 2005 CGDN

Molecular complementarity First & Last Name June X, 2005 Molecular complementarity Tight and specific binding implies that all features of the ligand will be recognized by the protein. Arg H52 Tyr L100 Tyr H33 Trp H107 negative charge distance hydrophilic Asp L97 Where are we with respect to our objectives ? hydrophobic positive charge Phosphorylcholine in antibody binding site (2MCP.PDB) 3.4 (c) 2005 CGDN

Mapping properties on surfaces First & Last Name June X, 2005 Mapping properties on surfaces Properties of atoms (B-factors) Ensemble properties of residues (hydrophobicity, conservation) Geometry (local curvature) Fields and potentials (isosurfaces, binding potential) Where are we with respect to our objectives ? AChE (1ACL.PDB) color coded by electrostatic potential with GRASP. http://trantor.bioc.columbia. edu/grasp/ 3.4 (c) 2005 CGDN

Visualization tools Rasmol Chime MolMol Cn3D others Molscript .... First & Last Name June X, 2005 Visualization tools Rasmol Chime MolMol Cn3D others Molscript .... ORTEP POVRay Where are we with respect to our objectives ? 3.4 (c) 2005 CGDN

Tools RasMol Cn3D DeepView VMD First & Last Name June X, 2005 3.4 (c) 2005 CGDN

RasMol Work through the Rasmol tutorial ! First & Last Name June X, 2005 RasMol Small footprint, easy to install, sufficient functionality for most tasks, widely distributed, powerful commandline interface, scriptable. Work through the Rasmol tutorial ! http://biochemistry.utoronto.ca/steipe/bioinformatics Rasmol download Features Stereo vision ! Where are we with respect to our objectives ? L R 1DRO.PDB, model 1 3.4 (c) 2005 CGDN

Cn3D Work through the Cn3D tutorial ! First & Last Name June X, 2005 Cn3D Good integration with NCBI databases, excellent functionality for domain and conservation analysis. Scriptable. No stereo :-( Work through the Cn3D tutorial ! http://ncbi.nih.gov/Structure/CN3D/cn3dtut.shtml Where are we with respect to our objectives ? 3.4 (c) 2005 CGDN

DeepView (Swiss PDB Viewer) First & Last Name June X, 2005 DeepView (Swiss PDB Viewer) Excellent tool for homology modeling, structure manipulation, structure alignment and analysis of sequence alignments. Calculates surfaces and electrostatics. Creates PovRay scenes. Good integration with SwissModel. Work through either DeepView tutorial ! http://ca.expasy.org/spdbv/text/tutorial.htm http://www.usm.maine.edu/~rhodes/SPVTut/ Where are we with respect to our objectives ? 3.4 (c) 2005 CGDN

VMD (http://www.ks.uiuc.edu/Research/vmd/) First & Last Name June X, 2005 VMD (http://www.ks.uiuc.edu/Research/vmd/) Very powerful, well maintained, good graphics, intuitive use, scriptable and well integrated with NAMD. Work through the VMD tutorial ! http://www.ks.uiuc.edu/Research/vmd/vmd-1.8.2/tutorial/html/vmd-tutorial.html Where are we with respect to our objectives ? 3.4 (c) 2005 CGDN