Sequence Alignments HEXA

Sequence Searches

Use of database searching tools

• FASTA

/bin/fasta36 seq.fasta /data/blast/nr/nr > fasta_out.txt

• BLAST

blastall -p blastp -d /data/blast/nr/nr -i mult_seq.fasta > blast_out.txt

• PSIBLAST

blastpgn -i seq.fasta -j <#iterations> -h <e-value threshold> -d /data/blast/nr/nr > psiblast_out.txt

• HHSearch

For the HHSearch tool we used the online server for HHSearch.

Statistic results

For the statistical analysis we wrote a script which shows the distribution of the E-Value and the Identity as well as the different aligned sequences. Furthermore we create a Venn diagram to presentate the overlap between the results of the different searching methods (with http://bioinfogp.cnb.csic.es/tools/venny/index.html). First we compared the methods BLAST, FASTA and PsiBlast(PsiBlast with 3 and 5 runs and E-Value cutoff from 10E-6). Then we looked for the overlap of all done PsiBlasts.

Overlap of the aligned sequences

FASTA found a large number of matches which are not found by the other methods. By comparison the number of hits which were not found by BLAST or PsiBlast, is about 1400. This is much higher than the number of sequences which is found by FASTA and BLAST together. This leads to the conclusion that FASTA aligns many sequences which are probably less good or even wrong. The both different PsiBlast-variants deliver the same hits which are all also found by FASTA. Furthermore all resulting sequences by BLAST were also aligned by FASTA and the most of them are also by PsiBlast. Besides, we decided to compare different runs of PsiBlast. We compared PsiBlast with 3 iterations and an e-Value Cutoff of 0.005 and 10E-6 and also two PsiBlast runs with 5 iterations and the same two e-Value cutoffs as before. In this Vann-Digramm could be seen that the result overlap mostly. Only a few ones differ from the other. This leads to the fact, that PsiBlast with different iteration number and e-value deliver usually a similar result. In summary the BLAST-methods agree with each other. In contrast the FASTa-method delivers much more sequences which do not correspond which one of the other methods.

Overlap of results from BLAST, FASTA and PsiBlast

Overlap of the results from different PsiBlast Declaration: Psiblast 1: 3 Iterations, E-Value Cutoff: 0.005; Psiblast 2: 5 Iterations, E-Value Cutoff: 0.005 Psiblast 3: 3 Iterations, E-Value Cutoff: 10E-6; Psiblast 4: 5 Iterations, E-Value Cutoff, 10E-6

Distribution of the sequence identity and the e-value

The following plots show the distribution of the sequence idetities and the e-values of all used methods. Both values (x-axis) and their frequencies (y-axis) were extractet from the corresponding output-files.

The first image shows the distribution of the sequence identities. The first plot is the distribution for BLAST. Here could be seen that these identity-distribution is very balanced which means the low identities are approximate same common as the very high ones. The same goes for the HHSearch-plot. Contrary the Fasta-distribution has many high frequency for very small identities. This means that FASTA aligns many sequences although they have only a small sequence identity. This could explain why FASTA receives so many hits which do not agree with the other sequence searching tools (see Venn diagramm). The last four plots represent the corresponding distribution for the different PsiBlasts which were very similar. This is another in indication that PsiBlast received very similar results for the different parameters. Their distribution is also very balanced. There are high frequencies for small identities, middle identities and for high identities.

The second image shows the distribution of the e-values. The e-value is a measurement for the probability that a hit is resulting by chance. Therefore the smaller the e-value the better the alignment. All plots except the one for FASTA have high frequencies for small e-values whereby BLAST receives the smalles e-values. The e-values of FASTA have range from 0 to 8 where in contrast the other methods have no evalue higher than 1. Furthermore the highest BLAST e-value is at about 1e-29 which is still very low. In summary this shows again that BLAST deliver the best results and FASTA the worst ones.

Distribution of the sequence identities of the different methods

Distribution of the e-values of the different methods

True positive hits

HSSP (Homology-derived Secondary Structure of Proteins) lists proteins which are homologue and have a similar secondary structure. Therefore we use the HSSP alignment to check our results. Therefore we check how much overlap is between HSSP and the other methods. The overlapping sequences are the true positives.

Overlap between HSSP and FASTA

Overlap between HSSP and Blast

Overlap between HSSP and PsiBlast with 3 Iterations and 10E-6 cutoff

Overlap between HSSP and PsiBlast with 5 Iterations and 10E-6 cutoff

Overlap between HSSP and PsiBlast with 3 Iterations and 0.005 cutoff

Overlap between HSSP and psiBlast with 5 Iterations and 0.005 cutoff

With the results of these analysis, we created our file for the multiple alignments.

gi|212691177|ref|ZP_03299305.1 || 22% | PsiBlast, 3 Iterations, E-Value Cutoff = 10E-6

SeqIdentifier	Seq Identity	source
99%-90% Sequence Identity
109157872|pdb|2GK1	99%	Blast
179460|gb|AAA51827.1	99%	Blast
194375013|dbj|BAG62619.1	97%	Blast
296213630|ref|XP_002753354.1	95.1%	Fasta
297296816|ref|XP_002804897.1	93%	Blast
89%-60% Sequence Identity
149692271|ref|XP_001494361.1	85%	Blast
187607461|ref|NP_001119815.1	84.3%	Fasta
67514549|ref|NP_034551.2	84.1%	Fasta
74213671|dbj|BAE35636.1	84%	Blast
178056464|ref|NP_001116693.1	83.2%	Fasta
59%-40% Sequence Identity
187608414|ref|NP_001120459.1	58.3%	Fasta
213513173|ref|NP_001133930.1	57.0%	Fasta
38492599|pdb|1O7A	56%	Blast
867691|gb|AAA68620.1	55%	PsiBlast, 3 Iterations, E-Value Cutoff = 0.005
189239563|ref|XP_975660.2	47%	Blast
39%-20% Sequence Identity
299139410|ref|ZP_07032585.1	36%	PsiBlast, 3 Iterations, E-Value Cutoff = 0.005
281209747|gb|EFA83915.1	33%	Blast
166159759|gb|ABY83272.1	32%	PsiBlast, 5 Iterations, E-Value Cutoff = 0.005
251836937|pdb|3GH4	26.4%	Fasta

Multiple Alignments

• Cobalt

For coblat it was first necessary to install the programm on our virtual box: Download Cobalt from ftp://ftp.ncbi.nlm.nih.gov/pub/cobalt/executables/2.0.1/ (ncbi-cobalt-2.0.1-x64-linux.tar). Uncompress the archive file with tar xfz ncbi-cobalt-2.0.1-x64-linux.tar and change directory to the uncompressed cobalt directoy.

Call: ./cobalt -i mult_seq.fasta -norps T > cobalt_out.aln

• ClustalW

clustalw -infile=mult_seq.fasta > clustalW_out.aln

• Muscle

muscle -in mult_seq.fasta -out muscle_out.aln -clw

• T-Coffee

t_coffee -seq mult_seq.fasta

• T-Coffee (3D)

t_coffee -seq mult_seq.fasta -mode expresso

Conservation

Alignment methods		Conserved Columns
	Gaps	100% cons	>90% cons	>80% cons	>70% cons	>60% cons	>50% cons	>40% cons
Cobalt	384	31	68	75	87	76	0	65
ClustalW	346	29	61	81	84	71	0	65
Muscle	463	32	70	74	84	76	0	74
T-Coffee	609	31	67	74	90	73	0	70
3D T-Coffee	533	32	64	77	89	74	0	70

Gaps

Alignment methods		Secundary Structure
	#Gaps in sum	Helix	Extended	Coil	No secundary strucutre
Cobalt	384	5	5	1	373
ClustalW	346	2	0	0	244
Muscle	463	3	4	1	455
T-Coffee	609	4	7	4	594
3D T-Coffee	533	5	4	2	522

Functional residues

We found several functional residues from (LINK FEHLT NOCH). Because these residues are functionally important, these residues should be conserved. We compared the different alignments and looked if these resides are conserved.

Amino acids		Methods
	residue position	Cobalt	ClustalW	Muscle	T-Coffee	3D T-Coffee
R	178	conserved	conserved	conserved	conserved	conserved
D	207	conserved (once E)	conserved (once E)	conserved (once E)	conserved (once E)	conserved (once E)
H	262	conserved	conserved	conserved	conserved	conserved
D	322	conserved	conserved	conserved	conserved	conserved
E	323	conserved	conserved	conserved	conserved	conserved
W	373	conserved	conserved (once V, R)	conserved	conserved	conserved
W	392	conserved	conserved (once P, T, G)	conserved	conserved	conserved
Y	421	conserved	conserved (twice G, once -, S)	conserved	conserved	conserved (once H)
N	423	non-conserved	non-conserved	non-conserved	non-conserved	non-conserved
W	460	conserved (once -)	conserved (once -)	conserved (once -)	conserved (once -)	conserved (once -)
E	462	conserved (once -)	conserved (once Q)	conserved (once Q)	conserved (once -)	conserved (once -)