Sequence and multiple alignments

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Revision as of 18:48, 23 May 2011 by Landerer (talk | contribs) (Multiple Alignments)

Sequence Alignments

Database search

Overlap.png

We used different tools for the search in a non-reduntant(NR) database like BLAST, FASTA and PSI-BLAST. Because of the absence of the database in a hmm format, we decided not to integrate the hhpred web-results. These results are not compareable.

We called BLAST and FASTA with the standart parameter. blast -p blastp -i 1a6z.fasta -d /data/nr/nr -o blastp_1a6z_on_NR.txt runtime 5:34
../../Desktop/fasta-36.3.4/bin/fasta36 -q 1a6z.fasta /data/nr/nr >fasta_1a5z_on_nr.txt the runtime was 10:44.

PSI-BLAST was used with different parameter settings. blastpgp -i 1a6z.fasta -d /data/nr/nr runtime 21:40
blastpgp -i 1a6z.fasta -d /data/nr/nr -j 6 -e 10E-6 > psiblast_on_NR_itera3_e-val_10E-6.txt runtime 23:49
blastpgp -i 1a6z.fasta -d /data/nr/nr -j 3 -e 10E-6 > psiblast_on_NR_itera6_e-val_10E-6.txt runtime 15:08
blastpgp -i 1a6z.fasta -d /data/nr/nr -j 3 > psiblast_on_NR_itera3.txt runtime 9:41
blastpgp -i 1a6z.fasta -d /data/nr/nr -j 6 > psiblast_on_NR_itera6.txt runtime 23:30
We also compared the runtime of the different tools. For PSI-BLAST, in our case, the e-Value and the number of iterations had no impact on the results.

Multiple Alignments

Used Sequences

SeqIdentifier Seq Identity source Protein function
99-90% Sequence Identity
AAG29575.1 91% BLAST xxx
1A6Z 90% BLAST xxx
XP_002816556.1 97.4% FASTA xxx
BAG62562.1 % FASTA xxx
AAH74721.1 % FASTA xxx
89-60% Sequence Identity
xxx % xxx xxx
xxx % xxx xxx
xxx % xxx xxx
xxx % xxx xxx
xxx % xxx xxx
59-40% Sequence Identity
xxx % xxx xxx
xxx % xxx xxx
xxx % xxx xxx
xxx % xxx xxx
xxx % xxx xxx
39-20% Sequence Identity
AAA39567.1 33% FASTA H-2D cell surface glycoprotein
NP_001029503.1 34% BLAST zinc-alpha-2-glycoprotein precursor
CAB56609.1 37% BLAST human leucocyte antigen A
CAF18417.1 36% BLAST MHC class I antigen
ACX42646.1 35.7% FASTA MHC class I antigen


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. Unfortunately no sequences in the range between 99-90% with known 3D-structure were found, so only sequences without known structure were used here.