Sequence-based predictions HEXA

Prediction of disordered regions

• DISOPRED

Authors: Ward JJ, Sodhi JS, McGuffin LJ, Buxton BF, Jones DT. Year: 2004 Source: [Prediction and functional analysis of native disorder in proteins from the three kingdoms of life.]

Description: This method is based on a neuronal network which was trained on high resolution X-ray structures from PDB. Disordered regions are regions, which appears in the sequence record, but their electrons are missing from electronic density map. This approach can also failed, because missing electrons can also arise because of the cristallization process. The method runs first a PsiBlast search against a filtered sequence database. Next, a profile for each residue is calculated and classified by using the trained neuronal network.

Prediction: As a prediction result you get a file with the predicted disordered region, the precision and recall. Furthermore you can a more detailed output. There you see the sequence, and the predictions and also numbers above the sequence (from 0 to 9 which shows you how likly your prediction is)

Input: If you run disopred on the console, you have to define the location of your database. The program needs as input your sequence in a file with fasta format.

Prediction of GO terms

Prediction of disordered regions

* Disopred

Disopred predicts two disordered regions in our protein. The first region is at the beginning of the protein (first two residues) and the second region is at the end (last three regions). This prediction is probably wrong, because it is normal, that the electrons from the first and the last amino acids lack in the electron density map. So, our protein Hexosamidase A has no disordered regions.

Template:Bausteindesign

conf: 970000000000000000000000000000000000000000000000000000000000 pred: **..........................................................

 AA: MTSSRLWFSLLLAAAFAGRATALWPWPQNFQTSDQRYVLYPNNFQFQYDVSSAAQPGCSV
             10        20        30        40        50        60

conf: 000000000000000003567778888887776530000000001122311000000000 pred: ..................****************..........................

 AA: LDEAFQRYRDLLFGSGSWPRPYLTGKRHTLEKNVLVVSVVTPGCNQLPTLESVENYTLTI
             70        80        90       100       110       120

conf: 000000000000000000000000000000000000000000000000000000000000 pred: ............................................................

 AA: NDDQCLLLSETVWGALRGLETFSQLVWKSAEGTFFINKTEIEDFPRFPHRGLLLDTSRHY
            130       140       150       160       170       180

conf: 000000000000000000000000000000000000000000000000000000000000 pred: ............................................................

 AA: LPLSSILDTLDVMAYNKLNVFHWHLVDDPSFPYESFTFPELMRKGSYNPVTHIYTAQDVK
            190       200       210       220       230       240