Difference between revisions of "Task 3 (MSUD)"

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===== BCKDHA =====
 
===== BCKDHA =====
 
<gallery perrow=1 width=800px height=280px caption="Profiles for disorders and globular regions of BCKDHA">
 
<gallery perrow=1 width=800px height=280px caption="Profiles for disorders and globular regions of BCKDHA">
File:BCKDHA_long.png|Prediction result of long range disorders|alt=Long disorder
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File:BCKDHA_long.png|Prediction result of long range disorders
File:BCKDHA_short.png|Prediction result of short range disorders|alt=Short disorder
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File:BCKDHA_short.png|Prediction result of short range disorders
File:BCKDHA_globular.png|Prediction of globular regions|alt=Globular regions
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File:BCKDHA_globular.png|Prediction of globular regions
 
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Revision as of 21:10, 19 May 2013

Secondary structure

Lab journal

Result

The results for ReProf and PsiPred predictions and the DSSP assignments are in the following folders:

/mnt/home/student/schillerl/MasterPractical/task3/reprof/

/mnt/home/student/schillerl/MasterPractical/task3/psipred/

/mnt/home/student/schillerl/MasterPractical/task3/dssp/


Position specific scoring matrices (PSSM) used as input for ReProt are located at:

/mnt/home/student/schillerl/MasterPractical/task3/pssm/


Approach for predicting secondary structure with ReProf

For P10775, ReProf was run with the protein sequence fasta file and position specific scoring matrices (PSSM) derived from big_80 and SwissProt as input. The following tables show the comparison of the prediction results to the secondary structure assignment of DSSP. The f-measure is the harmonic mean of recall and precision, it gives a good indication for the quality of a classificator.


Comparison of ReProf prediction (fasta input) to DSSP assignment
secondary structure element recall precision f-measure
H 0.719 0.585 0.645
E 0.211 0.500 0.296
L 0.616 0.654 0.635


Comparison of ReProf prediction (big_80 PSSM input) to DSSP assignment
secondary structure element recall precision f-measure
H 0.944 0.889 0.916
E 0.649 0.685 0.667
L 0.826 0.866 0.846


Comparison of ReProf prediction (SwissProt PSSM input) to DSSP assignment
secondary structure element recall precision f-measure
H 0.923 0.914 0.919
E 0.807 0.523 0.634
L 0.719 0.859 0.782


Predictions using a PSSM instead of a simple sequence have a considerably better quality. All methods predict helices better than loops and these better than beta sheets. The results of the run with the big_80 PSMM are better for E and L and only slightly worse for H than those using the SwissProt PSMM.

The percentages of correctly identified secondary structure (H, E or L) for the three methods are 61 %, 86 % and 82 %. So for the remaining sequences, the method with the best performance (usage of PSSM derived from big_80 as input for ReProf) was used.


Comparison of ReProf to PsiPred and DSSP

The following tables show the percentages of agreement for secondary structure between ReProf and PsiPred or DSSP.


P12694

secondary structure element PsiPred DSSP
H 0.804 0.812
E 0.400 0.585
L 0.876 0.782
all 0.849 0.816


P10775

secondary structure element PsiPred DSSP
H 0.798 0.889
E 0.691 0.649
L 0.779 0.828
all 0.849 0.855


Q08209

secondary structure element PsiPred DSSP
H 0.794 0.816
E 0.487 0.615
L 0.830 0.807
all 0.827 0.807


Q9X0E6

secondary structure element PsiPred DSSP
H 0.897 0.923
E 0.694 0.643
L 0.636 0.545
all 0.802 0.802


Altogether, ReProf agrees in 80-85% of the predictions with PsiPred and DSSP. In most cases the agreement for H and L is higher than for E.

Information from UniProt and PDB

A summary of interesting features for the proteins:


P12694, 2BFD:

  • name: 2-oxoisovalerate dehydrogenase subunit alpha, mitochondrial
  • EC: 1.2.4.4
  • gene: BCKDHA
  • organism: Homo sapiens (Human)
  • sequence length: 445 AA
  • subunit structure: heterotetramer of alpha and beta chains
  • subcellular location: mitochondrion matrix
  • secondary structure: 42% helical, 10% beta sheet
  • 3D similarity: pyruvate dehydrogenase E1
  • ligands: chloride ion, glycerol, potassium ion, manganese (II) ion, (4S)-2-methyl-2,4-pentanediol, thiamin diphosphate


P10775, 2BNH:

  • name: ribonuclease inhibitor
  • gene: RNH1
  • organism: Sus scrofa (Pig)
  • sequence length: 456 AA
  • subcellular location. cytoplasm
  • sequence similarities: contains 15 LRR (leucine-rich) repeats
  • secondary structure: alternating helix and strand, 42% helical, 12% beta sheet


Q08209, 1AUI:

  • name: serine/threonine-protein phosphatase 2B catalytic subunit alpha isoform
  • EC: 3.1.3.16
  • gene: PPP3CA
  • organism: Homo sapiens (Human)
  • sequence length: 521 AA
  • subunit structure: heterodimer of alpha and beta chain (human calcineurin heterodimer)
  • subcellular location: nucleus
  • secondary structure: 27% helical, 11% beta sheet
  • ligands: calcium ion, Fe (III) ion, zinc ion


Q9X0E6, 1KR4:

  • name: divalent-cation tolerance protein CutA
  • gene: cutA
  • organism: Thermotoga maritima (strain ATCC 43589 / MSB8 / DSM 3109 / JCM 10099)
  • sequence length: 101 AA
  • subunit structure: homotrimer
  • subcellular location: cytoplasm
  • secondary structure: great fraction of strands, 29% helical, 35% beta sheet

Discussion

In the first step, the ReProf results for P10775 were evaluated against the DSSP assignment. Here, DSSP was viewed as "the truth", because it assigns secondary structure based on the measured 3D structure by examining angles and H bonds between atoms.

The prediction of secondary structure is much better if a PSSM is used instead of the sequence. The reason is that a PSSM describes the requirements for each position better than the amino acid sequence, because it uses evolutionary information. So it identifies for each position alternatives for the residues in the primary sequence, that don't alter the overall structure of the protein. The difference between the usage of big_80 or SwissProt for generating the PSSM is not that obvious, but we decided to take big_80 for the remaining proteins because it showed a slightly better performance in our test with the example protein P10775.

For all proteins these ReProf results were compared to PsiPred and DSSP, to see how much the methods agree in the secondary structure assignment. The methods agree for most residues. The highest discrepancies can be observed for the prediction of beta strands, which shows that these are not as easy to predict as alpha helices or loops. A reason for this could be that beta strands are less frequent than alpha helices in most proteins, as can be seen in the informations taken from UniProt and PBD.

Disordered protein

Lab journal

Result

IUPred

IUPred performs prediction of intrinsic disordered regions of proteins by the observation of pairwise energy content from proteins with known structures. The results of IUPred fall into 3 categories: long (disordered regions), short (disordered regions) and globular (regions of protein where pairwise interactions between residues are more potential).

For the prediction of disordered regions (prediction mode long and short), position-specific score is assigned to each residue of the query sequence. The score indicates the tendency that the corresponding residue belongs disordered region. Following are the profiles of disorder tendency generated by web-tool of IUPred:

BCKDHA

Discussion

Transmembrane helices

Lab journal

Result

Discussion

Signal peptides

Lab journal

Result

SignalP predictions

The following diagrams show the C- (cleavage site), S- (signal peptide) and Y- (combined cleavage site) scores for the three proteins according to SignalP version 4.1. The combined cleavage site score combines the cleavage score with the slope of the signal peptide score to optimize the recognition of cleavage sites.

P02768 signalp.png


P47863 signalp.png


P11279 signalp.png


For P02768 and P11279 signal peptides are predicted, with the clevage site between position 18 and 19 for P02768 and between 28 and 29 for P11279. For P47863, no signal peptide is predicted.

SignalP version 3.0 (results see /mnt/home/student/schillerl/MasterPractical/task3/signalp/) came to the same result for P02768 and P11279. However for P47863 it predicts a signal peptide with cleavage site between positions 54 and 55 (neural network) or 56 and 57 (hidden markov model), although only with the probability 0.723 compared to near 1 for the other two proteins.


Known signal peptides

On the Signal Peptide Website there are entries for P02768 and P11279 but not for P47863:


Accession Number Entry Name Protein Name Organism Length Status Signal Sequence
P02768 ALBU_HUMAN Serum albumin Homo sapiens 18 confirmed MKWVTFISLLFLFSSAYS
P11279 LAMP1_HUMAN Lysosome-associated membrane glycoprotein 1 Homo sapiens 28 confirmed MAAPGSARRPLLLLLLLLLLGLMHCASA

Discussion

The predictions of the newest version of SignalP agree with the confirmed signal peptides. The older version predicted a signal peptide in P47863, where no one is. According to UniProt, P47863 has transmembrane helices, so these might be mistaken for a signal peptide by the old version because they resemble each other.

GO terms

Lab journal

Result

Discussion