Difference between revisions of "Task 6 - EVfold"

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For the proteins used in this practical, structures have been determined. However, in real-life projects, you often do not have protein structures only sequences. However, structure often provides crucial information and furthers understanding of the proteins function.
 
During this practical, you already predicted secondary structure elements from protein sequence and generated homology models from protein structures with sequence similarity to your protein. This week, we will use evolutionary couplings or correlated mutations to predict structures from protein sequence alignments.
 
 
== Theoretical background talk ==
 
The talk will give an introduction to structure prediction from correlated mutations. In particular EVcouplings and EVfold are introduced.
 
 
 
 
 
correlated mutations
 
 
local method: mutual information
 
 
 
your protein
 
+ example P01112 (RASH_HUMAN)
 
http://pfam.sanger.ac.uk/family/Ras
 
 
 
calculating the evolutionary couplings
 
 
0. aligment (clustalw.... Pfam alignment good) Many sequences
 
 
1. a2m2lm.... => aligment
 
2. freecontact -> standard (installed on student computers)
 
 
Output -> all couplings + evolutionary coupling score (last column)
 
 
rank by score => look at distrubution, values, range
 
 
Meaning of score unclear
 
 
Take only scores for i+6, i.e. neighboring residues neglected, minimal 5 residues between coupled residues
 
 
Take ranking, check for each coupled pair the actual distance in the structure. TP: distance <= 5 AA (minimal distance of all pairs of all atoms of both residues)
 
 
 
EVcoupling
 
Check evolutionary hot spots, i.e. relevant residues, functionally important sites.
 
Take L couplings (L=length of protein sequence), sum scores for each residue. Analyze.
 
(Cell paper)
 
 
- compare to conservation, single site conservation
 
 
 
EVfold.org
 
 
create model
 
 
choose number of contacts:
 
optimum ~ 60-70% of L
 
40% of L
 
100% of L
 
 
=> RMSD will be calculated by server, if you give PDB ID
 
 
PLM
 

Latest revision as of 01:23, 11 June 2013