Sequence Search and Multiple Sequence Alignment (PKU)

Short Task Description

The goal of this task is to learn a bit about our protein of interest (phenylalanine hydroxylase/PheOH)from existing databases and comparing it to similar (and probably related) sequences. To do this, we searched the big80 database (7.73 mio sequences), which contains a subset of swissprot and pdb with sequence similarity of 80% or less, with blast (sequence comparison) and psi-blast (profile comparison) and searched a preprocessed and clustered version of uniprot (44,757 clusters) with the more advanced HHblits method (HMM comparison).

From the search results, we created several datasets sorted by sequence similarity (highly conserved, less conserved, a little conserved, ...) and created multiple aligmnents from these sets with four different tools. The results are listed below, the commands, programms and scripts we used are listed at the appropriate places in the text or linked to their own site.

Reference Sequence of PAH

>sp|P00439|PH4H_HUMAN Phenylalanine-4-hydroxylase OS=Homo sapiens GN=PAH PE=1 SV=1
MSTAVLENPGLGRKLSDFGQETSYIEDNCNQNGAISLIFSLKEEVGALAKVLRLFEENDV
NLTHIESRPSRLKKDEYEFFTHLDKRSLPALTNIIKILRHDIGATVHELSRDKKKDTVPW
FPRTIQELDRFANQILSYGAELDADHPGFKDPVYRARRKQFADIAYNYRHGQPIPRVEYM
EEEKKTWGTVFKTLKSLYKTHACYEYNHIFPLLEKYCGFHEDNIPQLEDVSQFLQTCTGF
RLRPVAGLLSSRDFLGGLAFRVFHCTQYIRHGSKPMYTPEPDICHELLGHVPLFSDRSFA
QFSQEIGLASLGAPDEYIEKLATIYWFTVEFGLCKQGDSIKAYGAGLLSSFGELQYCLSE
KPKLLPLELEKTAIQNYTVTEFQPLYYVAESFNDAKEKVRNFAATIPRPFSVRYDPYTQR
IEVLDNTQQLKILADSINSEIGILCSALQKI

Database Searches

Blast

time blast2 -p blastp -d /mnt/project/pracstrucfunc12/data/big/big -i Dropbox/Phenylketonuria/Task1/PAH.fasta -o results_blast2_standard

real 1m47.401s user 1m25.290s sys 0m18.280s

time blast2 -p blastp -d /mnt/project/pracstrucfunc12/data/big/big -i Dropbox/Phenylketonuria/Task1/PAH.fasta -o results_blast2_e-10 -e 0.0000000001 -v 2000

real 1m35.454s user 1m21.700s sys 0m3.100s

PSIBlast

time blastpgp -j 5 -d /mnt/project/pracstrucfunc12/data/big/big_80 -i Dropbox/Phenylketonuria/Task1/PAH.fasta -o psi_blast_standard_5_it

real 8m48.107s user 8m21.950s sys 0m8.730s iteration: 1 87.21user 8.37system 1:59.44elapsed 80%CPU (0avgtext+0avgdata 3990608maxresident)k 8852328inputs+1712outputs (222major+675658minor)pagefaults 0swaps iteration: 2 183.40user 5.77system 3:14.13elapsed 97%CPU (0avgtext+0avgdata 10788800maxresident)k 2794968inputs+3344outputs (205major+1343786minor)pagefaults 0swaps iteration: 3 284.08user 3.71system 4:49.33elapsed 99%CPU (0avgtext+0avgdata 10829616maxresident)k 104376inputs+5160outputs (25major+2015594minor)pagefaults 0swaps iteration: 4 389.89user 5.17system 6:36.74elapsed 99%CPU (0avgtext+0avgdata 10837360maxresident)k 56472inputs+6768outputs (9major+2685186minor)pagefaults 0swaps iteration: 5 499.89user 7.36system 8:29.33elapsed 99%CPU (0avgtext+0avgdata 10839264maxresident)k 12592inputs+8808outputs (5major+3354681minor)pagefaults 0swaps iteration: 6 615.74user 8.73system 10:27.22elapsed 99%CPU (0avgtext+0avgdata 10840096maxresident)k 74344inputs+10232outputs (5major+4024207minor)pagefaults 0swaps iteration: 7 736.57user 10.26system 12:30.19elapsed 99%CPU (0avgtext+0avgdata 10840880maxresident)k 168inputs+11912outputs (6major+4693733minor)pagefaults 0swaps iteration: 8 852.37user 12.37system 14:27.78elapsed 99%CPU (0avgtext+0avgdata 10841248maxresident)k 0inputs+13208outputs (0major+5363227minor)pagefaults 0swaps iteration: 9 978.60user 13.86system 16:36.34elapsed 99%CPU (0avgtext+0avgdata 10841328maxresident)k 0inputs+15368outputs (0major+6032716minor)pagefaults 0swaps iteration: 10 1093.38user 15.58system 18:33.79elapsed 99%CPU (0avgtext+0avgdata 10841552maxresident)k 0inputs+17144outputs (0major+6702196minor)pagefaults 0swaps

HHBlits

time hhblits -i Dropbox/Phenylketonuria/Task1/PAH.fasta -d /mnt/project/pracstrucfunc12/data/hhblits/uniprot20_current -o results_hhblits_standard

real 6m10.059s user 3m15.640s sys 0m40.220s

hhblits -i Dropbox/Phenylketonuria/Task1/PAH.fasta -d /mnt/project/pracstrucfunc12/data/hhblits/uniprot20_current -o results_hhblits_n4_e-7 -n 4 -e 0.0000001 -o results_hhblits_n4_e-7

HHSearch

time hhsearch -i Dropbox/Phenylketonuria/Task1/PAH.fasta -d /mnt/project/pracstrucfunc12/data/hhblits/uniprot20_current_hhm_db

real 13m27.782s user 13m18.120s sys 0m8.480s

PDB

Instead of mapping hits in big_80 to PDB to get structural information for the alignments, we performed an additional search in PDB at NCBI, with parameters: scoring matrix=PAM70, gap open = 10, gap extend = 1, composition based statistics, max. 1000 target sequences.

MSA

Datasets

We tried to create datasets of 4 sequences + reference sequence for the identity ranges (1: 90%-99%, 2: 60%-89%, 3: 40%-59%, 4: 20%-39%) from our search in the big_80 database. Since these results don't contain PDB structures, we additionally searched PDB directly for proteins in the required range and added them to the dataset. For the most conserved range, there is only 1 sequence in big_80, so we experimentally created the best possible highly conserved dataset in the range 80%-90% and used the structure of the reference sequence for 3D-coffee. The resulting datasets are shown in the following tables. All sequences have roughly the same length as the reference sequence except for G5AMD7 in the first set. G5AMD7 contains an insertion of 162 aa ,that is easily identified in the alignment, but shows a very high similarity in the other sections.

80-90% Sequence Identity
Sequence Identity	ID	Comment
90%	G1P4I7	Uncharacterized protein OS=Myotis lucifugus
89%	G5AMD7	Phenylalanine-4-hydroxylase OS=Heterocephalus glaber
80%	G1KSL1	Uncharacterized protein OS=Anolis carolinensis
100%	1PAH	used as 3D-Template only

60-89% Sequence Identity
Sequence Identity	ID	Comment
80%	G1KSL1	Uncharacterized protein OS=Anolis carolinensis
76%	Q4VBE2	Putative uncharacterized protein mgc108157 OS=Xenopus tropicalis
70%	H2UJM8	Uncharacterized protein OS=Takifugu rubripes
63%	D1LXB2	Phenylalanine hydroxlase OS=Saccoglossus kowalevskii
60%	2XSN_A	human Tyrosine 3-Monooxygenase, also used as 3D-Template

40-59% Sequence Identity
Sequence Identity	ID	Comment
58%	O96947	Phenylalanine hydroxylase OS=Geodia cydonium
55%	D3BKZ8	Phenylalanine 4-monooxygenase OS=Polysphondylium pallidum
49%	Q5RHI3	Novel protein similar to tyrosine hydroxylase OS=Danio rerio
44%	A6P4D3	Tyrosine hydroxylase OS=Dugesia japonica
59%	1TOH_A	Tyrosine hydroxylase from rattus norvegicus, also used as 3D-Template

20-39% Sequence Identity
Sequence Identity	ID	Comment
37%	F4WGX3	Phenylalanine-4-hydroxylase OS=Acromyrmex echinatior
35%	Q23A76	Biopterin-dependent aromatic amino acid hydroxylase family protein OS=Tetrahymena thermophila
29%	D0I5S9	Phenylalanine-4-hydroxylase OS=Grimontia hollisae
28%	F6G5X4	Phenylalanine-4-hydroxylase OS=Ralstonia solanacearum
31%	1LTU_A	Phenylalanine-4-hydroxylase from Chromobacterium violaceum, also used as 3D-Template

Raw Results

We present the alignments and basic statistics for the different tools. Images have been created in Jalview. To count gaps and conserved columns a simple python script (Collection of scripts) was used.

ClustalW

Command used to create the alignments:

clustalw -align -infile=NN.fasta -outfile=clustalW_NN.aln

Alignment of set 4 created with ClustalW

20-39% Sequence Identity
Sequence ID	Gaps
P00439	83
Q23A76	87
D0I5S9	272
F4WGX3	69
F6G5X4	181
1LTU_A	238
Conserved columns	19

Alignment of set 3 created with ClustalW

40-59% Sequence Identity
Sequence ID	Gaps
P00439	37
A6P4D3	1
Q5RHI3	14
D3BKZ8	45
O96947	39
1TOH_A	146
Conserved columns	109

Alignment of set 2 created with ClustalW

60-89% Sequence Identity
Sequence ID	Gaps
P00439	17
H2UJM8	7
Q4VBE2	24
G1KSL1	16
D1LXB2	18
2XSN_A	126
Conserved columns	159

Alignment of set 1 created with ClustalW

80-90% Sequence Identity
Sequence ID	Gaps
P00439	165
G1P4I7	162
G1KSL1	164
G5AMD7	4
Conserved columns	329

Muscle

Command used to create the alignments:

muscle -in NN.fasta -out muscle_NN.fasta

Alignment of set 4 created with Muscle

20-39% Sequence Identity
Sequence ID	Gaps
P00439	94
Q23A76	98
D0I5S9	283
F4WGX3	80
F6G5X4	192
1LTU_A	249
Conserved columns	22

Alignment of set 3 created with Muscle

40-59% Sequence Identity
Sequence ID	Gaps
P00439	45
A6P4D3	9
Q5RHI3	22
D3BKZ8	53
O96947	47
1TOH_A	154
Conserved columns	109

Alignment of set 2 created with Muscle

60-89% Sequence Identity
Sequence ID	Gaps
P00439	17
H2UJM8	7
Q4VBE2	24
G1KSL1	16
D1LXB2	18
2XSN_A	126
Conserved columns	159

Alignment of set 1 created with Muscle

80-90% Sequence Identity
Sequence ID	Gaps
P00439	167
G1P4I7	164
G1KSL1	166
G5AMD7	6
Conserved columns	328

T-coffee

Command used to create the alignments:

t_coffee NN.fasta

Alignment of set 4 created with T-Coffee

20-39% Sequence Identity
Sequence ID	Gaps
P00439	103
Q23A76	107
D0I5S9	292
F4WGX3	89
F6G5X4	201
1LTU_A	258
Conserved columns	22

Alignment of set 3 created with T-Coffee

40-59% Sequence Identity
Sequence ID	Gaps
P00439	53
A6P4D3	17
Q5RHI3	30
D3BKZ8	61
O96947	55
1TOH_A	162
Conserved columns	109

Alignment of set 2 created with T-Coffee

60-89% Sequence Identity
Sequence ID	Gaps
P00439	18
H2UJM8	8
Q4VBE2	25
G1KSL1	17
D1LXB2	19
2XSN_A	127
Conserved columns	159

Alignment of set 1 created with T-Coffee

80-90% Sequence Identity
Sequence ID	Gaps
P00439	165
G1P4I7	162
G1KSL1	164
G5AMD7	4
Conserved columns	329

3D-coffee

Command to create the alignments:

t_coffee NN.fasta -method sap_pair,slow_pair -template_file <PDB-ID>

Alignment of set 4 created with 3D-Coffee

20-39% Sequence Identity
Sequence ID	Gaps
P00439	96
Q23A76	100
D0I5S9	285
F4WGX3	82
F6G5X4	194
1LTU_A	251
Conserved columns	22

Alignment of set 3 created with 3D-Coffee

40-59% Sequence Identity
Sequence ID	Gaps
P00439	51
A6P4D3	15
Q5RHI3	28
D3BKZ8	59
O96947	53
1TOH_A	160
Conserved columns	109

Alignment of set 2 created with 3D-Coffee

60-89% Sequence Identity
Sequence ID	Gaps
P00439	21
H2UJM8	11
Q4VBE2	28
G1KSL1	20
D1LXB2	22
2XSN_A	130
Conserved columns	159

Alignment of set 1 created with 3D-Coffee

80-90% Sequence Identity
Sequence ID	Gaps
P00439	165
G1P4I7	162
G1KSL1	164
G5AMD7	4
Conserved columns	329

Discussion of the alignment results and alignment tools

Looking at the used tools, for these small datasets (4-6 sequences) there is not much of a difference in execution time, but t-coffee offers the most options and different modes (we used only two here, but it still counts). Comparing the results, the programms perform quite similar, but can be sorted by the basic statistics of inroduced gaps and found conserved columns in the following order: ClustalW> Muscle>3D-Coffee>T-Coffee

to be continued shortly..