Task 4 (MSUD)

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Revision as of 17:20, 30 May 2013 by Schillerl (talk | contribs) (Results)

Explore structural alignments

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Use structural alignments to evaluate sequence alignments

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Results

The following table shows an overview of the structures used for building models, the scores of the structural alignment (RMSD and LGA_S - structure similarity score), and the scores of the sequence alignment (E-value, probability and sequence identity).


model RMSD LGA_S E-value probability sequence identity
1qs0 1.24 84.085 5.8E-94 100.0 38
1w85 1.77 78.356 8.3E-87 100.0 33
2ozl 1.63 74.027 3.2E-69 100.0 27
2yic 2.45 41.732 5.7E-47 100.0 16
3l84 2.01 32.412 6.5E-18 99.5 21
2q28 1.86 25.398 1.6E-08 97.9 13
1r9j 1.73 30.095 1.1E-06 97.2 25
2vk8 2.12 21.990 3.7E-05 96.4 22
1t9b 1.83 23.724 0.0011 94.9 18
2c31 2.00 21.849 0.011 92.7 21


Correlations of structural to sequence alignement scores
e-value log10(e-value) probability sequence identity
RMSD 0.15 0.49 -0.19 -0.74
LGA_S -0.33 -0.98 0.71 0.82


As can be seen in the above table, the RMSD has a weak correlation to the logarithm of E-value and a higher correlation to sequence identity. The RMSD is lower, if the E-value is lower or the sequence identity is higher.

The same tendency can be seen for the LGA_S score, but here the correlations are higher. The LGA_S score shows also a correlation to the probability in contrast to the RMSD.

The signs are opposite for RMSD and LGA_S, because the RMSD is lower for higher similarity, but the LGA_S is higher.


The relationship of LGA_S and E-value, the pair of scores with the highest correlation, for the 10 models is shown in the following plot.

MSUD cor LGA-S evalue.jpeg

Discussion