Task 6: Protein structure prediction from evolutionary sequence variation

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Revision as of 18:47, 23 August 2013 by Betza (talk | contribs) (Contact Prediction)

Results

lab journal

Contact Prediction

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<figure id="ras_score_dist">

Cn score ras.png

</figure>


<figtable id="hfe_score_dist" >

Cn score imm.png
Cn score mhc2.png

</figtable>

domain length seq. in alignment reference HS pairs TP FP TP -rate
Ras 160 21151 5P21 65 53 12 0.82
MHC I 174 25167 1A6Z_A 69 29 40 0.42
Ig C1-set 76 16509 1A6Z_A 15 9 6 0.6


<figure id="cm_1a6z">

ContactMap 1a6z new.png

</figure> <figure id="cm_hras">

ContactMap 5p21.png

</figure>

  • Why are the scores of residues close in sequence amongst the highest? Why are the pairs distant in sequence (n>5) more interesting for structure prediction?

It lies in the nature of proteins, that residues that are close in sequence, are also close in structure. Consequently, they are evolutionary coupled and show covariation in the multiple sequence alignment. The pairs that are at least five residues apart in sequence, are more interesting for structure prediction, because they contain more information about the overall topology of the protein, i.e. they reduce the space of possible protein conformations more than pairs that are close in sequence.

  • Look at the values, range and distribution of scores.

For the MHC I domain of HFE_HUMAN, the score distribution is shown in table <xr id="hfe_score_dist" />. The values range from -0.94 to 2.57 with the mean at -0.07. The score distribution corresponds to a slightly right skewed normal distribution, where most values are in the range of -1 to 1. Only 0.5% of scores have a value above 1. Thus, scores with a value greater than one can be considered as high scoring.


  • How many of the high-scoring pairs are true or false positives? Does this correlate with the value of the score? Visualize the predicted contacts together with the crystal structure contacts in a contact map plot.

Table <xr id="hs_table"> shows, that TP-rate can range from 0.8 for Ras to 0.4 for the MHC I domain. Since the number of sequences in the multiple alignment is above 15 000 for all three domains, the TP-rate among the high scoring pairs depends not only on the number of sequences in the alignment, but also on the actual sequence at hand. As discussed in <ref name="EVfold_method"> Marks DS, Colwell LJ, Sheridan R, Hopf TA, Pagnani A, et al. (2011) Protein 3D Structure Computed from Evolutionary Sequence Variation. PLoS ONE 6(12): e28766. doi:10.1371/journal.pone.0028766 </ref> , possible confounding factors could be pyhlogenetic bias or functional constraints from interactions with other molecules.

<figure id="score_correlation">

The distribution of scores for TP and FP predicted contact pairs of MHC I is shown. Note that only high scoring pairs are shown in this plot.

</figure>

The correlation between CN score and TP/FP contact is not very good as indicated by a Pearson correlation coefficient of 0.354 and the overlap between the boxplots in figure <xr id="score_correlation">.


  • Can you determine evolutionary hot spots, i.e. functionally important residues? Compare to conserved sites in the MSA. Compare with your results from task 7 (when you are working on task 7, i.e. this is a task for the future).
MHC Ig C1-set
AA Pos. Norm. Score SNP Conservation AA Pos Norm. Score SNP Conservation
V 59 9.97 Val->Met DC CM994469 2 C 225 9.09 - 10
C 124 8.20 - 2 W 239 6.53 - 10
L 33 7.08 - 2 C 282 6.04 Cys -> Tyr DC CM960828 2
Y 140 6.96 - 3 H 286 5.66 - 5
V 120 5.96 - 0 P 232 5.16 - 10
S 27 5.64 - 0 I 235 4.40 - 9
L 91 5.54 - 0 M 237 3.94 - 9
A 37 5.00 Ala->Val nDC 0 I 268 3.91 - 1
L 44 4.99 - 0 W 267 3.51 - 0
G 51 4.71 - 3 D 261 3.10 - 8




For RAS_HUMAN, only 20(40%) of the top 50 scores overlaped.


MHC EVFOLD: constraints: 70(40%) 113(65%) 174(100%)

imm EVFOLD

Structural Models

The structural models for Ras were calculated with three different numbers of evolutionary constraints: 76(40%), 123(65%) and 189 (100%).

<figure id="rmsd_evfold">

Comparison of Ca-RMSD values distributions between the different numbers of ECs used.

</figure>

Comparison of Ca-RMSD values distributions between the different numbers of ECs used.

Discussion

<references />