Difference between revisions of "Sequence-based predictions"
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==Phobius and PolyPhobius== |
==Phobius and PolyPhobius== |
Revision as of 23:05, 10 June 2011
Contents
Secondary structure prediction
PSIPRED
PSI-PRED use the PSI-BLAST output as input for a neuronal network which has a single hidden layer and a feed-forward back-propagation architecture to predict the secondary structure.
Results
PSI-PRED predicts a alpha/beta structure. The transmembrane region is predicted as a beta region.
PSIPRED HFORMAT (PSIPRED V3.0) Conf: 999851589999999877513567886245556456636899750389988756755687 Pred: CCCCCHHHHHHHHHHHHHHHCCCCCCCEEEEEEEEEEECCCCCCCEEEEEEEECCEEEEE AA: MGPRARPALLLLMLLQTAVLQGRLLRSHSLHYLFMGASEQDLGLSLFEALGYVDDQLFVF 10 20 30 40 50 60 Conf: 318998225536664688990669998865311211002358577441156788603899 Pred: ECCCCCCEEECCCCCCCCCCHHHHHHHHHHHHCCCCCHHHHHHHHHHHCCCCCCCCEEEE AA: YDHESRRVEPRTPWVSSRISSQMWLQLSQSLKGWDHMFTVDFWTIMENHNHSKESHTLQV 70 80 90 100 110 120 Conf: 987799319835459889765910588728988756689786135787788899999876 Pred: EEEEEEECCCEEEEEEEEEECCCEEEEECCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHH AA: ILGCEMQEDNSTEGYWKYGYDGQDHLEFCPDTLDWRAAEPRAWPTKLEWERHKIRARQNR 130 140 150 160 170 180 Conf: 310271499889888616322000378810000468999601699981450765189996 Pred: HHHCCCHHHHHHHHHHCCCCCCCCCCCCCEEEECCCCCCCEEEEEEEEEECCCCEEEEEE AA: AYLERDCPAQLQQLLELGRGVLDQQVPPLVKVTHHVTSSVTTLRCRALNYYPQNITMKWL 190 200 210 220 230 240 Conf: 288106667520025355899875899999965999872169986699998826885259 Pred: ECCEECCCCCCCCCCCEECCCCCEEEEEEEEECCCCCCCEEEEEECCCCCCCEEEEEECC AA: KDKQPMDAKEFEPKDVLPNGDGTYQGWITLAVPPGEEQRYTCQVEHPGLDQPLIVIWEPS 250 260 270 280 290 300 Conf: 999711124320001367777622367764115889887620212359 Pred: CCCCCEEEEEEEEEEEEEEEEEEEEEEEEEECCCCCCCCCCEEECCCC AA: PSGTLVIGVISGIAVFVVILFIGILFIILRKRQGSRGAMGHYVLAERE 310 320 330 340
Jpred3
Jpred use the Jnet algorithm which provides "a three-state (a-helix, ß-strand and coil) prediction of secondary structure at an accuracy of 81.5%" <ref>http://nar.oxfordjournals.org/content/36/suppl_2/W197.abstract</ref>.
Results
Jpred found in it's first blast search a lot of homologous hits with an e-value range from e-163 to 4e-44. There are some self hits included. We continued to the prediction which is:
Seq: MGPRARPALLLLMLLQTAVLQGRLLRSHSLHYLFMGASEQDLGLSLFEALGYVDD SS: ------HHHHHHHHHHHHH---------EEEEEEEEE-------EEEEEEEEE-- Seq: QLFVFYDHESRRVEPRTPWVSSRISSQMWLQLSQSLKGWDHMFTVDFWTIMENHN SS: EEEEEE-----EEEE----------HHHHHHHHHHHHHHHHHHHHHHHHHH---- Seq: HSKESHTLQVILGCEMQEDNSTEGYWKYGYDGQDHLEFCPDTLDWRAAEPRAWPT SS: -----EEEEEEEEEE------EEEEEEE-----EEEEEE----EEE-------HH Seq: KLEWERHKIRARQNRAYLERDCPAQLQQLLELGRGVLDQQVPPLVKVTHHVTSSV SS: HHHHH--HHHHHHHHHH------HHHHHHHHHH-H-------EEEEE-------- Seq: TTLRCRALNYYPQNITMKWLKDKQPMDAKEFEPKDVLPNGDGTYQGWITLAVPPG SS: -EEEEEEE------EEEEEEE----------EE----------EEEEEEEEE--- Seq: EEQRYTCQVEHPGLDQPLIVIWEPSPSGTLVIGVISGIAVFVVILFIGILFIILR SS: ---EEEEEEEE------EEEEE---------HHHHHHHHHHHHHHHHHHHHHHHH Seq: KRQGSRGAMGHYVLAERE SS: HH----------------
Comparison with DSSP
DSSP was designed by Wolfgang Kabsch and Chris Sander to provide a standard for the secondary structure assignment. DSSP calculates the secondary structure from PDB structures by using the distances between the atoms.
Results
Because, the PDB sequence is not complete, the dssp assignment is also incomplete. The interessting parts - the signal peptide and the cytoplasmic part - which are predicted as disordered are not covered by DSSP. PSIPRED and JPred predicted the transmembrane region well but assigned the - as disordered predicted - N- and C-terminus as a helical or beta sheet region. But the UniProt assignment gives no structure to this regions as well. Therefore, these regions may unstructured and not yet recognized as disordered regions.
UniProt: ---------------------------EEEEEEEEEEE----EEE--EEEEEE--EEEEE DSSP: --EEEEEEEEEEB-SS-SSB--EEEEEETTEEEEE PSIPRED: CCCCCHHHHHHHHHHHHHHHCCCCCCCEEEEEEEEEEECCCCCCCEEEEEEEECCEEEEE JPred: ------HHHHHHHHHHHHH---------EEEEEEEEE-------EEEEEEEEE--EEEEE AA: MGPRARPALLLLMLLQTAVLQGRLLRSHSLHYLFMGASEQDLGLSLFEALGYVDDQLFVF DSSPSeq: RSHSLHYLFMGASEQDLGLSLFEALGYVDDQLFVF 10 20 30 40 50 60 UniProt: EEEEE--EEE--------TTTHHHHHHHHHHHHHHHHHHHHHHHHHHTTT-EEE--EEEE DSSP: EESSS--EEE-STTS-SSTTTTHHHHHHHHHHHHHHHHHHHHHHHHHTTT-SSS--EEEE PSIPRED: ECCCCCCEEECCCCCCCCCCHHHHHHHHHHHHCCCCCHHHHHHHHHHHCCCCCCCCEEEE JPred: E-----EEEE----------HHHHHHHHHHHHHHHHHHHHHHHHHH---------EEEEE AA: YDHESRRVEPRTPWVSSRISSQMWLQLSQSLKGWDHMFTVDFWTIMENHNHSKESHTLQV DSSPSEQ: YDHESRRVEPRTPWVSSRISSQMWLQLSQSLKGWDHMFTVDFWTIMENHNHSKESHTLQV 70 80 90 100 110 120 UniProt: EEEEEE-----EEEEEEEEE--EEEEEEEHHH-EEEEEE---HHHHHHHH---HHHHHHH DSSP: EEEEEE-TTS-EEEEEEEEETTEEEEEEEGGGTEEEESSGGGHHHHHHHHSSTHHHHHHH PSIPRED: EEEEEEECCCEEEEEEEEEECCCEEEEECCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHH JPred: EEEEE------EEEEEEE-----EEEEEE----EEE-------HHHHHHH--HHHHHHHH AA: ILGCEMQEDNSTEGYWKYGYDGQDHLEFCPDTLDWRAAEPRAWPTKLEWERHKIRARQNR DSSPSEQ: ILGaEMQEDNSTEGYWKYGYDGQDHLEFCPDTLDWRAAEPRAWPTKLEWERHKIRARQNR 130 140 150 160 170 180 UniProt: HHHH-HHHHHHHHHHHHHTTT-------EEEEEEEE----EEEEEEEEEEEEE--EEEEE DSSP: HHHHTHHHHHHHHHHHHHTTTSS--B--EEEEEEEE-SS-EEEEEEEEEEBSS--EEEEE PSIPRED: HHHCCCHHHHHHHHHHCCCCCCCCCCCCCEEEECCCCCCCEEEEEEEEEECCCCEEEEEE JPred: HH------HHHHHHHHHH-H-------EEEEE---------EEEEEEE------EEEEEE AA: AYLERDCPAQLQQLLELGRGVLDQQVPPLVKVTHHVTSSVTTLRCRALNYYPQNITMKWL DSSPSEQ: AYLERDaPAQLQQLLELGRGVLDQQVPPLVKVTHHVTSSVTTLRbRALNYYPQNITMKWL 190 200 210 220 230 240 UniProt: E------HHH----EEEE-----EEEEEEEEE---HHHHEEEEEE---EEE-EEEE---- DSSP: ETTEE--GGGS---EEEE-TTS-EEEEEEEEE-TTGGGGEEEEEE-TTSSS-EEEE- PSIPRED: ECCEECCCCCCCCCCCEECCCCCEEEEEEEEECCCCCCCEEEEEECCCCCCCEEEEEECC JPred: E----------EE----------EEEEEEEEE------EEEEEEEE------EEEEE--- AA: KDKQPMDAKEFEPKDVLPNGDGTYQGWITLAVPPGEEQRYTCQVEHPGLDQPLIVIWEPS DSSPSEQ: KDKQPMDAKEFEPKDVLPNGDGTYQGWITLAVPPGEEQRYTbQVEHPGLDQPLIVIW 250 260 270 280 290 300 UniProt: ------------------------------------------------ DSSP: PSIPRED: CCCCCEEEEEEEEEEEEEEEEEEEEEEEEEECCCCCCCCCCEEECCCC JPred: ------HHHHHHHHHHHHHHHHHHHHHHHHHH---------------- AA: PSGTLVIGVISGIAVFVVILFIGILFIILRKRQGSRGAMGHYVLAERE DSSPSEQ: 310 320 330 340
Prediction of disordered regions
The HFE-Gen is not yet known as disordered. It is not contained in the Disprot<ref>http://www.disprot.org/</ref> database.
The prediction of unstructured regions predict serveral disorered regions in the protein, but most of them are predicted within secondary structure elements. Just the predicted disordered regions at the C- and N-terminus might be really unstructured but not yet experimentally recongnized because, these regions have no structural assignment.
The predictions are shown below.
DISOPRED
For the prediction, we used the DISOPRED-Server at http://bioinf.cs.ucl.ac.uk/disopred/
DISOPRED is a prediction tool for disordered regions based on a linear SVM. The SVM is trained with 750 non-redundant sequences with high resolution X-ray structures. "Disorder was identified with those residues that appear in the sequence records but with coordinates missing from the electron density map." <ref>http://bioinf.cs.ucl.ac.uk/index.php?id=806</ref> For each protein, a sequence profile was generated by using PSI-BLAST search against a filtered database. The PSI-BLAST profiles were used as input vectors for the SVM.
Result
Disopred predictes two disordered residues at the signal peptide and a disordered region at the end of the sequence which is located inside the cell.
AA:Target sequence Pred:Residue disorder prediction(.)= ordered residue(*)=Disordered residue conf:997600000000000000000000000000000000000000000000000000000000 pred:**.......................................................... AA:MGPRARPALLLLMLLQTAVLQGRLLRSHSLHYLFMGASEQDLGLSLFEALGYVDDQLFVF 10 20 30 40 50 60 conf:000120011000000000000000000000000000000000000000000000000000 pred:............................................................ AA:YDHESRRVEPRTPWVSSRISSQMWLQLSQSLKGWDHMFTVDFWTIMENHNHSKESHTLQV 70 80 90 100 110 120 conf:000000000000000000000000000000000000000000000000000000000000 pred:............................................................ AA:ILGCEMQEDNSTEGYWKYGYDGQDHLEFCPDTLDWRAAEPRAWPTKLEWERHKIRARQNR 130 140 150 160 170 180 conf:000000000000000000000002456777878777766530000000000000000000 pred:..............................*.*........................... AA:AYLERDCPAQLQQLLELGRGVLDQQVPPLVKVTHHVTSSVTTLRCRALNYYPQNITMKWL 190 200 210 220 230 240 conf:000035555545543000000000000000000000000000000000000001354667 pred:............................................................ AA:KDKQPMDAKEFEPKDVLPNGDGTYQGWITLAVPPGEEQRYTCQVEHPGLDQPLIVIWEPS 250 260 270 280 290 300 conf:777766643300000000000000047889999999999999898999 pred:...........................********************* AA:PSGTLVIGVISGIAVFVVILFIGILFIILRKRQGSRGAMGHYVLAERE 310 320 330 340 DISOPRED predictions for a false positive rate threshold of: 2%
POODLE
POODLE stands for Prediction Of Order and Disorder by machine LEarning.
POODLE provides three different predictions
- POODLE-S: short disorder regions prediction
- POODLE-L: long disorder regions prediction (longer 40 residues)
- unfolded protein prediction
All POODLE variants predict a disordered region at the end of the protein which contains a transmembrane region (pos: 307-330), this shows an evidance for a disordered region at the C-Terminus. But also, all variants predict a short disordered region at the beginning of the sequence which is a part of the signal peptid (pos: 1-22).
POODLE-I
POODLE-I (series only) predicted 4 disordered regions within the protein sequence.
MGPRARPALLLLMLLQTAVLQGRLLRSHSLHYLFMGASEQDLGLSLFEALGYVDDQLFVF **************---------------------------------------------- YDHESRRVEPRTPWVSSRISSQMWLQLSQSLKGWDHMFTVDFWTIMENHNHSKESHTLQV -------**********---******------*--------------------------- ILGCEMQEDNSTEGYWKYGYDGQDHLEFCPDTLDWRAAEPRAWPTKLEWERHKIRARQNR ------------------------------------------------------------ AYLERDCPAQLQQLLELGRGVLDQQVPPLVKVTHHVTSSVTTLRCRALNYYPQNITMKWL ---------------------***************------------------------ KDKQPMDAKEFEPKDVLPNGDGTYQGWITLAVPPGEEQRYTCQVEHPGLDQPLIVIWEPS ----*********----------------------------------------******* PSGTLVIGVISGIAVFVVILFIGILFIILRKRQGSRGAMGHYVLAERE ************************************************
POODLE-S
POODLE-S (using missing residues) predicts 6 short disordered regions within the protein sequence.
MGPRARPALLLLMLLQTAVLQGRLLRSHSLHYLFMGASEQDLGLSLFEALGYVDDQLFVF -**************--------------------------------------------- YDHESRRVEPRTPWVSSRISSQMWLQLSQSLKGWDHMFTVDFWTIMENHNHSKESHTLQV -------**********---******---------------------------------- ILGCEMQEDNSTEGYWKYGYDGQDHLEFCPDTLDWRAAEPRAWPTKLEWERHKIRARQNR ------------------------------------------------------------ AYLERDCPAQLQQLLELGRGVLDQQVPPLVKVTHHVTSSVTTLRCRALNYYPQNITMKWL ---------------------***************------------------------ KDKQPMDAKEFEPKDVLPNGDGTYQGWITLAVPPGEEQRYTCQVEHPGLDQPLIVIWEPS ----*********----------------------------------------******* PSGTLVIGVISGIAVFVVILFIGILFIILRKRQGSRGAMGHYVLAERE *--------------------------------********-------
POODLE-S (using High B-Factor residues) predicts 2 short disordered regions within the protein sequence.
MGPRARPALLLLMLLQTAVLQGRLLRSHSLHYLFMGASEQDLGLSLFEALGYVDDQLFVF -*-***------------------------------------------------------ YDHESRRVEPRTPWVSSRISSQMWLQLSQSLKGWDHMFTVDFWTIMENHNHSKESHTLQV ------------------------------------------------------------ ILGCEMQEDNSTEGYWKYGYDGQDHLEFCPDTLDWRAAEPRAWPTKLEWERHKIRARQNR ------------------------------------------------******------ AYLERDCPAQLQQLLELGRGVLDQQVPPLVKVTHHVTSSVTTLRCRALNYYPQNITMKWL ------------------------------------------------------------ KDKQPMDAKEFEPKDVLPNGDGTYQGWITLAVPPGEEQRYTCQVEHPGLDQPLIVIWEPS ------------------------------------------------------------ PSGTLVIGVISGIAVFVVILFIGILFIILRKRQGSRGAMGHYVLAERE ------------------------------------------------
POODLE-L
POODLE-L predicts a disordered region from 296 to the end.
MGPRARPALLLLMLLQTAVLQGRLLRSHSLHYLFMGASEQDLGLSLFEALGYVDDQLFVF ------------------------------------------------------------ YDHESRRVEPRTPWVSSRISSQMWLQLSQSLKGWDHMFTVDFWTIMENHNHSKESHTLQV ------------------------------------------------------------ ILGCEMQEDNSTEGYWKYGYDGQDHLEFCPDTLDWRAAEPRAWPTKLEWERHKIRARQNR ------------------------------------------------------------ AYLERDCPAQLQQLLELGRGVLDQQVPPLVKVTHHVTSSVTTLRCRALNYYPQNITMKWL ------------------------------------------------------------ KDKQPMDAKEFEPKDVLPNGDGTYQGWITLAVPPGEEQRYTCQVEHPGLDQPLIVIWEPS ------------------------------------------------------****** PSGTLVIGVISGIAVFVVILFIGILFIILRKRQGSRGAMGHYVLAERE ************************************************
IUPRED
IUPRED use the estimated pairwise energy to recognize unstructured regions within protein sequnces. For these, they use the assumption, that all globular proteins have an amino acid composision which gives it the potential to form a large number of favorable interactions.
Results
The short term prediction predicts 5 short regions. There are also disordered residues at the beginning and in the signal peptide.
MGPRARPALLLLMLLQTAVLQGRLLRSHSLHYLFMGASEQDLGLSLFEALGYVDDQLFVF ***--------------------------------------------------------- YDHESRRVEPRTPWVSSRISSQMWLQLSQSLKGWDHMFTVDFWTIMENHNHSKESHTLQV ------------------------------------------------------------ ILGCEMQEDNSTEGYWKYGYDGQDHLEFCPDTLDWRAAEPRAWPTKLEWERHKIRARQNR ------------------------------------------------------------ AYLERDCPAQLQQLLELGRGVLDQQVPPLVKVTHHVTSSVTTLRCRALNYYPQNITMKWL ------------------------------------------------------------ KDKQPMDAKEFEPKDVLPNGDGTYQGWITLAVPPGEEQRYTCQVEHPGLDQPLIVIWEPS ---------********----------***--------*-****---------------- PSGTLVIGVISGIAVFVVILFIGILFIILRKRQGSRGAMGHYVLAERE ---------------------------------------------***
The long term prediction predicted 7 disordered residues, but just one short region.
MGPRARPALLLLMLLQTAVLQGRLLRSHSLHYLFMGASEQDLGLSLFEALGYVDDQLFVF ------------------------------------------------------------ YDHESRRVEPRTPWVSSRISSQMWLQLSQSLKGWDHMFTVDFWTIMENHNHSKESHTLQV ------------------------------------------------------------ ILGCEMQEDNSTEGYWKYGYDGQDHLEFCPDTLDWRAAEPRAWPTKLEWERHKIRARQNR ------------------------------------------------------------ AYLERDCPAQLQQLLELGRGVLDQQVPPLVKVTHHVTSSVTTLRCRALNYYPQNITMKWL ------------------------------------------------------------ KDKQPMDAKEFEPKDVLPNGDGTYQGWITLAVPPGEEQRYTCQVEHPGLDQPLIVIWEPS ---------******-------------------------*------------------- PSGTLVIGVISGIAVFVVILFIGILFIILRKRQGSRGAMGHYVLAERE ------------------------------------------------
The prediction of sturcured regions predicts one globular domain from 1-348. This means, that the whole protein is structured. This is a contradiction to the prediction of POODLE, but because of the weak evidence given by the other IUPRED-methods not a real contradiction to the other results of IUPRED.
META-Disorder
For this task, we used the PredictProtein Server at https://www.predictprotein.org. META-Disorder, published in 2009 by Avner Schlessinger, Marco Punta, Guy Yachdav, Laszlo Kajan and Burkhard Rost, use a combined prediction of ORSnet PROFbval and Ucon.
predicted secondary structure composision
sec str type | H | E | L |
---|---|---|---|
% in protein | 27.30 | 28.74 | 43.97 |
Prediction of disordered residues by META-Disorder (last coloumn)
Number Residue NORSnet NORS2st PROFbval bval2st Ucon Ucon2st MD_raw MD_rel MD2st
.... 242 D 0.13 - 0.70 D 0.76 D 0.444 2 - 243 K 0.13 - 0.69 D 0.76 D 0.480 1 - 244 Q 0.13 - 0.66 D 0.93 D 0.531 0 D 245 P 0.17 - 0.73 D 0.92 D 0.520 0 D 246 M 0.28 - 0.65 D 0.90 D 0.525 0 D 247 D 0.31 - 0.68 D 0.87 D 0.515 0 - 248 A 0.36 - 0.70 D 0.87 D 0.520 0 D 249 K 0.40 - 0.69 D 0.89 D 0.485 1 - .... 344 L 0.37 - 0.59 D 0.18 - 0.515 0 - 345 A 0.35 - 0.74 D 0.17 - 0.515 0 - 346 E 0.31 - 0.89 D 0.17 - 0.520 0 D 347 R 0.35 - 0.91 D 0.23 - 0.525 0 D 348 E 0.34 - 0.92 D 0.38 - 0.520 0 D
Key for output ---------------- Number - residue number Residue - amino-acid type NORSnet - raw score by NORSnet (prediction of unstructured loops) NORS2st - two-state prediction by NORSnet; D=disordered PROFbval - raw score by PROFbval (prediction of residue flexibility from sequence) Bval2st - two-state prediction by PROFbval Ucon - raw score by Ucon (prediction of protein disorder using predicted internal contacts) Ucon2st - two-state prediction by Ucon MD - raw score by MD (prediction of protein disorder using orthogonal sources) MD_rel - reliability of the prediction by MD; values range from 0-9. 9=strong prediction MD2st - two-state prediction by MD
META-Disorder predict a very short disordered region of 3 residues at the end of the protein but with a week evidence of around 0.5. Therefore it is quite unlikely to have a disorered region at the C-Terminus if we just look at this method.
Prediction of transmembrane alpha-helices and signal peptides
General
We were given five additional proteins to work with and predict transmembrane regions, signal peptides and GO terms for. That was done, because most of the practials proteins are no membrane proteins and therefore produce only "no membrane" results. Thus the three membrane proteins [BACR_HALSA], [LAMP1_HUMAN] and [A4_HUMAN] were provided, but also our HFE Protein [HFE_HUMAN] is an membrane protein.
To give you a quick overview about the protein properties, look at the following table:
Accession | Entry name | Organism | Subcelluar location |
Q30201 | HFE_HUMAN | Homo sapiens (Human) | Membrane; Single-pass type I membrane protein |
P02945 | BACR_HALSA | Halobacterium salinarium / (Halobacterium halobium) | Cell membrane; Multi-pass membrane protein |
P02753 | RET4_HUMAN | Homo sapiens (Human) | Secreted |
Q9Y5Q6 | INSL5_HUMAN | Homo sapiens (Human) | Secreted |
P11279 | LAMP1_HUMAN | Homo sapiens (Human) | Cell membrane; Single-pass type I membrane protein [...] |
P05067 | A4_HUMAN | Homo sapiens (Human) | Membrane; Single-pass type I membrane protein |
We are going to predict membranes and signaling for these six proteins using different tools. Because our normally adressed protein HFE_HUMAN is an membrane protein and therefore we see the prediction accurancy by using it, we will give only graphical and detailed overview about the results of HFE_HUMAN and group the additional proteins in textual form.
We use the entries at UniProt for the real groundtruth and compare the prediction results shortly with them.
TMHMM
TMHMM is a tool for predicting membrane topology (transmembrane helices) in proteins based on a hidden Markov model with different states. It devides the regions in "inside", "outside" and "TMhelix". But TMHMM can not predict Signal Peptides
TMHMM was used locally in our linux box, after correcting some path issues inside some config files.
The command we used was:
- tmhmm x.fasta > x.tmhmm
where 'x' stands for one of the UniProt entry name of the proteins. Afterwards we tried to plot the result of HFE_HUMAN with gnuplot, but this was not working either, because of path issues inside the (automatically created) gnuplot script of tmhmm. After correcting the path issues again, gnuplot worked fine and produced successfully graphical output.
A color code is applied to provide easier reading:
- green: The predicted region matches the experimental resolved region from UniProt (+/- 5 residues allowed). TMHMM succeeded.
- yellow: The predicted region does only partially match the experimental region (mostly errors with signaling peptides). TMHMM has to be improved.
- red: The predicted region does absolutely not match the experimental region. TMHMM failed.
TMHMM | UniProt | ||||||
---|---|---|---|---|---|---|---|
id | version | region | start | end | region | start | end |
Q30201|HFE_HUMAN | TMHMM2.0 | outside | 1 | 306 | Signal peptide | 1 | 22 |
Q30201|HFE_HUMAN | Extracelluar | 23 | 306 | ||||
Q30201|HFE_HUMAN | TMHMM2.0 | TMhelix | 307 | 329 | Helical | 307 | 330 |
Q30201|HFE_HUMAN | TMHMM2.0 | inside | 330 | 348 | Cytoplasmic | 331 | 348 |
TMHMM misses clearly the the signal peptide and counts the region as outside (1-306), which is correct according to UniProt. Also the TMhelix (307-329) and the inside region (330-348) is placed right, only with one amino acid deviation, but that is insignificant. Therefore TMHMM was very successful in prediction of right regions. The results are shown in the figure to the right, too.
TMHMM | UniProt | ||||||
---|---|---|---|---|---|---|---|
id | version | region | start | end | region | start | end |
sp_P02945_BACR_HALSA | TMHMM2.0 | outside | 1 | 22 | Extracellular | 14 | 23 |
sp_P02945_BACR_HALSA | TMHMM2.0 | TMhelix | 23 | 42 | Helical; Name=Helix A | 24 | 42 |
sp_P02945_BACR_HALSA | TMHMM2.0 | inside | 43 | 54 | Cytoplasmic | 43 | 56 |
sp_P02945_BACR_HALSA | TMHMM2.0 | TMhelix | 55 | 77 | Helical; Name=Helix B | 57 | 75 |
sp_P02945_BACR_HALSA | TMHMM2.0 | outside | 78 | 91 | Extracellular | 76 | 91 |
sp_P02945_BACR_HALSA | TMHMM2.0 | TMhelix | 92 | 114 | Helical; Name=Helix C | 92 | 109 |
sp_P02945_BACR_HALSA | TMHMM2.0 | inside | 115 | 120 | Cytoplasmic | 110 | 120 |
sp_P02945_BACR_HALSA | TMHMM2.0 | TMhelix | 121 | 143 | Helical; Name=Helix D | 121 | 140 |
sp_P02945_BACR_HALSA | TMHMM2.0 | outside | 144 | 147 | Extracellular | 141 | 147 |
sp_P02945_BACR_HALSA | TMHMM2.0 | TMhelix | 148 | 170 | Helical; Name=Helix E | 148 | 167 |
sp_P02945_BACR_HALSA | TMHMM2.0 | inside | 171 | 189 | Cytoplasmic | 168 | 185 |
sp_P02945_BACR_HALSA | TMHMM2.0 | TMhelix | 190 | 212 | Helical; Name=Helix F | 186 | 204 |
sp_P02945_BACR_HALSA | TMHMM2.0 | outside | 213 | 262 | Extracellular | 205 | 216 |
Helical; Name=Helix G | 217 | 236 | |||||
Cytoplasmic | 237 | 262 |
As clearly visible, TMHMM is also capable of prediction regions of non eukaroynts almost completely correctly. Only the last helical and cytoplasmic regions are missed.
TMHMM | UniProt | ||||||
---|---|---|---|---|---|---|---|
id | version | region | start | end | region | start | end |
sp_P02753_RET4_HUMAN | TMHMM2.0 | outside | 1 | 201 | Signal peptide | 1 | 18 |
TMHMM misses the signaling peptide but everything else is superb, because RET4_Human is a protein that gets secreted.
TMHMM | UniProt | ||||||
---|---|---|---|---|---|---|---|
id | version | region | start | end | region | start | end |
sp_Q9Y5Q6_INSL5_HUMAN | TMHMM2.0 | outside | 1 | 135 | Signal peptide | 1 | 22 |
As usual, the TMHMM misses the signaling peptide but predicts accuratly. INSL5_Human is a hormone and thus sectred at the extracellular regions.
TMHMM | UniProt | ||||||
---|---|---|---|---|---|---|---|
id | version | region | start | end | region | start | end |
sp_P11279_LAMP1_HUMAN | TMHMM2.0 | inside | 1 | 10 | Signal peptide | 1 | 28 |
sp_P11279_LAMP1_HUMAN | TMHMM2.0 | TMhelix | 11 | 33 | |||
sp_P11279_LAMP1_HUMAN | TMHMM2.0 | outside | 34 | 383 | Lumenal | 29 | 382 |
sp_P11279_LAMP1_HUMAN | TMHMM2.0 | TMhelix | 384 | 406 | Helical | 383 | 405 |
sp_P11279_LAMP1_HUMAN | TMHMM2.0 | inside | 407 | 417 | Cytoplasmic | 406 | 417 |
TMHMM | UniProt | ||||||
---|---|---|---|---|---|---|---|
id | version | region | start | end | region | start | end |
sp_P05067_A4_HUMAN | TMHMM2.0 | outside | 1 | 700 | Signal peptide | 1 | 17 |
Extracellular | 18 | 699 | |||||
sp_P05067_A4_HUMAN | TMHMM2.0 | TMhelix | 701 | 723 | Helical | 700 | 723 |
sp_P05067_A4_HUMAN | TMHMM2.0 | inside | 724 | 770 | Cytoplasmic | 724 | 770 |
TMHMM predicted again almost correctly and missed only the beginning unpredictable signaling peptide.
Phobius and PolyPhobius
For Phobius and PolyPhobius, we used the webservice<ref>http://www.ncbi.nlm.nih.gov/pubmed/17483518?dopt=Abstract</ref> at http://phobius.sbc.su.se/ with standard settings.
Phobius is a combined predictor for transmembrane protein topology and signal peptide. Phobius models different regions of the seuqence in a series of interconnected states of a HMM.<ref>http://www.ncbi.nlm.nih.gov/pubmed/15111065?dopt=Abstract</ref>
PolyPhobius is a hidden Markov model (HMM) decoding algorithm. It combines probabilities for sequence features of homologs by considering the average of the posterior label probability of each position in a global sequence alignment. PolyPhobius is benchmarked by Phobius. <ref>http://www.ncbi.nlm.nih.gov/pubmed/15961464?dopt=Abstract</ref>
Phobius
Phobius predicts very accurate as seen below. The transmembrane region is predicted just 1-2 residues upstream from the annotated region. The same holds for the topological domains before and after the transmembrane region. Also the signal peptid is correctly predicted.
PREDICTED ANNOTATION ID sp|Q30201|HFE_HUMAN FT SIGNAL 1 21 | 1-20 FT REGION 1 7 N-REGION. FT REGION 8 16 H-REGION. FT REGION 17 21 C-REGION. FT TOPO_DOM 22 304 NON CYTOPLASMIC. | 23-306 FT TRANSMEM 305 329 | 307-330 FT TOPO_DOM 330 348 CYTOPLASMIC. | 331-348
PolyPhobius
PolyPhobius also predicts very accurate but in our case not as accurate as Phobius.
PREDICTED ANNOTATION ID sp|Q30201|HFE_HUMAN FT SIGNAL 1 23 | 1-20 FT REGION 1 5 N-REGION. FT REGION 6 19 H-REGION. FT REGION 20 23 C-REGION. FT TOPO_DOM 24 304 NON CYTOPLASMIC. | 23-306 FT TRANSMEM 305 329 | 307-330 FT TOPO_DOM 330 348 CYTOPLASMIC. | 331-348
OCTOPUS and SPOCTOPUS
OCTOPUS is a combined mehtod of HMM's and artificial neural networks. OCTOPUS first create a sequence profile by homology search using BLAST. The profile is used as the input to a set of neural networks which predict the preferance of the location for each residue. Each residue is predicted to be either inside or outside the cell and located in a transmembrane (M), interface (I), close loop (L) or globular loop (G) environment.
SPOCTOPUS is an extended version of OCTOPUS that can also predict signal peptides. It use a neural network to predict a signal peptide if the score for each of the 70 N-Terminal residues is high enough.
Both, OCTOPUS and SPOCTOPUS predict the signal peptide and the transmembrane region correctly as you can see in the images below. Also both methods predict a signal peptide at the N-terminus which has the correct length.
SignalP
For using it locally at our linux box, we had to correct again some path issues.
The command we used was:
- signalp -t y x.fasta > x.signalp
where 'x' stands again for the UniProt entry names of the proteins. 'y' was chosen accordingly to the organism of the protein, for all human proteins 'y' was set to eukaryotes 'euk' and for the bacterial protein P02945 to gram- 'gram-'. This switch specifies the neural network and hidden Markov models, that are seperatly trained for different organismns.
For the graphical output of HFE_HUMAN we used the SignalP server from: http://www.cbs.dtu.dk/services/SignalP
There are three scorings for the SignalP-prediction NN:
- C-score: 'cleavage site': raw cleavage site prediction
- S-mean-score: 'average of the S-score': discrimination of secretory and non-secretory proteins
- Y-max-score: 'combination of C-score with s-core': better cleavage site prediction
sp|Q30201|HFE_HUMAN length = 348 Measure Position Value Cutoff signal peptide? max. C 23 0.534 0.32 YES max. Y 23 0.599 0.33 YES max. S 16 0.995 0.87 YES mean S 1-22 0.935 0.48 YES D 1-22 0.767 0.43 YES Most likely cleavage site between pos. 22 and 23: LQG-RL
>sp|Q30201|HFE_HUMAN Prediction: Signal peptide Signal peptide probability: 0.998 Signal anchor probability: 0.000 Max cleavage site probability: 0.297 between pos. 22 and 23
SignalP predicts an signal peptide probability with almost 1.0 and thus an signal anchor probability with 0. This leads to the prediction of an cleavage site between pos. 22 and 23.
According to UniProt is there an signal peptide, it starts at pos. 1 to 22, which means, SignalP has predicted the signal peptide and cleavage site with 100% accurancy.
TODO TODO TODO TODO short version!
>sp_P02945_BACR_HALSA Bacteriorhodopsin OS_Halobacterium salinarium _strain ATCC 700922 _ JCM 11081 _ NRC-1_ GN_bop PE_1 SV_2
SignalP-NN result: >sp_P02945_BACR_HALSA length = 70
- Measure Position Value Cutoff signal peptide?
max. C 16 0.331 0.52 NO max. Y 43 0.066 0.33 NO max. S 32 0.948 0.92 YES mean S 1-42 0.216 0.49 NO D 1-42 0.141 0.44 NO
- Most likely cleavage site between pos. 42 and 43: FLV-KG
SignalP-HMM result: >sp_P02945_BACR_HALSA Prediction: Non-secretory protein Signal peptide probability: 0.000 Max cleavage site probability: 0.000 between pos. 15 and 16
>sp_P02753_RET4_HUMAN Retinol-binding protein 4 OS_Homo sapiens GN_RBP4 PE_1 SV_3
SignalP-NN result: >sp_P02753_RET4_HUMAN length = 70
- Measure Position Value Cutoff signal peptide?
max. C 19 0.929 0.32 YES max. Y 19 0.901 0.33 YES max. S 1 0.994 0.87 YES mean S 1-18 0.938 0.48 YES D 1-18 0.920 0.43 YES
- Most likely cleavage site between pos. 18 and 19: GRA-ER
SignalP-HMM result: >sp_P02753_RET4_HUMAN Prediction: Signal peptide Signal peptide probability: 1.000 Signal anchor probability: 0.000 Max cleavage site probability: 0.979 between pos. 18 and 19
>sp_Q9Y5Q6_INSL5_HUMAN Insulin-like peptide INSL5 OS_Homo sapiens GN_INSL5 PE_1 SV_2
SignalP-NN result: >sp_Q9Y5Q6_INSL5_HUMA length = 70
- Measure Position Value Cutoff signal peptide?
max. C 23 0.855 0.32 YES max. Y 23 0.778 0.33 YES max. S 13 0.987 0.87 YES mean S 1-22 0.852 0.48 YES D 1-22 0.815 0.43 YES
- Most likely cleavage site between pos. 22 and 23: VRS-KE
SignalP-HMM result: >sp_Q9Y5Q6_INSL5_HUMAN Prediction: Signal peptide Signal peptide probability: 0.999 Signal anchor probability: 0.000 Max cleavage site probability: 0.911 between pos. 22 and 23
>sp_P11279_LAMP1_HUMAN Lysosome-associated membrane glycoprotein 1 OS_Homo sapiens GN_LAMP1 PE_1 SV_3
SignalP-NN result: >sp_P11279_LAMP1_HUMA length = 70
- Measure Position Value Cutoff signal peptide?
max. C 29 0.978 0.32 YES max. Y 29 0.903 0.33 YES max. S 19 0.999 0.87 YES mean S 1-28 0.960 0.48 YES D 1-28 0.932 0.43 YES
- Most likely cleavage site between pos. 28 and 29: ASA-AM
SignalP-HMM result: >sp_P11279_LAMP1_HUMAN Prediction: Signal peptide Signal peptide probability: 1.000 Signal anchor probability: 0.000 Max cleavage site probability: 0.847 between pos. 28 and 29
>sp_P05067_A4_HUMAN Amyloid beta A4 protein OS_Homo sapiens GN_APP PE_1 SV_3
SignalP-NN result: >sp_P05067_A4_HUMAN length = 70
- Measure Position Value Cutoff signal peptide?
max. C 18 0.891 0.32 YES max. Y 18 0.850 0.33 YES max. S 2 0.992 0.87 YES mean S 1-17 0.967 0.48 YES D 1-17 0.909 0.43 YES
- Most likely cleavage site between pos. 17 and 18: ARA-LE
SignalP-HMM result: >sp_P05067_A4_HUMAN Prediction: Signal peptide Signal peptide probability: 1.000 Signal anchor probability: 0.000 Max cleavage site probability: 0.993 between pos. 17 and 18
TargetP
TargetP predict for each of the proteins a signal preptide with high probability. But P02945 which is a bacteria and has no signal peptide, the method seems to be pretty accurate.
### targetp v1.1 prediction results ################################## Number of query sequences: 6 Cleavage site predictions included. Using NON-PLANT networks. Name Len mTP SP other Loc RC TPlen ---------------------------------------------------------------------- sp_Q30201_HFE_HUMAN 348 0.433 0.912 0.004 S 3 22 sp_P02945_BACR_HALSA 262 0.019 0.897 0.562 S 4 116 sp_P02753_RET4_HUMAN 201 0.242 0.928 0.020 S 2 18 sp_Q9Y5Q6_INSL5_HUMA 135 0.074 0.899 0.037 S 1 22 sp_P11279_LAMP1_HUMA 417 0.043 0.953 0.017 S 1 28 sp_P05067_A4_HUMAN 770 0.035 0.937 0.084 S 1 17 ---------------------------------------------------------------------- cutoff 0.000 0.000 0.000
Prediction of GO terms
General
HFE_HUMAN is annotated with 27 different GO Terms which are <ref>http://www.ebi.ac.uk/QuickGO/GProtein?ac=Q30201</ref>:
GOID | GO Term | Aspect |
---|---|---|
GO:0002474 | antigen processing and presentation of peptide antigen via MHC class I | Process |
GO:0005515 | protein binding | Function |
GO:0005737 | cytoplasm | Component |
GO:0005769 | early endosome | Component |
GO:0005886 | plasma membrane | Component |
GO:0005887 | integral to plasma membrane | Component |
GO:0006461 | protein complex assembly | Process |
GO:0006810 | transport | Process |
GO:0006811 | ion transport | Process |
GO:0006826 | iron ion transport | Process |
GO:0006879 | cellular iron ion homeostasis | Process |
GO:0006898 | receptor-mediated endocytosis | Process |
GO:0006955 | immune response | Process |
GO:0007565 | female pregnancy | Process |
GO:0010106 | cellular response to iron ion starvation | Process |
GO:0016020 | membrane | Component |
GO:0016021 | integral to membrane | Component |
GO:0019882 | antigen processing and presentation | Process |
GO:0031410 | cytoplasmic vesicle | Component |
GO:0042446 | hormone biosynthetic process | Process |
GO:0042612 | MHC class I protein complex | Component |
GO:0045177 | apical part of cell | Component |
GO:0045178 | basal part of cell | Component |
GO:0048471 | perinuclear region of cytoplasm | Component |
GO:0055037 | recycling endosome | Component |
GO:0055072 | iron ion homeostasis | Process |
GO:0060586 | multicellular organismal iron ion homeostasis | Process |
GOPET
Gopet predicted 2 GO-Terms which have no overlap to the annotation.
GOID | Aspect | Confidence | GO Term |
---|---|---|---|
GO:0004872 | Molecular Function | 91% | receptor activity |
GO:0030106 | Molecular Function | 88% | MHC class I receptor activity |
Pfam
Pfam is a database that contains protein domains and families. For our search we used the webserver at http://pfam.sanger.ac.uk/search with standard values.
Afterwards we used the pfam2go database, to find the GO-entries matching the pfam descriptions.
Pfam classifies the HFE_Human protein into two families:
- Family: MHC_I (PF00129)
- Family: C1-set (PF07654)
For the PF00129 family are four hits at the pfam2go data:
Pfam:PF00129 MHC_I > GO:immune response ; GO:0006955 Pfam:PF00129 MHC_I > GO:antigen processing and presentation ; GO:0019882 Pfam:PF00129 MHC_I > GO:membrane ; GO:0016020 Pfam:PF00129 MHC_I > GO:MHC class I protein complex ; GO:0042612
All those GO-Entries are at the UniProt entry about HFE_Human, so this family is correct.
For the PF07654 family are no entries at the pfam2go data and thus no validateable crosslinks to UniProt, maybe this family is just unitl now not included in the pfam2go data.
For a more detailed picture have a look at the figure on the right, you can see the Pfam-A matches with alignment.
ProtFun 2.2
ProtFun is an ab initio prediction server.
Results
ProtFun assignet immune response(GO:0006955;Process) to HFE what is correct. But ProtFun predict just one correct GO-number for the HFE-Gen.
Functional category Prob Odds
Amino_acid_biosynthesis 0.011 0.484
Biosynthesis_of_cofactors 0.105 1.452
Cell_envelope => 0.633 10.377
Cellular_processes 0.095 1.297
Central_intermediary_metabolism 0.231 3.663
Energy_metabolism 0.059 0.659
Fatty_acid_metabolism 0.016 1.265
Purines_and_pyrimidines 0.583 2.400
Regulatory_functions 0.013 0.079
Replication_and_transcription 0.019 0.073
Translation 0.079 1.801
Transport_and_binding 0.732 1.785
Enzyme/nonenzyme Prob Odds
Enzyme 0.208 0.727
Nonenzyme => 0.792 1.110
Enzyme class Prob Odds
Oxidoreductase (EC 1.-.-.-) 0.084 0.404
Transferase (EC 2.-.-.-) 0.062 0.179
Hydrolase (EC 3.-.-.-) 0.135 0.425
Lyase (EC 4.-.-.-) 0.049 1.054
Isomerase (EC 5.-.-.-) 0.010 0.321
Ligase (EC 6.-.-.-) 0.042 0.827
Gene Ontology category Prob Odds
Signal_transducer 0.201 0.939
Receptor 0.353 2.076
Hormone 0.002 0.365
Structural_protein 0.005 0.190
Transporter 0.024 0.219
Ion_channel 0.008 0.147
Voltage-gated_ion_channel 0.002 0.085
Cation_channel 0.010 0.221
Transcription 0.036 0.283
Transcription_regulation 0.018 0.147
Stress_response 0.274 3.108
Immune_response => 0.381 4.486
Growth_factor 0.013 0.943
Metal_ion_transport 0.009 0.02
Reference
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