The selection and plot below are almost the same as the single sequence predictions, refer to the single sequence tutorial
for the main functionality. Hovering over the plot, however, will display the Gaussian Mixture Model (GMM) score for that
residue. This score is based on an analysis of the 7-dimensional 'biophysical space' for that residue, in relation to
the column it occupies in the MSA. High scores indicate very normal scores, low (negative) scores indicate unusual
scores, meaning this residue is unlike other ones in the alignment. Below the plot, you will also find a breakdown
of the residues that are indicated by the GMM as unusual, using 5%, 1% and 0.1% cutoffs over the full MSA..
The above plot shows the following predictions for :
| DynaMine backbone dynamics |
Values above 0.8 indicate rigid conformations, values above 1.0 membrane spanning regions, values
below 0.69 flexible regions. Values between 0.69-0.80 are 'context' dependent and capable of being either
rigid or flexible. |
| DynaMine sidechain dynamics | Higher values mean more likely rigid. These values are highly dependent
on the amino acid type (i.e. a Trp will be rigid, an Asp flexible). |
| DynaMine conformational propensities (sheet, helix,
coil, ppII (polyproline II)) | Higher values indicate higher propensities. |
| EFoldMine earlyFolding propensity | Values above 0.169 indicate residues that are likely
to start the protein folding process, based on only local interactions with other amino acids. |
| Disomine disorder | Values above 0.5 indicate that this is likely a disordered residue. |
These predictions reflect 'emerging' properties, so what the sequence is capable of, not necessarily what it will adopt in a final fold.
The plot below shows, for the protein you selected above, the variation in predicted biophysical parameters
within the multiple sequence alignment (MSA) that you uploaded. This variation is displayed according to
simple box plot statistics, with median, first/third quartile, and outlier range of the distributions shown.
Columns in the MSA that are 'gapped' for the
selected protein are not shown here. In other words, what is displayed is how the biophysical prediction
for each aligned position varies for all the proteins that are in the MSA. You can select the type of
prediction that you want to display in the selection box below the plot, and turn each distribution statistic
on and off by clicking on its name. The 'prediction' field corresponds to the same type of prediction shown in the
top plot.
The above plot shows multiple sequence alignment (MSA) derived distributions of the prediction type you selected,
organised by the protein you selected for the top graph. The distributions are based on an analysis of the uploaded MSA,
and shows the 'evolutionary allowed' range for this prediction. The red line corresponds to the single protein prediction in the top graph,
the other lines show simple statistical parameters calculated from the values per MSA column. Values of the red line outside
of the quartile range therefore indicate rather unusual behavior for this particular protein compared to its homologues in the MSA.
If you now select the following characteristics in the dropdown box above, and compare the values for
the natural TIM barrel proteins to the de novo designed sTIM-11 protein, and for the misfolding OctaV1 protein (select these at the top of the page):
- backbone The backbone dynamics are very similar to the MSA-based distributions for all proteins, with the red line mostly falling within its quartile ranges
- earlyFolding The early folding predictions show some immediate differences, with some peaks being higher in sTIM-11 and OctaV1,
many similar and one notably absent in OctaV1 (around A138). The early folding differences imply that, compared to natural TIM barrel proteins,
some regions of both the sTIM-11 and OctaV1 protein will start to fold earlier, but only few later.
- helix The helix propensities for sTIM-11 are similar to the MSA-based distributions, whilst OctaV1 has overall higher propensities.
- sheet Both proteins have generally lower beta-sheet propensities, but the pronounced beta-sheet propensity peaks are present in sTIM-11,
while some notable ones are absent in OctaV1.
These changes can be connected to each other; for example, the absent early folding peak around A138 in
OctaV1 also corresponds to much reduced beta-sheet propensity in OctaV1 (outside of the quartile range),
whilst this region is similar to the natural proteins for sTIM-11 (around I128). This might indicate
that this region is important for correct folding, and so highlights points where mutations might be
explored. Overall, this type of analysis can highlight differences of interest between the inherent
biophysical characteristics encoded by protein sequences, with as only requirement the protein sequences,
and a multiple sequence alignment.
