ASPA Sequence Based Predictions
Contents
Prediction of Secondary Structure Elements
PsiPred
# PSIPRED HFORMAT (PSIPRED V3.0)
Conf: 987522213466199993246776008999999984450000587389976339987971
Pred: CCCCCCCCCCCCEEEEEECCCCCCHHHHHHHHHHHHCCCCCCCCCCEEEEEECCHHHHHH
AA: MTSCHIAEEHIQKVAIFGGTHGNELTGVFLVKHWLENGAEIQRTGLEVKPFITNPRAVKK
10 20 30 40 50 60
Conf: 998788998878786647999999984999999999988199999997428994187898
Pred: CCCCCCCCCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHCCCCCCCCCCEEEECCCCCC
AA: CTRYIDCDLNRIFDLENLGKKMSEDLPYEVRRAQEINHLFGPKDSEDSYDIIFDLHNTTS
70 80 90 100 110 120
Conf: 999505864599448999999998762999737862048886301220027861499667
Pred: CCCCEEEEECCCCHHHHHHHHHHHHHCCCCCEEEEECCCCCCCCHHHHCCCCCCEEEEEC
AA: NMGCTLILEDSRNNFLIQMFHYIKTSLAPLPCYVYLIEHPSLKYATTRSIAKYPVGIEVG
130 140 150 160 170 180
Conf: 877898808999999999999998976406998899973479998113515579877700
Pred: CCCCCCCHHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCEEEEEEEEEEECCCCCCCCCE
AA: PQPQGVLRADILDQMRKMIKHALDFIHHFNEGKEFPPCAIEVYKIIEKVDYPRDENGEIA
190 200 210 220 230 240
Conf: 552467669998546888832213699778518622057770372000011102000100
Pred: EEECCCCCCCCCCCCCCCCCCCCCCCCCEEEECCCCCEEEEECCCCHHCCCCHHHEECCE
AA: AIIHPNLQDQDWKPLHPGDPMFLTLDGKTIPLGGDCTVYPVFVNEAAYYEKKEAFAKTTK
250 260 270 280 290 300
Conf: 3544256113309
Pred: EEEEECCCEEECC
AA: LTLNAKSIRCCLH
310
JPred3
JPred3 was published in 1998 by Christian Cole, Jonathan D. Barber and Geoffrey J. Barton.
Reference: Original paper, current version
JPred3 uses the JNet 2.0 algorithm to make its predictions. This algorithm generates profiles using PSI-Blast (which is used to build a position-specific scoring matrix) and HMMer (which is used to construct HMM profiles.) Both position-specific scoring matrix and the HMMs are used to predict secondary structure and solvent accessibility.
Input: A protein sequence or a pre-made MSA; a PDB database is needed, too, but provided by the JPred3 server.
MTSCHIAEEHIQKVAIFGGTHGNELTGVFLVKHWLENGAEIQRTGLEVKPFITNPRAVKKCTRYID ------------EEEEEEEE------HHHHHHHHHH---------EEEEEEEE-HHHHHH-----H CDLNRIFDLENLGKKMSEDLPYEVRRAQEINHLFGPKDSEDSYDIIFDLHNTTSNMGCTLILEDSR ---------------------HHHHHHHHHHHHHH-------EEEEEE-----------EEEE--- NNFLIQMFHYIKTSLAPLPCYVYLIEHPSLKYATTRSIAKYPVGIEVGPQPQGVLRADILDQMRKM -HHHHHHHHHHHH------EEEEEE---------HHEE----EEEEE---------HHHHHHHHHH IKHALDFIHHFNEGKEFPPCAIEVYKIIEKVDYPRDENGEIAAIIHPNLQDQDWKPLHPGDPMFLT HHHHHHHHHHH----------EEEEEEEEEE----------EEEE----------------HHE-- LDGKTIPLGGDCTVYPVFVNEAAYYEKKEAFAKTTKLTLNAKSIRCCLH ----EEEE----EEEEEEE-----HHH-HHHHHHHHEEE-----EEEE-
DSSP
DSSP (Define Secondary Structure of Proteins) is a software for secondary structure assignment and was published in 1983 by Wolfgang Kabsch and Chris Sander. Reference: Original paper
DSSP does not predict secondary structure from amino acid sequences; instead, it uses a 3D structure (a PDB file) to deduce the secondary structure from the 3D structure. To this end, DSSP examines the phi and psi angles and the C alpha positions in the protein backbone and H-bonds present in the structure; these are used to define "n-turns", which are H-bonds between the NH and CO groups of amino acids with sequence separations of 3-5 residues, and "bridges" with greater sequence separations. Repeating 4-turns are used to identify helices, repeating bridges identify beta sheets.
Input: A 3D structure (a PDB file, ID 2o53 in our case)
Output: (from [1])
H = alpha helix
B = residue in isolated beta-bridge
E = extended strand, participates in beta ladder
G = 3-helix (3/10 helix)
I = 5 helix (pi helix)
T = hydrogen bonded turn
S = bend
The results differ from those of the two secondary structure predictors, as the PDB file contains a dimer, whereas the Uniprot sequence only contains one domain (which is a sensible thing, since both domains are essentially identical.)
The prediction shows slight differences between both domains; we assume that reasons for this are slight differences in the actual 3D structure of the two chains as well as H-bonds between the two chains.
10 20 30 40 50 60
| | | | | |
1 - 60 EHIQKVAIFGGTHGNELTGVFLVKHWLENGAEIQRTGLEVKPFITNPRAVKKCTRYIDCD
1 - 60 SSSSSS TTTT HHHHHHHHHHTT 333 TT SSSSSST HHHHHTTTT TTT
1 - 60
1 - 60 AA AA A AA AAA AA AAAA A A AA AAAA AAAA
70 80 90 100 110 120
| | | | | |
61 - 120 LNRIFDLENLGKKMSEDLPYEVRRAQEINHLFGPKDSEDSYDIIFDLHNTTSNMGCTLIL
61 - 120 333 THHHHTT TTT HHHHHHHHHHHHH TTTTTT TSSSSSSS TTT SSSSSS
61 - 120 ** * * ** ** * *
61 - 120 A AAA AAAAAAAAA A A AA AAA AA A
130 140 150 160 170 180
| | | | | |
121 - 180 EDSRNNFLIQMFHYIKTSLAPLPCYVYLIEHPSLKYATTRSIAKYPVGIEVGPQPQGVLR
121 - 180 T TT HHHHHHHHHHHHHHTTT SSSSS TT 3333TTSSSSSSSST TT
121 - 180 * ** **
121 - 180 A A A AA AAA AAAA A AAAAAA AA A A A
190 200 210 220 230 240
| | | | | |
181 - 240 ADILDQMRKMIKHALDFIHHFNEGKEFPPCAIEVYKIIEKVDYPRDENGEIAAIIHPNLQ
181 - 240 HHHHHHHHHHHHHHHHHHHHHHTT SSSSSSSSSSSS TTT TSS TTTT
181 - 240
181 - 240 A AA AA AA AA AAAA AA A A A AAA A AAAAA A AA
250 260 270 280 290 300
| | | | | |
241 - 300 DQDWKPLHPGDPMFLTLDGKTIPLGGDCTVYPVFVNEAAYYEKKEAFAKTTKLTLNAKSI
241 - 300 T TTT TTTSSSS TT SSS TTT SSSTTT 333TTTT TSSSSSSSSSSS
241 - 300
241 - 300 AA AA AAAAA A AAAAAA AAAAA A AAA A AAA A A
301 - 302 RC
301 - 302
301 - 302
301 - 302 AA
310 320 330 340 350 360
| | | | | |
303 - 362 EHIQKVAIFGGTHGNELTGVFLVKHWLENGAEIQRTGLEVKPFITNPRAVKKCTRYIDCD
303 - 362 SSSSSS TTTT HHHHHHHHHHHH 3333 TT SSSSSST HHHHHTT T TTT
303 - 362
303 - 362 AA AA AA AAA AA AAAA A A A AA AAAA AAAA
370 380 390 400 410 420
| | | | | |
363 - 422 LNRIFDLENLGKKMSEDLPYEVRRAQEINHLFGPKDSEDSYDIIFDLHNTTSNMGCTLIL
363 - 422 333 THHHHTT TTT HHHHHHHHHHHHH TTTTTT TSSSSSSS TTT SSSSSS
363 - 422 ** *** * ** ****
363 - 422 A AAA AAAAAAAAA A A AA AAA AA A
430 440 450 460 470 480
| | | | | |
423 - 482 EDSRNNFLIQMFHYIKTSLAPLPCYVYLIEHPSLKYATTRSIAKYPVGIEVGPQPQGVLR
423 - 482 T TT HHHHHHHHHHHHHHTTT SSSSS TTTT 3333TTSSSSSSSS TT
423 - 482
423 - 482 A A A AA AA AAAA A AAAAAA AA A A
490 500 510 520 530 540
| | | | | |
483 - 542 ADILDQMRKMIKHALDFIHHFNEGKEFPPCAIEVYKIIEKVDYPRDENGEIAAIIHPNLQ
483 - 542 HHHHHHHHHHHHHHHHHHHHHHTT SSSSSSSSSSSS TTT TSS TTTT
483 - 542 *** *
483 - 542 A AA AA A AA A AA AA A A A AAA A AAAAA A A AA
550 560 570 580 590 600
| | | | | |
543 - 602 DQDWKPLHPGDPMFLTLDGKTIPLGGDCTVYPVFVNEAAYYEKKEAFAKTTKLTLNAKSI
543 - 602 T TTT TTTSSSS TT SSS TTT SSSTTT THHHHTT TSSSSSSSSSSS
543 - 602 *
543 - 602 AA AA AAAAA A AAAAAA AAAAA A AAA A AAAA A AA
603 - 604 RC
603 - 604
603 - 604
603 - 604 AA
Clearly solvent accessible: A; involved in symmetry contacts: *
All in all, the two prediction methods Psipred and JPred3 did a good job; they managed to predict most of the main secondary structure elements, with only minor variations in length and position of the individual helices/sheets and very minor variations between each other. A somewhat more detailed result from DSSP is to be expected, as it has pointedly better information to and merely assigns instead of actually predicting the secondary structure.
Prediction of disordered regions
DISOPRED
DISOPRED predicts native disorder in proteins. It was published in 2004 by Ward JJ, Sodhi JS, McGuffin LJ, Buxton BF and Jones DT. Reference: [2]
DISOPRED uses linear support vector machines to predict disorder in a given protein sequence. A set of 750 proteins with high-quality structures was used as training data; to this end, PSI-Blast profiles were generated by aligning the training structures against a filtered database of protein structures. The resulting profiles were used to train the SVMs.
DISOPRED predictions for a false positive rate threshold of: 2%
conf: 999999999877640000000000000000000000000000000000000000000000
pred: **********..................................................
AA: MTSCHIAEEHIQKVAIFGGTHGNELTGVFLVKHWLENGAEIQRTGLEVKPFITNPRAVKK
10 20 30 40 50 60
conf: 000000000000000356777788777654200000000000000000000000000000
pred: ......................**....................................
AA: CTRYIDCDLNRIFDLENLGKKMSEDLPYEVRRAQEINHLFGPKDSEDSYDIIFDLHNTTS
70 80 90 100 110 120
conf: 000000000000000000000000000000000000000000000000000000000000
pred: ............................................................
AA: NMGCTLILEDSRNNFLIQMFHYIKTSLAPLPCYVYLIEHPSLKYATTRSIAKYPVGIEVG
130 140 150 160 170 180
conf: 000000000000000000000000000000000000000000000000000000000000
pred: ............................................................
AA: PQPQGVLRADILDQMRKMIKHALDFIHHFNEGKEFPPCAIEVYKIIEKVDYPRDENGEIA
190 200 210 220 230 240
conf: 000000000000000000000000000000000000000000000000000000000000
pred: ............................................................
AA: AIIHPNLQDQDWKPLHPGDPMFLTLDGKTIPLGGDCTVYPVFVNEAAYYEKKEAFAKTTK
250 260 270 280 290 300
conf: 0000000000002
pred: .............
AA: LTLNAKSIRCCLH
310
Asterisks (*) represent disorder predictions and dots (.)
prediction of order. The confidence estimates give a rough
indication of the probability that each residue is disordered.
POODLE
POODLE (Prediction Of Order and Disorder by machine LEarning) is a series of programs published between 2005 and 2008. We used the latest variant, POODLE-I, which was published in 2008 by S.Hirose, K.Shimizu, N.Inoue, S.Kanai and T.Noguchi.
Reference: S.Hirose, K.Shimizu, N.Inoue, S.Kanai and T.Noguchi, "Disordered region prediction by integrating POODLE series", CASP8 Proceedings 2008, 14-15.
Input: Protein amino acid sequence
POODLE-I is an integrated variant of other flavors of POODLE (-S and -L for short/long regions of disorder and -W for proteins that are mostly disordered) and several other tools like Psipred, JNet etc. It employs a rather involved workflow.
Custom-formatted output for Aspartoacyclase:
POS 1 M T S C H I A E E H I
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.461 0.444 0.413 0.401 0.418 0.461 0.537 0.644 0.693 0.62 0.468
POS 12 Q K V A I F G G T H G
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.321 0.238 0.177 0.146 0.128 0.116 0.106 0.104 0.111 0.126 0.132
POS 23 N E L T G V F L V K H
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.131 0.118 0.098 0.073 0.053 0.041 0.036 0.035 0.035 0.036 0.036
POS 34 W L E N G A E I Q R T
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.038 0.045 0.06 0.081 0.099 0.119 0.133 0.146 0.147 0.143 0.129
POS 45 G L E V K P F I T N P
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.111 0.09 0.073 0.062 0.054 0.047 0.039 0.033 0.033 0.037 0.041
POS 56 R A V K K C T R Y I D
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.043 0.047 0.054 0.062 0.068 0.071 0.073 0.07 0.067 0.069 0.075
POS 67 C D L N R I F D L E N
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.08 0.081 0.078 0.075 0.073 0.072 0.076 0.094 0.127 0.176 0.249
POS 78 L G K K M S E D L P Y
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.403 0.554 0.737 0.766 0.804 0.755 0.682 0.65 0.632 0.636 0.583
POS 89 E V R R A Q E I N H L
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.505 0.448 0.348 0.262 0.201 0.16 0.131 0.11 0.103 0.104 0.111
POS 100 F G P K D S E D S Y
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.116 0.117 0.108 0.089 0.067 0.049 0.039 0.034 0.033 0.035
POS 110 D I I F D L H N T T
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.038 0.041 0.043 0.043 0.042 0.041 0.042 0.045 0.052 0.06
POS 120 S N M G C T L I L E
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.07 0.081 0.092 0.101 0.109 0.111 0.107 0.096 0.085 0.072
POS 130 D S R N N F L I Q M
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.06 0.051 0.046 0.04 0.036 0.033 0.032 0.031 0.031 0.031
POS 140 F H Y I K T S L A P
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.033 0.036 0.04 0.043 0.046 0.049 0.05 0.053 0.055 0.059
POS 150 L P C Y V Y L I E H
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.065 0.073 0.088 0.103 0.115 0.119 0.118 0.111 0.104 0.104
POS 160 P S L K Y A T T R S
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.121 0.147 0.19 0.229 0.264 0.263 0.245 0.196 0.149 0.098
POS 170 I A K Y P V G I E V
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.069 0.053 0.051 0.057 0.066 0.08 0.093 0.102 0.103 0.099
POS 180 G P Q P Q G V L R A
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.096 0.094 0.095 0.095 0.099 0.098 0.099 0.095 0.094 0.086
POS 190 D I L D Q M R K M I
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.074 0.059 0.048 0.04 0.038 0.038 0.038 0.039 0.04 0.043
POS 200 K H A L D F I H H F
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.046 0.049 0.051 0.052 0.056 0.064 0.077 0.092 0.112 0.142
POS 210 N E G K E F P P C A
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.17 0.198 0.21 0.311 0.281 0.248 0.105 0.084 0.072 0.071
POS 220 I E V Y K I I E K V
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.069 0.065 0.06 0.056 0.052 0.054 0.062 0.076 0.105 0.141
POS 230 D Y P R D E N G E I
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.176 0.203 0.224 0.227 0.217 0.209 0.228 0.248 0.271 0.282
POS 240 A A I I H P N L Q D
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.289 0.269 0.24 0.208 0.188 0.169 0.155 0.152 0.167 0.193
POS 250 Q D W K P L H P G D
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.222 0.236 0.235 0.21 0.175 0.136 0.11 0.097 0.099 0.104
POS 260 P M F L T L D G K T
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.107 0.108 0.104 0.095 0.084 0.077 0.073 0.082 0.102 0.125
POS 270 I P L G G D C T V Y
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.144 0.162 0.169 0.166 0.156 0.149 0.133 0.117 0.099 0.089
POS 280 P V F V N E A A Y Y
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.077 0.072 0.067 0.064 0.066 0.082 0.122 0.184 0.241 0.279
POS 290 E K K E A F A K T T
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.282 0.264 0.236 0.229 0.238 0.257 0.263 0.252 0.231 0.222
POS 300 K L T L N A K S I R
-1 -1 -1 -1 -1 -1 -1 -1 -1 -1
0.246 0.278 0.305 0.31 0.303 0.277 0.263 0.371 0.382 0.38
POS 310 C C L H
-1 -1 -1 -1
0.348 0.51 0.496 0.489
IUPRED
IUPRED is a software for the prediction of intrinsically unstructured regions in proteins. It was published in 2005 by Zsuzsanna Dosztányi, Veronika Csizmók, Péter Tompa and István Simon.
Reference: IUPred: web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content Zsuzsanna Dosztányi, Veronika Csizmók, Péter Tompa and István Simon, Bioinformatics (2005) 21, 3433-3434.
IUPRED predicts disordered regions by estimating the capacity of the amino acid chain to form stabilizing contacts. The underlying assumption is that proteins intrinsically unable to do so have distinct sequences that can be identified via their unfavorable energy values. To this end a 20x20 predictor matrix was calculated from a set of globular proteins with known structure. IUPRED uses this matrix to derive a tendency to be intrinsically unstructured from the amino acid composition alone.
Input: An amino acid sequence.
IUPRED comes in three flavors: Long Disorder, which specializes in finding long stretches of disorder, Short Disorder, which does the same for short stretches of disorder, and structured regions, which predicts regions lacking disorder.
Long Disorder
POS 1 M T S C H I A E E H I
0.3215 0.3426 0.2817 0.2783 0.2064 0.1275 0.1554 0.1823 0.2094 0.2364 0.2575
POS 12 Q K V A I F G G T H G
0.2988 0.3087 0.2364 0.3215 0.3149 0.3321 0.2609 0.1823 0.1275 0.1206 0.1759
POS 23 N E L T G V F L V K H
0.1028 0.0676 0.1070 0.1298 0.1881 0.2575 0.2715 0.1969 0.2034 0.2034 0.2064
POS 34 W L E N G A E I Q R T
0.1942 0.1206 0.1914 0.1399 0.1373 0.2064 0.2002 0.1969 0.2541 0.2715 0.2951
POS 45 G L E V K P F I T N P
0.3840 0.4256 0.3460 0.3321 0.3286 0.2609 0.2503 0.3249 0.2292 0.1583 0.1611
POS 56 R A V K K C T R Y I D
0.0985 0.1554 0.0929 0.1373 0.1424 0.0765 0.0749 0.1229 0.0749 0.0780 0.0719
POS 67 C D L N R I F D L E N
0.0424 0.0506 0.0734 0.0734 0.0605 0.1048 0.1115 0.1184 0.1229 0.2064 0.1323
POS 78 L G K K M S E D L P Y
0.2258 0.1643 0.2364 0.2292 0.2002 0.2884 0.4087 0.3215 0.4119 0.3948 0.3053
POS 89 E V R R A Q E I N H L
0.2849 0.2849 0.3149 0.3182 0.3631 0.3667 0.3667 0.3631 0.4441 0.3286 0.4220
POS 100 F G P K D S E D S Y
0.3215 0.3053 0.1969 0.2034 0.1611 0.1501 0.1476 0.2224 0.2164 0.2164
POS 110 D I I F D L H N T T
0.3053 0.3704 0.3704 0.2609 0.2680 0.1823 0.1184 0.0662 0.0690 0.0734
POS 120 S N M G C T L I L E
0.1229 0.1184 0.1914 0.2817 0.2849 0.2034 0.2064 0.2193 0.1759 0.0985
POS 130 D S R N N F L I Q M
0.0948 0.0581 0.0327 0.0398 0.0414 0.0719 0.0414 0.0581 0.1092 0.1092
POS 140 F H Y I K T S L A P
0.1162 0.0662 0.0398 0.0269 0.0163 0.0105 0.0115 0.0184 0.0275 0.0300
POS 150 L P C Y V Y L I E H
0.0372 0.0433 0.0424 0.0405 0.0581 0.0618 0.0618 0.0618 0.1007 0.0749
POS 160 P S L K Y A T T R S
0.0543 0.0870 0.0443 0.0888 0.1007 0.1424 0.1449 0.2292 0.2470 0.2328
POS 170 I A K Y P V G I E V
0.2575 0.2503 0.2752 0.3667 0.3704 0.3948 0.3426 0.3356 0.3019 0.3149
POS 180 G P Q P Q G V L R A
0.2328 0.2328 0.2752 0.2951 0.3321 0.3087 0.3631 0.3182 0.3182 0.2918
POS 190 D I L D Q M R K M I
0.3494 0.3182 0.2164 0.2129 0.1115 0.0605 0.0592 0.0870 0.0734 0.0780
POS 200 K H A L D F I H H F
0.1048 0.0967 0.1501 0.2364 0.1349 0.1399 0.1942 0.1206 0.1048 0.0817
POS 210 N E G K E F P P C A
0.1449 0.1048 0.0618 0.0734 0.0704 0.0389 0.0835 0.1349 0.0948 0.1028
POS 220 I E V Y K I I E K V
0.1115 0.1184 0.1092 0.1184 0.1323 0.1275 0.2129 0.2094 0.1229 0.1731
POS 230 D Y P R D E N G E I
0.1731 0.1759 0.1028 0.1476 0.2470 0.2609 0.2680 0.3631 0.3566 0.3740
POS 240 A A I I H P N L Q D
0.4476 0.3392 0.4256 0.4256 0.3460 0.3356 0.3392 0.3249 0.3392 0.3460
POS 250 Q D W K P L H P G D
0.3910 0.3215 0.2783 0.3631 0.3667 0.3774 0.3566 0.3392 0.4220 0.3321
POS 260 P M F L T L D G K T
0.3426 0.2541 0.2436 0.3426 0.3566 0.2470 0.3286 0.2680 0.1643 0.1852
POS 270 I P L G G D C T V Y
0.1298 0.0631 0.0543 0.1048 0.1731 0.1449 0.1881 0.1115 0.0646 0.0734
POS 280 P V F V N E A A Y Y
0.0690 0.1092 0.1048 0.1399 0.0765 0.0646 0.0581 0.1028 0.1007 0.1373
POS 290 E K K E A F A K T T
0.1449 0.1298 0.1184 0.2034 0.2364 0.2164 0.2002 0.1583 0.1823 0.1852
POS 300 K L T L N A K S I R
0.1881 0.1184 0.1184 0.1184 0.0888 0.0851 0.1349 0.1349 0.1137 0.0870
POS 310 C C L H
0.0631 0.0473 0.0734 0.0483
Short Disorder
POS 1 M T S C H I A E E H I
0.8886 0.7772 0.7418 0.6984 0.5992 0.5296 0.4149 0.2748 0.2333 0.1921 0.1566
POS 12 Q K V A I F G G T H G
0.1805 0.1844 0.1732 0.2700 0.1766 0.2531 0.2913 0.2080 0.1292 0.0832 0.0965
POS 23 N E L T G V F L V K H
0.0909 0.0991 0.0935 0.0660 0.1088 0.1766 0.1766 0.1495 0.1566 0.0991 0.1041
POS 34 W L E N G A E I Q R T
0.1041 0.0909 0.1456 0.0935 0.0935 0.0909 0.1416 0.2385 0.2080 0.1416 0.1322
POS 45 G L E V K P F I T N P
0.1844 0.2963 0.2820 0.2558 0.1921 0.2167 0.2041 0.1998 0.1921 0.1921 0.1380
POS 56 R A V K K C T R Y I D
0.0935 0.1495 0.0935 0.1416 0.0935 0.0771 0.1322 0.1416 0.0935 0.0965 0.0464
POS 67 C D L N R I F D L E N
0.0490 0.0567 0.0542 0.0554 0.0567 0.0935 0.0813 0.0858 0.1292 0.1958 0.1322
POS 78 L G K K M S E D L P Y
0.2385 0.1732 0.2558 0.1958 0.1878 0.2432 0.2963 0.3184 0.4149 0.3359 0.3399
POS 89 E V R R A Q E I N H L
0.4116 0.3491 0.2820 0.2913 0.3535 0.3399 0.3456 0.3399 0.4333 0.4078 0.4825
POS 100 F G P K D S E D S Y
0.3992 0.4651 0.4149 0.3578 0.3005 0.2820 0.1878 0.2483 0.2385 0.2385
POS 110 D I I F D L H N T T
0.2963 0.3668 0.3630 0.2865 0.2963 0.2209 0.2122 0.1292 0.0789 0.0441
POS 120 S N M G C T L I L E
0.0771 0.0771 0.1117 0.1635 0.2333 0.2209 0.1878 0.1292 0.0771 0.0858
POS 130 D S R N N F L I Q M
0.0660 0.0336 0.0316 0.0226 0.0102 0.0179 0.0179 0.0327 0.0279 0.0363
POS 140 F H Y I K T S L A P
0.0387 0.0173 0.0218 0.0128 0.0078 0.0044 0.0055 0.0059 0.0055 0.0055
POS 150 L P C Y V Y L I E H
0.0070 0.0167 0.0194 0.0200 0.0387 0.0212 0.0160 0.0157 0.0327 0.0455
POS 160 P S L K Y A T T R S
0.0387 0.0414 0.0279 0.0441 0.0455 0.0884 0.0991 0.1602 0.1635 0.1602
POS 170 I A K Y P V G I E V
0.1088 0.0965 0.1150 0.1878 0.2167 0.3146 0.3535 0.2865 0.2080 0.2080
POS 180 G P Q P Q G V L R A
0.1766 0.2748 0.2333 0.1667 0.2531 0.2385 0.2748 0.2748 0.3630 0.3184
POS 190 D I L D Q M R K M I
0.3146 0.3096 0.2748 0.2292 0.1292 0.1292 0.0744 0.0701 0.1150 0.1117
POS 200 K H A L D F I H H F
0.0723 0.0701 0.1150 0.1732 0.1602 0.1602 0.1205 0.1456 0.1766 0.1532
POS 210 N E G K E F P P C A
0.1958 0.1322 0.1416 0.1178 0.1205 0.1088 0.1205 0.1240 0.1380 0.1322
POS 220 I E V Y K I I E K V
0.1566 0.1698 0.1060 0.1266 0.1178 0.1240 0.2080 0.1766 0.1566 0.2292
POS 230 D Y P R D E N G E I
0.1878 0.2432 0.2041 0.2041 0.2122 0.2122 0.3225 0.3992 0.3005 0.3359
POS 240 A A I I H P N L Q D
0.4149 0.4245 0.5173 0.4078 0.4116 0.4245 0.3359 0.3263 0.3578 0.3399
POS 250 Q D W K P L H P G D
0.4282 0.4825 0.4703 0.4651 0.4600 0.4600 0.3399 0.3578 0.4333 0.4078
POS 260 P M F L T L D G K T
0.3885 0.2913 0.3053 0.3096 0.3184 0.2820 0.3630 0.3005 0.2657 0.1998
POS 270 I P L G G D C T V Y
0.1205 0.1205 0.1041 0.1018 0.1117 0.1150 0.1844 0.1380 0.1117 0.0701
POS 280 P V F V N E A A Y Y
0.0425 0.0744 0.0567 0.0909 0.0965 0.0744 0.0387 0.0464 0.0441 0.0607
POS 290 E K K E A F A K T T
0.0991 0.0771 0.0660 0.1041 0.0935 0.0935 0.0660 0.0832 0.1041 0.1041
POS 300 K L T L N A K S I R
0.1698 0.1041 0.0660 0.0441 0.0405 0.0701 0.1602 0.2333 0.2865 0.3456
POS 310 C C L H
0.4037 0.4556 0.5802 0.6334
Structured Regions
IUPRED predicts one structured region comprised of the whole input sequence.
Results
IUPRED predicts no significant disorder in Aspartoacyclase. The disorder tendency stays below 0.5 in all cases (except for short stretches of about 3-5 residues at each end of the sequence in short disorder mode, which are negligible) and the structured regions mode predicts one continuous structured region spanning all of the protein sequence. This makes sense when looking at the 3D structure: Aspartoacyclase is a rather densely packed globular structure, which according to the assumptions that IUPRED makes has a strong tendency to form many inter-residue contacts and to stabilize itself thereby, markedly reducing the tendency for disorder in the process.
Meta-Disorder
Meta-Disorder, as the name implies, employs a set of so-called orthogonal disorder predictors in order to combine their strengths and mitigate their weak points. It was published in 2009 by Avner Schlessinger, Marco Punta, Guy Yachdav, Laszlo Kajan and Burkhard Rost.
Reference: Paper
As with the previous methods, Meta-Disorder predicts disorder from the amino acid sequence alone; results from the predictors IUPRED, DISOPRED, NORSnet and Ucon are molded into one final result using a neural network.
Results for Aspartoacyclase:
Number Residue NORSnet NORS2st PROFbval bval2st Ucon Ucon2st MD_raw MD_rel MD2st
1 M 0.33 - 0.99 D 0.17 - 0.551 1 D
2 T 0.26 - 0.78 D 0.25 - 0.531 0 D
3 S 0.16 - 0.72 D 0.35 - 0.535 0 D
4 C 0.23 - 0.65 D 0.33 - 0.505 0 -
5 H 0.20 - 0.48 D 0.25 - 0.475 1 -
6 I 0.16 - 0.55 D 0.30 - 0.465 1 -
7 A 0.34 - 0.56 D 0.40 - 0.444 2 -
8 E 0.28 - 0.67 D 0.30 - 0.424 3 -
9 E 0.21 - 0.73 D 0.38 - 0.404 3 -
10 H 0.15 - 0.70 D 0.30 - 0.374 4 -
11 I 0.15 - 0.59 D 0.29 - 0.354 5 -
12 Q 0.15 - 0.60 D 0.28 - 0.313 6 -
13 K 0.14 - 0.51 D 0.23 - 0.263 8 -
14 V 0.14 - 0.30 - 0.19 - 0.253 8 -
15 A 0.16 - 0.24 - 0.19 - 0.250 9 -
16 I 0.13 - 0.20 - 0.24 - 0.242 9 -
17 F 0.10 - 0.13 - 0.23 - 0.250 9 -
18 G 0.13 - 0.18 - 0.21 - 0.242 9 -
19 G 0.10 - 0.24 - 0.20 - 0.253 8 -
20 T 0.07 - 0.34 - 0.20 - 0.253 8 -
21 H 0.06 - 0.26 - 0.26 - 0.260 8 -
22 G 0.06 - 0.39 - 0.29 - 0.253 8 -
23 N 0.06 - 0.48 D 0.22 - 0.250 9 -
24 E 0.06 - 0.47 D 0.18 - 0.242 9 -
25 L 0.11 - 0.43 - 0.16 - 0.242 9 -
26 T 0.12 - 0.39 - 0.20 - 0.253 8 -
27 G 0.10 - 0.32 - 0.20 - 0.242 9 -
28 V 0.08 - 0.28 - 0.15 - 0.242 9 -
29 F 0.12 - 0.35 - 0.13 - 0.242 9 -
30 L 0.14 - 0.28 - 0.15 - 0.242 9 -
31 V 0.09 - 0.30 - 0.16 - 0.253 8 -
32 K 0.07 - 0.40 - 0.16 - 0.263 8 -
33 H 0.06 - 0.40 - 0.18 - 0.293 7 -
34 W 0.08 - 0.38 - 0.29 - 0.273 8 -
35 L 0.09 - 0.45 - 0.30 - 0.283 7 -
36 E 0.09 - 0.56 D 0.41 - 0.313 6 -
37 N 0.12 - 0.62 D 0.32 - 0.313 6 -
38 G 0.16 - 0.62 D 0.35 - 0.330 6 -
39 A 0.11 - 0.64 D 0.46 - 0.313 6 -
40 E 0.10 - 0.66 D 0.47 - 0.323 6 -
41 I 0.09 - 0.65 D 0.47 - 0.323 6 -
42 Q 0.10 - 0.64 D 0.36 - 0.293 7 -
43 R 0.09 - 0.61 D 0.50 - 0.273 8 -
44 T 0.08 - 0.61 D 0.56 - 0.273 8 -
45 G 0.08 - 0.53 D 0.34 - 0.263 8 -
46 L 0.09 - 0.43 - 0.35 - 0.260 8 -
47 E 0.10 - 0.33 - 0.32 - 0.253 8 -
48 V 0.07 - 0.23 - 0.32 - 0.250 9 -
49 K 0.06 - 0.17 - 0.34 - 0.253 8 -
50 P 0.08 - 0.18 - 0.37 - 0.263 8 -
51 F 0.08 - 0.17 - 0.49 - 0.273 8 -
52 I 0.07 - 0.21 - 0.33 - 0.273 8 -
53 T 0.06 - 0.28 - 0.53 - 0.303 7 -
54 N 0.07 - 0.28 - 0.53 - 0.303 7 -
55 P 0.09 - 0.36 - 0.37 - 0.313 6 -
56 R 0.08 - 0.41 - 0.51 - 0.313 6 -
57 A 0.10 - 0.40 - 0.66 D 0.280 7 -
58 V 0.13 - 0.40 - 0.51 - 0.263 8 -
59 K 0.16 - 0.48 D 0.37 - 0.263 8 -
60 K 0.19 - 0.47 D 0.40 - 0.263 8 -
61 C 0.18 - 0.47 D 0.29 - 0.253 8 -
62 T 0.16 - 0.55 D 0.35 - 0.263 8 -
63 R 0.18 - 0.51 D 0.31 - 0.253 8 -
64 Y 0.22 - 0.47 D 0.25 - 0.273 8 -
65 I 0.23 - 0.47 D 0.20 - 0.260 8 -
66 D 0.23 - 0.56 D 0.21 - 0.263 8 -
67 C 0.25 - 0.57 D 0.16 - 0.263 8 -
68 D 0.30 - 0.43 - 0.18 - 0.263 8 -
69 L 0.29 - 0.40 - 0.18 - 0.260 8 -
70 N 0.28 - 0.40 - 0.25 - 0.263 8 -
71 R 0.40 - 0.39 - 0.23 - 0.273 8 -
72 I 0.46 - 0.43 - 0.22 - 0.280 7 -
73 F 0.46 - 0.37 - 0.19 - 0.273 8 -
74 D 0.37 - 0.46 - 0.32 - 0.310 6 -
75 L 0.33 - 0.57 D 0.40 - 0.390 4 -
76 E 0.36 - 0.61 D 0.30 - 0.444 2 -
77 N 0.44 - 0.62 D 0.41 - 0.465 1 -
78 L 0.38 - 0.66 D 0.65 D 0.531 0 D
79 G 0.30 - 0.70 D 0.64 D 0.485 1 -
80 K 0.35 - 0.69 D 0.64 D 0.515 0 -
81 K 0.23 - 0.69 D 0.59 D 0.475 1 -
82 M 0.23 - 0.66 D 0.42 - 0.444 2 -
83 S 0.28 - 0.69 D 0.64 D 0.449 2 -
84 E 0.34 - 0.72 D 0.56 - 0.485 1 -
85 D 0.29 - 0.74 D 0.45 - 0.424 3 -
86 L 0.20 - 0.64 D 0.35 - 0.424 3 -
87 P 0.20 - 0.64 D 0.45 - 0.404 3 -
88 Y 0.17 - 0.55 D 0.46 - 0.384 4 -
89 E 0.14 - 0.50 D 0.46 - 0.364 5 -
90 V 0.13 - 0.45 - 0.30 - 0.333 6 -
91 R 0.12 - 0.43 - 0.43 - 0.320 6 -
92 R 0.11 - 0.40 - 0.36 - 0.293 7 -
93 A 0.11 - 0.34 - 0.36 - 0.283 7 -
94 Q 0.10 - 0.45 - 0.22 - 0.290 7 -
95 E 0.12 - 0.41 - 0.25 - 0.303 7 -
96 I 0.09 - 0.34 - 0.26 - 0.283 7 -
97 N 0.11 - 0.40 - 0.33 - 0.313 6 -
98 H 0.10 - 0.49 D 0.39 - 0.313 6 -
99 L 0.10 - 0.47 D 0.38 - 0.313 6 -
100 F 0.13 - 0.47 D 0.38 - 0.293 7 -
101 G 0.14 - 0.54 D 0.58 D 0.323 6 -
102 P 0.13 - 0.61 D 0.58 D 0.333 6 -
103 K 0.13 - 0.60 D 0.47 - 0.323 6 -
104 D 0.11 - 0.61 D 0.71 D 0.323 6 -
105 S 0.10 - 0.65 D 0.73 D 0.283 7 -
106 E 0.10 - 0.70 D 0.62 D 0.283 7 -
107 D 0.12 - 0.70 D 0.42 - 0.273 8 -
108 S 0.11 - 0.64 D 0.37 - 0.270 8 -
109 Y 0.12 - 0.50 D 0.23 - 0.253 8 -
110 D 0.13 - 0.39 - 0.20 - 0.242 9 -
111 I 0.16 - 0.29 - 0.18 - 0.240 9 -
112 I 0.15 - 0.20 - 0.16 - 0.240 9 -
113 F 0.14 - 0.20 - 0.16 - 0.240 9 -
114 D 0.17 - 0.21 - 0.20 - 0.242 9 -
115 L 0.21 - 0.20 - 0.19 - 0.253 8 -
116 H 0.17 - 0.28 - 0.19 - 0.273 8 -
117 N 0.11 - 0.48 D 0.23 - 0.283 7 -
118 T 0.13 - 0.39 - 0.24 - 0.283 7 -
119 T 0.13 - 0.41 - 0.21 - 0.273 8 -
120 S 0.15 - 0.46 - 0.21 - 0.273 8 -
121 N 0.22 - 0.54 D 0.18 - 0.263 8 -
122 M 0.25 - 0.51 D 0.14 - 0.260 8 -
123 G 0.30 - 0.51 D 0.16 - 0.253 8 -
124 C 0.26 - 0.42 - 0.18 - 0.250 9 -
125 T 0.29 - 0.40 - 0.18 - 0.242 9 -
126 L 0.24 - 0.34 - 0.18 - 0.253 8 -
127 I 0.17 - 0.28 - 0.23 - 0.260 8 -
128 L 0.13 - 0.28 - 0.25 - 0.263 8 -
129 E 0.14 - 0.41 - 0.24 - 0.253 8 -
130 D 0.14 - 0.54 D 0.18 - 0.253 8 -
131 S 0.10 - 0.59 D 0.19 - 0.273 8 -
132 R 0.07 - 0.68 D 0.27 - 0.280 7 -
133 N 0.05 - 0.64 D 0.28 - 0.273 8 -
134 N 0.06 - 0.61 D 0.18 - 0.273 8 -
135 F 0.07 - 0.53 D 0.15 - 0.260 8 -
136 L 0.08 - 0.47 D 0.13 - 0.242 9 -
137 I 0.10 - 0.47 D 0.13 - 0.242 9 -
138 Q 0.16 - 0.42 - 0.13 - 0.242 9 -
139 M 0.15 - 0.34 - 0.13 - 0.242 9 -
140 F 0.11 - 0.32 - 0.14 - 0.250 9 -
141 H 0.13 - 0.41 - 0.14 - 0.263 8 -
142 Y 0.16 - 0.36 - 0.16 - 0.263 8 -
143 I 0.12 - 0.34 - 0.16 - 0.263 8 -
144 K 0.11 - 0.46 - 0.15 - 0.283 7 -
145 T 0.07 - 0.54 D 0.20 - 0.273 8 -
146 S 0.07 - 0.55 D 0.17 - 0.253 8 -
147 L 0.09 - 0.56 D 0.17 - 0.242 9 -
148 A 0.10 - 0.57 D 0.17 - 0.250 9 -
149 P 0.09 - 0.60 D 0.13 - 0.253 8 -
150 L 0.11 - 0.51 D 0.13 - 0.242 9 -
151 P 0.13 - 0.44 - 0.14 - 0.242 9 -
152 C 0.12 - 0.38 - 0.13 - 0.240 9 -
153 Y 0.13 - 0.31 - 0.13 - 0.240 9 -
154 V 0.18 - 0.28 - 0.13 - 0.242 9 -
155 Y 0.17 - 0.33 - 0.14 - 0.250 9 -
156 L 0.21 - 0.47 D 0.13 - 0.253 8 -
157 I 0.22 - 0.54 D 0.15 - 0.263 8 -
158 E 0.17 - 0.58 D 0.15 - 0.283 7 -
159 H 0.16 - 0.62 D 0.17 - 0.303 7 -
160 P 0.13 - 0.65 D 0.21 - 0.323 6 -
161 S 0.14 - 0.59 D 0.29 - 0.303 7 -
162 L 0.17 - 0.58 D 0.41 - 0.303 7 -
163 K 0.21 - 0.56 D 0.36 - 0.293 7 -
164 Y 0.32 - 0.51 D 0.29 - 0.273 8 -
165 A 0.31 - 0.47 D 0.26 - 0.273 8 -
166 T 0.28 - 0.45 - 0.32 - 0.273 8 -
167 T 0.22 - 0.41 - 0.33 - 0.273 8 -
168 R 0.15 - 0.47 D 0.26 - 0.273 8 -
169 S 0.14 - 0.47 D 0.28 - 0.280 7 -
170 I 0.12 - 0.46 - 0.29 - 0.273 8 -
171 A 0.12 - 0.47 D 0.22 - 0.283 7 -
172 K 0.11 - 0.58 D 0.27 - 0.290 7 -
173 Y 0.13 - 0.47 D 0.20 - 0.263 8 -
174 P 0.11 - 0.38 - 0.19 - 0.253 8 -
175 V 0.10 - 0.26 - 0.26 - 0.250 9 -
176 G 0.09 - 0.24 - 0.31 - 0.250 9 -
177 I 0.13 - 0.33 - 0.25 - 0.250 9 -
178 E 0.20 - 0.28 - 0.37 - 0.253 8 -
179 V 0.26 - 0.41 - 0.33 - 0.253 8 -
180 G 0.20 - 0.45 - 0.33 - 0.270 8 -
181 P 0.17 - 0.59 D 0.25 - 0.283 7 -
182 Q 0.12 - 0.49 D 0.35 - 0.283 7 -
183 P 0.12 - 0.51 D 0.28 - 0.273 8 -
184 Q 0.13 - 0.54 D 0.42 - 0.273 8 -
185 G 0.10 - 0.51 D 0.33 - 0.263 8 -
186 V 0.12 - 0.55 D 0.22 - 0.253 8 -
187 L 0.17 - 0.54 D 0.24 - 0.253 8 -
188 R 0.14 - 0.48 D 0.24 - 0.263 8 -
189 A 0.11 - 0.53 D 0.18 - 0.273 8 -
190 D 0.11 - 0.51 D 0.19 - 0.273 8 -
191 I 0.08 - 0.41 - 0.31 - 0.283 7 -
192 L 0.07 - 0.42 - 0.33 - 0.263 8 -
193 D 0.06 - 0.47 D 0.24 - 0.273 8 -
194 Q 0.08 - 0.45 - 0.33 - 0.270 8 -
195 M 0.04 - 0.34 - 0.26 - 0.263 8 -
196 R 0.04 - 0.43 - 0.34 - 0.273 8 -
197 K 0.05 - 0.44 - 0.34 - 0.263 8 -
198 M 0.06 - 0.29 - 0.34 - 0.263 8 -
199 I 0.06 - 0.28 - 0.22 - 0.253 8 -
200 K 0.07 - 0.34 - 0.22 - 0.263 8 -
201 H 0.07 - 0.32 - 0.20 - 0.253 8 -
202 A 0.08 - 0.28 - 0.15 - 0.250 9 -
203 L 0.08 - 0.35 - 0.15 - 0.253 8 -
204 D 0.09 - 0.43 - 0.19 - 0.263 8 -
205 F 0.11 - 0.41 - 0.18 - 0.263 8 -
206 I 0.12 - 0.45 - 0.18 - 0.253 8 -
207 H 0.15 - 0.59 D 0.23 - 0.270 8 -
208 H 0.18 - 0.59 D 0.40 - 0.290 7 -
209 F 0.22 - 0.58 D 0.24 - 0.283 7 -
210 N 0.27 - 0.63 D 0.37 - 0.293 7 -
211 E 0.27 - 0.66 D 0.53 - 0.313 6 -
212 G 0.28 - 0.68 D 0.44 - 0.313 6 -
213 K 0.26 - 0.70 D 0.46 - 0.323 6 -
214 E 0.26 - 0.71 D 0.50 - 0.323 6 -
215 F 0.20 - 0.70 D 0.56 - 0.303 7 -
216 P 0.21 - 0.69 D 0.37 - 0.293 7 -
217 P 0.24 - 0.69 D 0.28 - 0.280 7 -
218 C 0.14 - 0.66 D 0.28 - 0.263 8 -
219 A 0.14 - 0.58 D 0.19 - 0.263 8 -
220 I 0.15 - 0.52 D 0.19 - 0.263 8 -
221 E 0.11 - 0.47 D 0.22 - 0.270 8 -
222 V 0.11 - 0.34 - 0.26 - 0.273 8 -
223 Y 0.12 - 0.30 - 0.28 - 0.280 7 -
224 K 0.08 - 0.37 - 0.34 - 0.280 7 -
225 I 0.09 - 0.32 - 0.33 - 0.273 8 -
226 I 0.07 - 0.35 - 0.29 - 0.283 7 -
227 E 0.09 - 0.43 - 0.38 - 0.313 6 -
228 K 0.09 - 0.49 D 0.61 D 0.333 6 -
229 V 0.12 - 0.49 D 0.58 D 0.337 6 -
230 D 0.16 - 0.53 D 0.75 D 0.354 5 -
231 Y 0.14 - 0.52 D 0.84 D 0.343 5 -
232 P 0.12 - 0.57 D 0.84 D 0.313 6 -
233 R 0.13 - 0.66 D 0.59 D 0.303 7 -
234 D 0.15 - 0.69 D 0.70 D 0.310 6 -
235 E 0.10 - 0.71 D 0.59 D 0.293 7 -
236 N 0.12 - 0.71 D 0.62 D 0.303 7 -
237 G 0.17 - 0.67 D 0.44 - 0.293 7 -
238 E 0.22 - 0.60 D 0.40 - 0.283 7 -
239 I 0.17 - 0.53 D 0.36 - 0.270 8 -
240 A 0.16 - 0.38 - 0.30 - 0.260 8 -
241 A 0.19 - 0.29 - 0.22 - 0.253 8 -
242 I 0.16 - 0.28 - 0.24 - 0.263 8 -
243 I 0.22 - 0.33 - 0.24 - 0.263 8 -
244 H 0.25 - 0.34 - 0.34 - 0.293 7 -
245 P 0.14 - 0.48 D 0.41 - 0.323 6 -
246 N 0.16 - 0.53 D 0.30 - 0.343 5 -
247 L 0.16 - 0.58 D 0.53 - 0.343 5 -
248 Q 0.16 - 0.61 D 0.71 D 0.374 4 -
249 D 0.22 - 0.64 D 0.59 D 0.354 5 -
250 Q 0.30 - 0.64 D 0.51 - 0.364 5 -
251 D 0.34 - 0.62 D 0.52 - 0.333 6 -
252 W 0.33 - 0.52 D 0.65 D 0.313 6 -
253 K 0.22 - 0.58 D 0.68 D 0.283 7 -
254 P 0.21 - 0.58 D 0.63 D 0.283 7 -
255 L 0.18 - 0.54 D 0.45 - 0.263 8 -
256 H 0.16 - 0.68 D 0.27 - 0.263 8 -
257 P 0.18 - 0.69 D 0.28 - 0.273 8 -
258 G 0.19 - 0.57 D 0.21 - 0.270 8 -
259 D 0.28 - 0.54 D 0.16 - 0.290 7 -
260 P 0.25 - 0.54 D 0.23 - 0.270 8 -
261 M 0.19 - 0.40 - 0.24 - 0.273 8 -
262 F 0.16 - 0.34 - 0.29 - 0.253 8 -
263 L 0.13 - 0.37 - 0.30 - 0.253 8 -
264 T 0.10 - 0.46 - 0.20 - 0.242 9 -
265 L 0.14 - 0.56 D 0.20 - 0.253 8 -
266 D 0.13 - 0.61 D 0.20 - 0.263 8 -
267 G 0.11 - 0.62 D 0.26 - 0.280 7 -
268 K 0.10 - 0.60 D 0.34 - 0.283 7 -
269 T 0.10 - 0.60 D 0.40 - 0.273 8 -
270 I 0.08 - 0.46 - 0.41 - 0.250 9 -
271 P 0.07 - 0.43 - 0.35 - 0.250 9 -
272 L 0.12 - 0.46 - 0.29 - 0.242 9 -
273 G 0.10 - 0.53 D 0.18 - 0.242 9 -
274 G 0.08 - 0.52 D 0.19 - 0.250 9 -
275 D 0.05 - 0.62 D 0.19 - 0.253 8 -
276 C 0.06 - 0.68 D 0.15 - 0.263 8 -
277 T 0.10 - 0.59 D 0.16 - 0.263 8 -
278 V 0.08 - 0.52 D 0.17 - 0.263 8 -
279 Y 0.09 - 0.33 - 0.20 - 0.242 9 -
280 P 0.10 - 0.27 - 0.17 - 0.242 9 -
281 V 0.12 - 0.23 - 0.21 - 0.242 9 -
282 F 0.12 - 0.18 - 0.17 - 0.253 8 -
283 V 0.09 - 0.24 - 0.16 - 0.263 8 -
284 N 0.05 - 0.28 - 0.23 - 0.303 7 -
285 E 0.06 - 0.39 - 0.28 - 0.384 4 -
286 A 0.09 - 0.35 - 0.46 - 0.404 3 -
287 A 0.08 - 0.43 - 0.72 D 0.418 3 -
288 Y 0.08 - 0.37 - 0.79 D 0.374 4 -
289 Y 0.09 - 0.55 D 0.61 D 0.354 5 -
290 E 0.10 - 0.41 - 0.49 - 0.333 6 -
291 K 0.10 - 0.50 D 0.65 D 0.323 6 -
292 K 0.07 - 0.47 D 0.66 D 0.323 6 -
293 E 0.07 - 0.36 - 0.79 D 0.333 6 -
294 A 0.06 - 0.29 - 0.95 D 0.354 5 -
295 F 0.08 - 0.27 - 0.82 D 0.333 6 -
296 A 0.09 - 0.32 - 0.70 D 0.323 6 -
297 K 0.09 - 0.42 - 0.41 - 0.343 5 -
298 T 0.08 - 0.42 - 0.36 - 0.343 5 -
299 T 0.10 - 0.51 D 0.36 - 0.414 3 -
300 K 0.09 - 0.54 D 0.64 D 0.455 2 -
301 L 0.09 - 0.48 D 0.70 D 0.394 4 -
302 T 0.15 - 0.55 D 0.43 - 0.404 3 -
303 L 0.15 - 0.48 D 0.46 - 0.374 4 -
304 N 0.12 - 0.48 D 0.34 - 0.374 4 -
305 A 0.13 - 0.47 D 0.19 - 0.374 4 -
306 K 0.22 - 0.55 D 0.19 - 0.384 4 -
307 S 0.07 - 0.53 D 0.18 - 0.434 2 -
308 I 0.07 - 0.41 - 0.23 - 0.424 3 -
309 R 0.07 - 0.37 - 0.21 - 0.414 3 -
310 C 0.11 - 0.60 D 0.19 - 0.414 3 -
311 C 0.14 - 0.67 D 0.14 - 0.394 4 -
312 L 0.15 - 0.72 D 0.13 - 0.424 3 -
313 H 0.44 - 0.80 D 0.13 - 0.485 1 -
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
The last column indicates whether or not disorder was predicted at the current position. Meta-Disorder predicts a total of four disorder positions, which are not significant. This coincides with the predictions of the other programs employed previously - not alltogether surprising, since Meta-Disorder draws its predictions from two of them.
Prediction of transmembrane alpha-helices and signal peptides
The results of this task are unequivocal: Aspartoacyclase does not contain any transmembrane regions. From a biological point of view this was to be expected, as Aspartoacyclase is known to be located in the cytosol.
TMHMM
Since the VM version could not be made to work, we used the server at http://www.cbs.dtu.dk/services/TMHMM/.
TMHMM uses a hidden markov model to predict transmembrane helices in proteins. It was published in 1998 by E. L.L. Sonnhammer, G. von Heijne, and A. Krogh.
Reference: Original paper
The hidden markov model used by TMHMM models the biological structure with states for helix turns, helix caps and loops on either side of the membrane, which are specially designed to model membrane insertion, too. The HMM probabilities were estimated both by using a maximum likelihood method and a discriminative method.
Results for Aspartoacyclase very clearly show absence of any sort of transmembrane structure, which is biologically sound.
# sp_P45381_ACY2_HUMAN Length: 313 # sp_P45381_ACY2_HUMAN Number of predicted TMHs: 0 # sp_P45381_ACY2_HUMAN Exp number of AAs in TMHs: 0.2005 # sp_P45381_ACY2_HUMAN Exp number, first 60 AAs: 0.01618 # sp_P45381_ACY2_HUMAN Total prob of N-in: 0.03827 sp_P45381_ACY2_HUMAN TMHMM2.0 outside 1 313
http://www.cbs.dtu.dk/services/TMHMM-2.0/TMHMM2.0.guide.html#output
Phobius & PolyPhobius
Phobius is a program for the prediction of transmembrane region with special emphasis on reducing confusion with signal peptides. It was published in 2005 by Käll L, Krogh A, Sonnhammer EL.
Reference: Paper
Signal peptides and transmembrane proteins share a great deal of similarity and are often confused by predictors for either class; Phobius aims to predict both and to discriminate between them. It employs a hidden markov model to do this, modelling the different sequence regions pertaining to either class.
Again, neither signal nor transmembrane regions were detected in Aspartoacyclase.
OCTOPUS & SPOCTOPUS
No transmembrane regions were predicted by both methods.
SignalP
HMM
Neural Network
TargetP
### targetp v1.1 prediction results ################################## Number of query sequences: 1 Cleavage site predictions not included. Using NON-PLANT networks. Name Len mTP SP other Loc RC ---------------------------------------------------------------------- sp_P45381_ACY2_HUMAN 313 0.073 0.109 0.898 _ 2 ---------------------------------------------------------------------- cutoff 0.000 0.000 0.000
http://www.cbs.dtu.dk/services/TargetP-1.1/output.php
Prediction of GO terms
GOPET
| GOid | Aspect | Confidence | GO Term |
|---|---|---|---|
| GO:0016787 | F | 96% | hydrolase activity |
| GO:0004046 | F | 82% | aminoacyclase activity |
| GO:0019807 | F | 82% | aspartoacyclase activity |
| GO:0016788 | F | 81% | hydrolase activity acting on ester bonds |
Pfam
ProtFun 2.2
############## ProtFun 2.2 predictions ############## >sp_P45381_A # Functional category Prob Odds Amino_acid_biosynthesis 0.071 3.233 Biosynthesis_of_cofactors 0.144 2.003 Cell_envelope 0.033 0.535 Cellular_processes 0.137 1.875 Central_intermediary_metabolism => 0.334 5.309 Energy_metabolism 0.226 2.511 Fatty_acid_metabolism 0.022 1.663 Purines_and_pyrimidines 0.367 1.512 Regulatory_functions 0.021 0.128 Replication_and_transcription 0.167 0.625 Translation 0.113 2.559 Transport_and_binding 0.017 0.042 # Enzyme/nonenzyme Prob Odds Enzyme => 0.703 2.454 Nonenzyme 0.297 0.416 # Enzyme class Prob Odds Oxidoreductase (EC 1.-.-.-) 0.111 0.534 Transferase (EC 2.-.-.-) 0.202 0.585 Hydrolase (EC 3.-.-.-) 0.115 0.363 Lyase (EC 4.-.-.-) 0.031 0.662 Isomerase (EC 5.-.-.-) => 0.084 2.637 Ligase (EC 6.-.-.-) 0.074 1.460 # Gene Ontology category Prob Odds Signal_transducer 0.053 0.246 Receptor 0.004 0.024 Hormone 0.001 0.206 Structural_protein 0.001 0.041 Transporter 0.025 0.230 Ion_channel 0.015 0.257 Voltage-gated_ion_channel 0.004 0.173 Cation_channel 0.011 0.234 Transcription 0.100 0.785 Transcription_regulation 0.039 0.313 Stress_response 0.010 0.117 Immune_response 0.061 0.720 Growth_factor 0.006 0.450 Metal_ion_transport 0.009 0.020
