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Iosif Vaisman
Email: [email protected]
Introduction to Bioinformatics
Protein Modeling Methods
- Ab initio methods: solution of a protein folding problem search in conformational space
- Energy-based methods: energy minimization molecular simulation
- Knowledge-based methods: homology modeling fold recogniion
a pattern that exceeds certain threshold of interestingness.
Knowledge
Knowledge is ...
Factors that contribute to interestingness: coverage confidence statistical significance simplicity unexpectedness actionability
Knowledge-based methods
Finding patterns in known structures
Deriving rules (usually in the form of PMF)
Applying the rules
Protein representation (Crambin) Protein representation (Crambin)
4 neighbors
7 neighbors 2 neighbors
10 neighbors
Neighbor identification in proteins
Voronoi Tessellation
Delaunay simplex is defined by points, whose Voronoi polyhedra have common vertex Delaunay simplex is always a triangle in a 2D space and a tetrahedron in a 3D space
Delaunay Tessellation
Neighbor identification in proteins:
Voronoi/Delaunay Tessellation in 2D
Neighbor identification in proteins:
Voronoi/Delaunay Tessellation in 2D
Voronoi Tessellation Delaunay Tessellation
Neighbor identification in proteins:
Voronoi/Delaunay Tessellation in 2D
6 7
6
Delaunay tessellation of Crambin Delaunay tessellation of Crambin
Swiss-Model
- Method: Knowledge-based approach.
- Requirements: At least one known 3D-structure of a related protein. Good quality sequence alignements.
- Procedures: Superposition of related 3D-structures. Generation of a multiple a alignement. Generation of a framework for the new sequence. Rebuild lacking loops. Complete and correct backbone. Correct and rebuild side chains. Verify model structure quality and check packing. Refine structure by energy minimisation and molecular dynamics.
Methods and Programs used by Swiss-Model
- Sequence Alignment BLAST (Altschul S.F., J. Mol. Biol. 215 :403, 1990) SIM (Huang, X., Miller, M. Adv. Appl. Math. 12 :337, 1991) ProModII (Peitsch, M.C. Unpublished, Server-specific tool)
- Knowledge Based Protein Modelling ProMod (Peitsch M.C. Biochem Soc Trans 24 :274, 1996)
- Energy Minimisation Gromos96 (van Gunsteren W.F. http://igc.ethz.ch/gromos/ )
- Model evaluation Swiss-PdbViewer ( http://www.expasy.ch/spdbv/mainpage.html )
Swiss-Model Request Types
- First Approach mode.
- Optimise mode.
- Combine mode.
- GPCR mode.
Model Confidence Factors
The Model B-factors are determined as follows:
- The number of template structures used for model building.
- The deviation of the model from the template structures.
- The Distance trap value used for framework building.
The Model B-factor is computed as:
85.0 * (1/ # selected template str.) * (Distance trap / 2.5) and 99.9 for all atoms added during loop and side-chain building
