tools and techniques for:

Tema 14. Bases of protein structure and structural prediction. Structural data bank. Protein Data Bank.

Molecular Visualization Tools for 3D. Prediction based on sequence. Folding prediction. 3D structural

prediction by homology. Quality criteria.

Structural Bioinformatics: analysisis of protein structures and their functions by

informatic tools

Tools and techniques for:

• Analize

• Save

• Visualize

• Predict

• Compare

• Evaluate– ESTRUCTURE OF PROTEINS

1-GLSDGEWQLV LNVWGKVEAD IPGHGQEVLI RLFKGHPETL EKFDKFKHLK SEDEMKASED LKKHGATVLT ALGGILKKKG HHEAEIKPLA QSHATKHKIP VKYLEFISEC IIQVLQSKHP GDFGADAQGA MNKALELFRK DMASNYKELG FQG-153

-Ala-Ser-Ile-Met-Arg-

Función

Aminoacid sequence determines one significative form.3D form of the protein determines its function

Complexity levels: Hierarchics

Primary: so far

Secundary: α-helix 35% of residuesß - sheet, 25% of residuesß turns, Ω turns, 3/10 helix Total: 65-75%Rest: inclasificable subestructures, hazard forms (ramdom coils)

Tertiary Structure

• Simple Clasification:– All alfa (>50% helix; <10% ß)– All ß (>30% beta; <5% heix)– Mixture

• Refined Clasification– Topologies, motifs, domains– Foldings . Most of the proteins will be

classified in one or other way from about 1000 distinct basic foldings

Quaternary structure

X ray difraction

NMR

•3D structural Data Bank

Protein data Bank Tour

•Statistics•Look for the active form (closed Conformation from human glucokinase)•Take a look to the file•Save archive

PDB archives

Molecular Visualization

JMOL web

JMOL molecular visualization program

FIRST GLANCE JMOL

Example of a tutorial on glucokinase

Molecular Visualization Programs

• Rasmol (1995)• Chime• Protein Explorer ( Chime interface, requieres

Chime, problems with Chime)• Jmol (java)

• Deep View• Others: “professionals” Pymol

Tools for 3D structures analysis and comparison

• Check structures

• Looking for similars in structures. VAST

• (1 mbn, whale myoglobin)

• Structure alignment: servers and deepview

• conserved surfaces (glucokinase)

Structural alignment

Structural alignment

• Goal: Obtain best superposition from several structures– Dinamic program scoring from geometric

characteristics – Matrices of intramolecular distances– Clustering in 3D

• It is possible to classify proteins based on structural homology

Servidor

Derived Data bases and classification of proteins based on

3D structures

• PDBsum

• Clasification: SCOP, CATH

PDBSUM

CATH Hierarchy

• C: Class (secondary structure content)• A: Architecture (disposition of the

secondary structure elements)• T: Topology (disposition of the connexions

between elements)• H: Homology (Structural homology)• S: Sequence (Sequence homology)

SCOP. Structural Classification of Proteins

1. Family. Clear evolutive relationship

2. Superfamily. Probably common evolutive origin

3. Folding. Strong structural homology