Difference between revisions of "Metachromatic leukodystrophy reference aminoacids"

From Bioinformatikpedia
Line 113: Line 113:
 
!Seq Identity
 
!Seq Identity
 
!source
 
!source
  +
!Protein function
 
|-
 
|-
 
!colspan="3"| 99-90% Sequence Identity
 
!colspan="3"| 99-90% Sequence Identity
 
|-
 
|-
|gi109094666||%||bla
+
|gi109094666||%||bla||unknown
 
|-
 
|-
|gi281339526||%||bla
+
|gi281339526||%||bla||unknown
 
|-
 
|-
|gi47522624||%||bla
+
|gi47522624||%||bla||unknown
 
|-
 
|-
|gi149759319||%||bla
+
|gi149759319||%||bla||unknown
 
|-
 
|-
|gi301763795||%||bla
+
|gi301763795||%||bla||unknown
 
|-
 
|-
 
!colspan="3"| 89-60% Sequence Identity
 
!colspan="3"| 89-60% Sequence Identity
 
|-
 
|-
|1E2S||| % || bla
+
|1E2S||| % || bla||unknown
 
|-
 
|-
|gi118081865||%|| bla
+
|gi118081865||%|| bla||unknown
 
|-
 
|-
|gi126339031||%|| bla
+
|gi126339031||%|| bla||unknown
 
|-
 
|-
|gi114326188||%|| bla
+
|gi114326188||%|| bla||unknown
 
|-
 
|-
|gi164519052||%|| bla
+
|gi164519052||%|| bla||unknown
 
|-
 
|-
 
!colspan="3"| 59-40% Sequence Identity
 
!colspan="3"| 59-40% Sequence Identity
 
|-
 
|-
|1HDH||%||bla
+
|1HDH||%||bla||unknown
 
|-
 
|-
|1P49||%||bla
+
|1P49||%||bla||unknown
 
|-
 
|-
|gi120537984||%||bla
+
|gi120537984||%||bla||unknown
 
|-
 
|-
|gi301625378||%||bla
+
|gi301625378||%||bla||unknown
 
|-
 
|-
|gi86142609||%||bla
+
|gi86142609||%||bla||unknown
 
|-
 
|-
 
!colspan="3"| 39-20% Sequence Identity
 
!colspan="3"| 39-20% Sequence Identity
 
|-
 
|-
|1FSU||%|| bla
+
|1FSU||%|| bla||unknown
 
|-
 
|-
|2VQR||%||bla
+
|2VQR||%||bla||unknown
 
|-
 
|-
|3ED4||%|| bla
+
|3ED4||%|| bla||unknown
 
|-
 
|-
|gi113971721||%|| bla
+
|gi113971721||%|| bla||unknown
 
|-
 
|-
|gi310635680||%||bla
+
|gi310635680||%||bla||unknown
   
 
|}
 
|}

Revision as of 14:29, 23 May 2011

Sequence

>sp|P15289|ARSA_HUMAN Arylsulfatase A OS=Homo sapiens GN=ARSA PE=1 SV=3
MGAPRSLLLALAAGLAVARPPNIVLIFADDLGYGDLGCYGHPSSTTPNLDQLAAGGLRFT
DFYVPVSLCTPSRAALLTGRLPVRMGMYPGVLVPSSRGGLPLEEVTVAEVLAARGYLTGM
AGKWHLGVGPEGAFLPPHQGFHRFLGIPYSHDQGPCQNLTCFPPATPCDGGCDQGLVPIP
LLANLSVEAQPPWLPGLEARYMAFAHDLMADAQRQDRPFFLYYASHHTHYPQFSGQSFAE
RSGRGPFGDSLMELDAAVGTLMTAIGDLGLLEETLVIFTADNGPETMRMSRGGCSGLLRC
GKGTTYEGGVREPALAFWPGHIAPGVTHELASSLDLLPTLAALAGAPLPNVTLDGFDLSP
LLLGTGKSPRQSLFFYPSYPDEVRGVFAVRTGKYKAHFFTQGSAHSDTTADPACHASSSL
TAHEPPLLYDLSKDPGENYNLLGGVAGATPEVLQALKQLQLLKAQLDAAVTFGPSQVARG
EDPALQICCHPGCTPRPACCHCPDPHA


Source


Database Searches

FASTA, BLAST and PSI-BLAST were run against the non-redundant database (NR). HHsearch was run through the web interface<ref>http://toolkit.lmb.uni-muenchen.de/hhpred</ref> aigainst the PDB and Interpro database. The following parameter settings were used:

  • BLAST: blastall -p blastp -i refSeq.fasta -d /data/blast/nr/nr > blastp with refSeq.fasta being the file containing the reference sequence and blastp the * PSI-BLAST: blastpgp -i refSeq.fasta -d /data/blast/nr/nr -e"e-value" -j "#iterations" > psiblast_"e-value"_"#iterations"
  • PSI-BLAST was run with the following parameter settings:
    • e-value cutoff 0.005, 3 iterations (Psi-blast1)
    • e-value cutoff 0.005, 5 iterations (Psi-blast2)
    • e-value cutoff 10E-6, 3 iterations (Psi-blast3)
    • e-value cutoff 10E-6, 5 iterations (Psi-blast4)
  • HHsearch: We used the online version of hhPred <ref>http://toolkit.lmb.uni-muenchen.de/hhpred</ref> with default parameters. One search was performed against PDB and one against Interpro.

Alignment results

We wrote a perl script to parse the output files of the individual programs and extracted identifier, alignment score and the percentage of identical residues within the alignment.

Mapping of identifier

The non-redundant database contains entries from various databases, including RefSeq, PDB, PIR, PRF, GenBank and Swiss-Prot. In order to compare results of NR database searches with the results of the HHpred searches, a mapping of the IDs is necessary. Furthermore, the entries in HSSP - which is used later to benchmark the alignment results - contains only references to the UniProtKB accession number (ACCNUM). To overcome this problem we downloaded a mapping table between the IDs from <ref>http://pir.georgetown.edu/pirwww/search/idmapping.shtml</ref>. This table was used - together with some short perl scripts - to map IDs between the databases and compare the results.

Summary of database searches

In this section, we give a short summary description of the search results of the individual programs and the compare them to each other.

Comparison of the methods

  • FASTA yielded with 4733 alignments the highest number of hits.
  • BLAST produced 252 alignments.
  • PSI-BLAST
    • Using an E-value cutoff of 0.005, PSI-BLAST produced 756 alignments for 3 iterations and 1257 for 5 iterations.
    • Using an E-value cutoff of 10E-6, PSI-BLAST produced 756 alignments for 3 iterations and 1257 for 5 iterations.
  • HHsearch produced 33 alignments for the search against PDB and 74 alignments for search against Interpro.

FASTA shows the highest number of alignments, probably due to the fact, that no e-value cutoff was chosen. Contrary, hhsearch has very few alignments. This could be ascribed to the fact, that completely different databases were used for the alignments and Interpro and pdb just did not have as much homolguous sequences as the nr database. This is also supported by the benchmark with HSSP (see next section). Aother interesting fact is that the results of PSI-BLAST depended for our parameter setting only on the number of iterations. Ragarding the results for the number of iterations, both e-value cutoffs yielded excepted of some single exceptions the same aligned target sequences from the database.

Overlap between methods
The number of shared target sequences between two methods is shown in the upper panel (self overlaps not shown). The lower panel depicts how many percent of the aligned target sequences of a given method (x-axis) are shared with the other methods.

The results of the four different PSI-BLAST runs show the highest overlap. The additional iterations find more related sequences and yield a higher number of alignments. Interestingly, almost all BLAST hits overlap with the PSI-BLAST and FASTA results. The overlaps of the searches, show that the number of hits highly depend on the database. hhpred1 does not have a good overlap with any of the other methods, but hhpred2 shares a significant part of its results with PSI-BLAST.

Scores and identity of aligned residues

coming soon...

The density of alignment scores and percentage of identical residues within the alignments are plotted
HSSP
Method Recall (GI) Recall (pdb) Precision (GI)
FASTA 0.92 0.67 0.23
BLAST 0.11 0.42 0.54
Psi-blast1 0.21 0.42 0.65
Psi-blast2 0.23 0.5 0.62
Psi-blast3 0.21 0.42 0.65
Psi-blast4 0.23 0.5 0.62
hhpred (pdb) 0.01 1 0.11
hhpred (interpro) 0.01 0.92 0.12


Multiple Alignments

For building the multiple Alignments the following sequences were chosen:

SeqIdentifier Seq Identity source Protein function
99-90% Sequence Identity
gi109094666 % bla unknown
gi281339526 % bla unknown
gi47522624 % bla unknown
gi149759319 % bla unknown
gi301763795 % bla unknown
89-60% Sequence Identity
1E2S % bla unknown
gi118081865 % bla unknown
gi126339031 % bla unknown
gi114326188 % bla unknown
gi164519052 % bla unknown
59-40% Sequence Identity
1HDH % bla unknown
1P49 % bla unknown
gi120537984 % bla unknown
gi301625378 % bla unknown
gi86142609 % bla unknown
39-20% Sequence Identity
1FSU % bla unknown
2VQR % bla unknown
3ED4 % bla unknown
gi113971721 % bla unknown
gi310635680 % bla unknown


The sequences with <20% and >99% sequence identitiy were ignored and 5 samples were randomly picked from the other ranges. So 20 sequences were available for the multiple alignments.


References

<references />