Example of verbose text output from NORSp
The following information has been received by the server:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
________________________________________________________________________________
reference predict_h24157 (Mar 11, 2003 20:01:57)
reference pred_h24157 (Mar 11, 2003 19:59:16)
PPhdr from: liu@cubic.bioc.columbia.edu
PPhdr resp: MAIL
PPhdr orig: HTML
PPhdr want: ASCII
PPhdr password(###)
run nors_only
ret store
ret nors verbose
expert nors ws=70 seccut=12 acclen=10
# default: single protein sequence
MARAEEVDGP APGEVLLSPV DGLHNHVIHV ALQEHGWATY AVHPVEAQPA
PHPGALLHQV EVPAPLDRVD PYPLIALYHH PRLECPPYSL PNTLLSLPPP
HITRRYIEYY GYVTPQPLLI LYHLPLAQLH PTVLEYLVGP RVRHNNTREP
EDPVYTLLGR LPSKALPKEV GVCNNLAEPG GPNLIHTNLL PIHVYDRKEG
GRLHNTMLCI DPADPPRQID IPNLKHRPGP TRNPSRLPTL IAPESKPPFE
GWMSVGQEA
________________________________________________________________________________
Result of NORS prediction (Jinfeng Liu & Burkhard Rost)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Jinfeng Liu, Hepan Tan & Burkhard Rost
J. Mol. Biol. (2002) 322: 53-64
________________________________________________________________________________
Sequence length : 259
Secondary structure : Helix=9.7%, Strand=19.3%, Loop=71.0%
window size : 70
Structure content cutoff: 12%
Minimum consecutive exposed residues: 10
NORS : n=NORS region
Secondary structure : h=helix, e=strand, l=loop
Transmembrane helix : m=transmembrane helix
Solvent accessibility: e=exposed, b=buried
NORS region : 187-259
. : . : . : . : . 5
seq MARAEEVDGPAPGEVLLSPVDGLHNHVIHVALQEHGWATYAVHPVEAQPA
NORS ..................................................
SEC lllleellllllleeeeellllllleeeeeehhhllleeeeelleellll
COILS ..................................................
HTM ..................................................
ACC eeebeebeeebebebbbbebeebeebbbbbbbeeeebbbbbbbebebeeb
. : . : . : . : . 10
seq PHPGALLHQVEVPAPLDRVDPYPLIALYHHPRLECPPYSLPNTLLSLPPP
NORS ..................................................
SEC lllllleeeeelllllllllllleeeeellllllllllllllllllllll
COILS ..................................................
HTM ..................................................
ACC eeeebbbbebebebebeebeebbbbbbbbbeebebeebebeeebbebeee
. : . : . : . : . 15
seq HITRRYIEYYGYVTPQPLLILYHLPLAQLHPTVLEYLVGPRVRHNNTREP
NORS ..................................................
SEC lllhhhhhhhleellhhhhhhhlllhhhllllhhhhhlllllllllllll
COILS ..................................................
HTM ..................................................
ACC ebbeebbebbeebeebbbbbbbbbebbebbeebbeebbebebeeeeeeee
. : . : . : . : . 20
seq EDPVYTLLGRLPSKALPKEVGVCNNLAEPGGPNLIHTNLLPIHVYDRKEG
NORS ....................................nnnnnnnnnnnnnn
SEC llleeeeelllllllllllleellllllllllleeellllleeeeellll
COILS ..................................................
HTM ..................................................
ACC eeebbbbbeebeeeebeeebebbeebeeeeeeebbbbebbbbbbbeeeee
. : . : . : . : . 25
seq GRLHNTMLCIDPADPPRQIDIPNLKHRPGPTRNPSRLPTLIAPESKPPFE
NORS nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn
SEC lllllleeelllllllllllllllllllllllllllllllllllllllll
COILS ..................................................
HTM ..................................................
ACC eebbbbbbbbbeeeeeeebebeebeeeeeeeeeeeebeebbbeeeeeebe
. : . : . : . : . 30
seq GWMSVGQEA
NORS nnnnnnnnn
SEC lllllllll
COILS .........
HTM .........
ACC ebbeeeeee
//
________________________________________________________________________________
The resulting network (PROF) prediction is:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
________________________________________________________________________________
# #
# ==================================================================== #
# PROF predictions for predict_h24157 #
# ==================================================================== #
# #
# -------------------------------------------------------------------- #
# SYNOPSIS of prediction #
# -------------------------------------------------------------------- #
# #
# PROFsec summary #
# #
# overall your protein can be classified as: #
# #
# >>> mixed <<< #
# #
# given the following classes: #
# 'all-alpha': %H > 45% AND %E < 5% #
# 'all-beta': %H < 5% AND %E > 45% #
# 'alpha-beta': %H > 30% AND %E > 20% #
# 'mixed': all others #
# #
# Predicted secondary structure composition: #
# +-----------------+-------+-------+-------+ #
# | sec str type | H | E | L | #
# | % in protein | 9.7 | 19.3 | 71.0 | #
# +-----------------+-------+-------+-------+ #
# #
# #
# Predicted solvent accessibility composition (core/surface ratio): #
# Classes used: #
# e: residues exposed with more than 16% of their surface #
# b: all other residues. #
# +--------------+-------+-------+ #
# | acc type | b | e | #
# | % in protein | 46.0 | 54.0 | #
# +--------------+-------+-------+ #
# #
# -------------------------------------------------------------------- #
# HEADER information #
# -------------------------------------------------------------------- #
# #
# ................... #
# About your protein: #
# ................... #
# #
# prot_id : query #
# prot_nres : 259 #
# prot_nali : 1 #
# prot_nchn : 1 #
# prot_nfar : 0 #
# #
# ......................... #
# About the alignment used: #
# ......................... #
# #
# ali_orig : /home/phd/server/work/predict_h24157.hsspPsiFil #
# #
# ..................................... #
# Residue composition for your protein: #
# ..................................... #
# #
# +-----------------+-------+-------+-------+-------+-------+ #
# | amino acid type | A | C | D | E | F | #
# | % in protein | 6.6 | 1.2 | 3.5 | 6.6 | 0.4 | #
# +-----------------+-------+-------+-------+-------+-------+ #
# | amino acid type | G | H | I | K | L | #
# | % in protein | 6.2 | 6.6 | 4.2 | 1.9 | 13.5 | #
# +-----------------+-------+-------+-------+-------+-------+ #
# | amino acid type | M | N | P | Q | R | #
# | % in protein | 1.2 | 4.2 | 15.8 | 2.7 | 5.8 | #
# +-----------------+-------+-------+-------+-------+-------+ #
# | amino acid type | S | T | V | W | Y | #
# | % in protein | 2.7 | 4.2 | 7.3 | 0.8 | 4.6 | #
# +-----------------+-------+-------+-------+-------+-------+ #
# #
# ............................. #
# About the PROF methods used: #
# ............................. #
# #
# prof_fpar : acc=/home/phd/server/pub/prof/net/PROFboth_best.par #
# prof_nnet : acc=6 #
# #
# .................... #
# Copyright & Contact: #
# .................... #
# #
# -> Copyright:Burkhard Rost, CUBIC NYC / LION Heidelberg #
# -> Email: rost@columbia.edu #
# -> WWW: http://cubic.bioc.columbia.edu #
# -> Fax: +1-212-305 3773 #
# #
# ............. #
# Please quote: #
# ............. #
# #
# -> PROF: B Rost (1996) Methods in Enzymology, 266:525-539 #
# -> PROFsec: B Rost & C Sander (1993) J Mol Biol, 232:584-599 #
# -> PROFacc: B Rost & C Sander (1994) Proteins, 20:216-226 #
# #
# #
# -------------------------------------------------------------------- #
# ABBREVIATIONS used: #
# -------------------------------------------------------------------- #
# #
# AA : amino acid sequence #
# OBS_sec : observed secondary structure: H=helix, E=extended #
# (sheet), blank=other (loop) #
# PROF_sec : PROF predicted secondary structure: H=helix, E=extended #
# (sheet), blank=other (loop) #
# PROF = PROF: Profile network prediction HeiDelberg #
# Rel_sec : reliability index for PROFsec prediction (0=low #
# to 9=high) #
# Note: for the brief presentation strong predictions #
# marked by '*' #
# SUB_sec : subset of the PROFsec prediction, for all residues #
# with an expected average accuracy > 82% (tables #
# in header) #
# NOTE: for this subset the following symbols are used: #
# L: is loop (for which above ' ' is used) #
# .: means that no prediction is made for this #
# residue, as the reliability is: Rel < 5 #
# pH_sec : 'probability' for assigning helix (1=high, 0=low) #
# pE_sec : 'probability' for assigning strand (1=high, 0=low) #
# pL_sec : 'probability' for assigning neither helix, nor #
# strand (1=high, 0=low) #
# O_2_acc : observerd relative solvent accessibility (acc) #
# in 2 states: b = 0-16%, e = 16-100%. #
# P_2_acc : PROF predicted relative solvent accessibility #
# (acc) in 2 states: b = 0-16%, e = 16-100%. #
# O_3_acc : observerd relative solvent accessibility (acc) #
# in 3 states: b = 0-9%, i = 9-36%, e = 36-100%. #
# P_3_acc : PROF predicted relative solvent accessibility #
# (acc) in 3 states: b = 0-9%, i = 9-36%, e = 36-100%. #
# OBS_acc : observed relative solvent accessibility (acc) #
# in 10 states: a value of n (=0-9) corresponds #
# to a relative acc. of between n*n % and (n+1)*(n+1) #
# % (e.g. for n=5: 16-25%). #
# PROF_acc : PROF predicted relative solvent accessibility #
# (acc) in 10 states: a value of n (=0-9) corresponds #
# to a relative acc. of between n*n % and (n+1)*(n+1) #
# % (e.g. for n=5: 16-25%). #
# Rel_acc : reliability index for PROFacc prediction (0=low #
# to 9=high) #
# Note: for the brief presentation strong predictions #
# marked by '*' #
# SUB_acc : subset of the PROFacc prediction, for all residues #
# with an expected average correlation > 0.69 (tables #
# in header) #
# NOTE: for this subset the following symbols are used: #
# I: is intermediate (for which above ' ' is used) #
# .: means that no prediction is made for this #
# residue, as the reliability is: Rel < 4 #
# #
# prot_id : identifier of protein [w] #
# prot_nres : number of residues [d] #
# prot_nali : number of proteins aligned in family [d] #
# prot_nchn : number of chains (if PDB protein) [d] #
# prot_nfar : number of distant relatives [d] #
# ali_orig : input file #
# prof_fpar : name of parameter file, used [w] #
# prof_nnet : number of networks used for prediction [d] #
# prof_skip : note: sequence stretches with less than 9 are #
# not predicted, the symbol '*' is used! #
# #
# ==================================================================== #
# PROF_BODY with predictions for predict_h24157 #
# ==================================================================== #
# #
# ---------------------
# PROF results (normal)
# ---------------------
#
....,....1....,....2....,....3....,....4....,....5....,....6
AA |MARAEEVDGPAPGEVLLSPVDGLHNHVIHVALQEHGWATYAVHPVEAQPAPHPGALLHQV|
OBS_sec | |
PROF_sec | EE EEEEE EEEEEEHHH EEEEE EE EEEE|
Rel_sec |940020357776236751223345403443202158436745020213577866200122|
subset: SUB_sec |L......LLLLL..EEE......L..........LL..EE.E......LLLLLL......|
3st: O_3_acc |bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb|
P_3_acc |eeebeeieeeieiebbbbiieebiibbbbbbbieiebbbbbbbeiebieieieebbbbib|
Rel_acc |625023342124120153103202135927772232233152120302212112000122|
subset: SUB_acc |e.e....e...e....b.........bb.bbb........b...................|
....,....7....,....8....,....9....,....10.1.,....11.1.,....12.1
AA |EVPAPLDRVDPYPLIALYHHPRLECPPYSLPNTLLSLPPPHITRRYIEYYGYVTPQPLLI|
OBS_sec | |
PROF_sec |E EEEEE HHHHHHH EE HHHHH|
Rel_sec |313655675762004431143221356556530025676200044455305106215655|
subset: SUB_sec |...LLLLLLLL..............LLLLLL....LLLL.......HH..L..L..HHHH|
3st: O_3_acc |bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb|
P_3_acc |eieieieeiieibbbbbbbieibebieieieiibbeieieibbiibbeiiiibiiibbbb|
Rel_acc |412132331201035770010323323412201012210021223542110202102346|
subset: SUB_acc |e.............bbb..........i.................bb...........bb|
....,....13.1.,....14.1.,....15.1.,....16.1.,....17.1.,....18.1
AA |LYHLPLAQLHPTVLEYLVGPRVRHNNTREPEDPVYTLLGRLPSKALPKEVGVCNNLAEPG|
OBS_sec | |
PROF_sec |HH HHH HHHHH EEEEE EE |
Rel_sec |523651103711221101873003567677673254412457533772020102345666|
subset: SUB_sec |H..LL....L........LL....LLLLLLLL..E.....LLL..LL.........LLLL|
3st: O_3_acc |bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb|
P_3_acc |bbbbebbeiieebbeibbiiebiieieeeeeiibbbbbiibeeeeieeeiibbeibieee|
Rel_acc |411220120122532310111022310111411313220323133304421001100034|
subset: SUB_acc |b...........b.................e................ee..........e|
....,....19.1.,....20.1.,....21.1.,....22.1.,....23.1.,....24.1
AA |GPNLIHTNLLPIHVYDRKEGGRLHNTMLCIDPADPPRQIDIPNLKHRPGPTRNPSRLPTL|
OBS_sec | |
PROF_sec | EEE EEEEE EEE |
Rel_sec |663142143434666121476201112100566660013363223355666574546641|
subset: SUB_sec |LL..........EEE....LL.........LLLLL.....L.....LLLLLLL.L.LL..|
3st: O_3_acc |bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb|
P_3_acc |iiibbbbibbbbbbbiieeeiibbbbbbbbieeeieieiebeebeeieiieiiieebiei|
Rel_acc |101220101135070033621212012334102222212312223032103010122001|
subset: SUB_acc |...........b.b....e..........b..............................|
....,....25.1.,....26.1
AA |IAPESKPPFEGWMSVGQEA|
OBS_sec | |
PROF_sec | |
Rel_sec |1675567622222434358|
subset: SUB_sec |.LLLLLLL.........LL|
3st: O_3_acc |bbbbbbbbbbbbbbbbbbb|
P_3_acc |iieeeeieieeiieieeee|
Rel_acc |0015221113122211188|
subset: SUB_acc |...e.............ee|
# --------------------------------------------------------------------
________________________________________________________________________________
The resulting network (PHD) prediction is:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
________________________________________________________________________________
PHD: Profile fed neural network systems from HeiDelberg
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Prediction of:
secondary structure, by PHDsec
solvent accessibility, by PHDacc
and helical transmembrane regions, by PHDhtm
Author:
Burkhard Rost
EMBL, 69012 Heidelberg, Germany
Internet: Rost@EMBL-Heidelberg.DE
All rights reserved.
The network systems are described in:
PHDsec: B Rost & C Sander: JMB, 1993, 232, 584-599.
B Rost & C Sander: Proteins, 1994, 19, 55-72.
PHDacc: B Rost & C Sander: Proteins, 1994, 20, 216-226.
PHDhtm: B Rost et al.: Prot. Science, 1995, 4, 521-533.
Some statistics
~~~~~~~~~~~~~~~
Percentage of amino acids:
+--------------+--------+--------+--------+--------+--------+
| AA: | P | L | V | H | E |
| % of AA: | 15.8 | 13.5 | 7.3 | 6.6 | 6.6 |
+--------------+--------+--------+--------+--------+--------+
| AA: | A | G | R | Y | T |
| % of AA: | 6.6 | 6.2 | 5.8 | 4.6 | 4.2 |
+--------------+--------+--------+--------+--------+--------+
| AA: | N | I | D | S | Q |
| % of AA: | 4.2 | 4.2 | 3.5 | 2.7 | 2.7 |
+--------------+--------+--------+--------+--------+--------+
| AA: | K | M | C | W | F |
| % of AA: | 1.9 | 1.2 | 1.2 | 0.8 | 0.4 |
+--------------+--------+--------+--------+--------+--------+
Percentage of helical trans-membrane predicted:
+--------------+--------+--------+
| SecStr: | H | L |
| % Predicted: | 3.5 | 96.5 |
+--------------+--------+--------+
PHD output for your protein
~~~~~~~~~~~~~~~~~~~~~~~~~~~
Tue Mar 11 20:05:35 2003
Jury on: 4 different architectures (version 8.94_69 ).
Note: differently trained architectures, i.e., different versions can
result in different predictions.
About the protein
~~~~~~~~~~~~~~~~~
HEADER
COMPND
SOURCE
AUTHOR
SEQLENGTH 259
NCHAIN 1 chain(s) in query data set
NALIGN 1
(=number of aligned sequences in HSSP file)
WARNING
~~~~~~~
Expected accuracy is about 94% if, and only if, the alignment contain
sufficient information. For your sequence there was no homologue in
the current version of Swissprot detected. This implies that the
expected accuracy is about 2-5 percentage points lower !
protein: query length 259
---
--- ------------------------------------------------------------
--- PhdTopology prediction of transmembrane helices and topology
--- ------------------------------------------------------------
---
--- PhdTopology REFINEMENT AND TOPOLOGY HEADER: ABBREVIATIONS
---
--- NHTM_BEST : number of transmembrane helices best model
--- NHTM_2ND_BEST: number of transmembrane helices 2nd best model
--- REL_BEST : reliability of best model (0 is low, 9 high)
--- HTMTOP_PRD : topology predicted ('in': intra-cytoplasmic)
--- HTMTOP_RID : difference between positive charges
--- HTMTOP_RIP : reliability of topology prediction (0-9)
--- MOD_NHTM : number of transmembrane helices of model
--- MOD_STOT : score for all residues
--- MOD_SHTM : score for HTM added at current iteration step
--- MOD_N-C : N - C term of HTM added at current step
---
--- ALGORITHM REF: The refinement is performed by a dynamic pro-
--- ALGORITHM : gramming-like procedure: iteratively the best
--- ALGORITHM : transmembrane helix (HTM) compatible with the
--- ALGORITHM : network output is added (starting from the 0
--- ALGORITHM : assumption, i.e., no HTM's in the protein).
--- ALGORITHM TOP: Topology is predicted by the positive-inside
--- ALGORITHM : rule, i.e., the positive charges are compiled
--- ALGORITHM : separately for all even and all odd non-HTM
--- ALGORITHM : regions. If the difference (charge even-odd)
--- ALGORITHM : is < 0, topology is predicted as 'in'. That
--- ALGORITHM : means, the protein N-term starts on the intra
--- ALGORITHM : cytoplasmic side.
---
--- PhdTopology REFINEMENT HEADER: SUMMARY
MOD_NHTM MOD_STOT MOD_SHTM MOD_N-C
1 0.957 0.000 0 - 0
---
--- PhdTopology REFINEMENT AND TOPOLOGY HEADER: SUMMARY
--- NHTM_BEST : 1
--- NHTM_2ND_BEST: 0
--- REL_BEST : 0
--- HTMTOP_PRD : unk
--- HTMTOP_RID : 0.000
--- HTMTOP_RIP : 0
---
--- PhdTopology REFINEMENT AND TOPOLOGY PREDICTION: SYMBOLS
--- AA : amino acid in one-letter code
--- PHD htm : HTM's predicted by the PHD neural network
--- system (H=HTM, ' '=not HTM)
--- Rel htm : Reliability index of prediction (0-9, 0 is low)
--- detail : Neural network output in detail
--- prH htm : 'Probability' for assigning a helical trans-
--- membrane region (HTM)
--- prL htm : 'Probability' for assigning a non-HTM region
--- note: 'Probabilites' are scaled to the interval
--- 0-9, e.g., prH=5 means, that the first
--- output node is 0.5-0.6
--- subset : Subset of more reliable predictions
--- SUB htm : All residues for which the expected average
--- accuracy is > 82% (tables in header).
--- note: for this subset the following symbols are used:
--- L: is loop (for which above ' ' is used)
--- '.': means that no prediction is made for this,
--- residue as the reliability is: Rel < 5
--- other : predictions derived based on PHDhtm
--- PHDFhtm : filtered prediction, i.e., too long HTM's are
--- split, too short ones are deleted
--- PHDRhtm : refinement of neural network output
--- PHDThtm : topology prediction based on refined model
--- symbols used:
--- i: intra-cytoplasmic
--- T: transmembrane region
--- o: extra-cytoplasmic
---
--- PhdTopology REFINEMENT AND TOPOLOGY PREDICTION
....,....1....,....2....,....3....,....4....,....5....,....6
AA |MARAEEVDGPAPGEVLLSPVDGLHNHVIHVALQEHGWATYAVHPVEAQPAPHPGALLHQV|
PHD htm | |
Rel htm |999999999999999999999999999999999999999999999999999999999999|
detail:
prH htm |000000000000000000000000000000000000000000000000000000000000|
prL htm |999999999999999999999999999999999999999999999999999999999999|
subset: SUB htm |LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL|
PHDRhtm | |
PHDThtm |i???????????????????????????????????????????????????????????|
....,....7....,....8....,....9....,....10...,....11...,....12
AA |EVPAPLDRVDPYPLIALYHHPRLECPPYSLPNTLLSLPPPHITRRYIEYYGYVTPQPLLI|
PHD htm | HH|
Rel htm |999999999999988999999999999999999999999999999999998788753101|
detail:
prH htm |000000000000000000000000000000000000000000000000000100123455|
prL htm |999999999999999999999999999999999999999999999999999899876544|
subset: SUB htm |LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL....|
PHDRhtm | |
PHDThtm |????????????????????????????????????????????????????????????|
....,....13...,....14...,....15...,....16...,....17...,....18
AA |LYHLPLAQLHPTVLEYLVGPRVRHNNTREPEDPVYTLLGRLPSKALPKEVGVCNNLAEPG|
PHD htm |HHHHH HH |
Rel htm |100100002456678899999999999999999999999999999999999999999999|
detail:
prH htm |555554553221110000000000000000000000000000000000000000000000|
prL htm |444445446778889999999999999999999999999999999999999999999999|
subset: SUB htm |.........LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL|
PHDRhtm | |
PHDThtm |????????????????????????????????????????????????????????????|
....,....19...,....20...,....21...,....22...,....23...,....24
AA |GPNLIHTNLLPIHVYDRKEGGRLHNTMLCIDPADPPRQIDIPNLKHRPGPTRNPSRLPTL|
PHD htm | |
Rel htm |999988899999999999999999999999999999999999999999999999999999|
detail:
prH htm |000000000000000000000000000000000000000000000000000000000000|
prL htm |999999999999999999999999999999999999999999999999999999999999|
subset: SUB htm |LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL|
PHDRhtm | |
PHDThtm |????????????????????????????????????????????????????????????|
....,....25...,....26...,....27...,....28...,....29...,....30
AA |IAPESKPPFEGWMSVGQEA|
PHD htm | |
Rel htm |9999999999999999999|
detail:
prH htm |0000000000000000000|
prL htm |9999999999999999999|
subset: SUB htm |LLLLLLLLLLLLLLLLLLL|
PHDRhtm | |
PHDThtm |???????????????????|
---
--- PhdTopology REFINEMENT AND TOPOLOGY PREDICTION END
---
________________________________________________________________________________
Result of COILS prediction (Andrei Lupas):
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
A Lupas: Methods in Enzymology, 1996, 266, 513-525.
version 2.2: Rob B. Russell & Andrei N. Lupas, 1999
________________________________________________________________________________
no coiled-coil above probability 0.5
________________________________________________________________________________
NORSp CUBIC Contact