prof - Online in the Cloud

PROGRAM:

NAME

prof - secondary structure and solvent accessibility predictor

SYNOPSIS

prof [INPUTFILE+] [OPTIONS]

DESCRIPTION

Secondary structure is predicted by a system of neural networks rating at an expected
average accuracy > 72% for the three states helix, strand and loop (Rost & Sander, PNAS,
1993 , 90, 7558-7562; Rost & Sander, JMB, 1993 , 232, 584-599; and Rost & Sander,
Proteins, 1994 , 19, 55-72; evaluation of accuracy). Evaluated on the same data set,
PROFsec is rated at ten percentage points higher three-state accuracy than methods using
only single sequence information, and at more than six percentage points higher than,
e.g., a method using alignment information based on statistics (Levin, Pascarella, Argos &
Garnier, Prot. Engng., 6, 849-54, 1993). PHDsec predictions have three main features:

1. improved accuracy through evolutionary information from multiple sequence alignments
2. improved beta-strand prediction through a balanced training procedure
3. more accurate prediction of secondary structure segments by using a multi-level system

Solvent accessibility is predicted by a neural network method rating at a correlation
coefficient (correlation between experimentally observed and predicted relative solvent
accessibility) of 0.54 cross-validated on a set of 238 globular proteins (Rost & Sander,
Proteins, 1994, 20, 216-226; evaluation of accuracy). The output of the neural network
codes for 10 states of relative accessibility. Expressed in units of the difference
between prediction by homology modelling (best method) and prediction at random (worst
method), PROFacc is some 26 percentage points superior to a comparable neural network
using three output states (buried, intermediate, exposed) and using no information from
multiple alignments.

Transmembrane helices in integral membrane proteins are predicted by a system of neural
networks. The shortcoming of the network system is that often too long helices are
predicted. These are cut by an empirical filter. The final prediction (Rost et al.,
Protein Science, 1995, 4, 521-533; evaluation of accuracy) has an expected per-residue
accuracy of about 95%. The number of false positives, i.e., transmembrane helices
predicted in globular proteins, is about 2%. The neural network prediction of
transmembrane helices (PHDhtm) is refined by a dynamic programming-like algorithm. This
method resulted in correct predictions of all transmembrane helices for 89% of the 131
proteins used in a cross-validation test; more than 98% of the transmembrane helices were
correctly predicted. The output of this method is used to predict topology, i.e., the
orientation of the N-term with respect to the membrane. The expected accuracy of the
topology prediction is > 86%. Prediction accuracy is higher than average for eukaryotic
proteins and lower than average for prokaryotes. PHDtopology is more accurate than all
other methods tested on identical data sets.

If no output file option (such as --fileRdb or --fileOut) is given the RDB formatted
output is written into ./INPUTFILENAME.prof where 'prof' replaces the extension of the
input file. In lack of extension '.prof' is appended to the input file name.

Output format
The RDB format is self-annotating, see example outputs in /share/profphd/prof/exa.

REFERENCES

Rost, B. and Sander, C. (1994a). Combining evolutionary information and neural networks to
predict protein secondary structure. Proteins, 19(1), 55-72.
Rost, B. and Sander, C. (1994b). Conservation and prediction of solvent accessibility in
protein families. Proteins, 20(3), 216-26.
Rost, B., Casadio, R., Fariselli, P., and Sander, C. (1995). Transmembrane helices
predicted at 95% accuracy. Protein Sci, 4(3), 521-33.

OPTIONS

See each keyword for more help. Most of these are likely to be broken.

a alternative connectivity patterns (default=3)

3 predict sec + acc + htm

acc predict solvent accessibility, only

ali add alignment to 'human-readable' PROF output file(s)

arch
system architecture (e.g.: SGI64|SGI5|SGI32|SUNMP|ALPHA)

ascii
write 'human-readable' PROF output file(s)

best
PROF with best accuracy and longest run-time

both
predict secondary structure and solvent accessibility

data
data=<all|brief|normal|detail> for HTML out: only those parts of predictions written

debug
keep most intermediate files, print debugging messages

dirWork
work directory, default: a temporary directory from File::Temp::tempdir. Must be fully
qualified path.

Known to work.

doEval
DO evaluation for list (only for known structures and lists)

doFilterHssp
filter the input HSSP file (excluding some pairs)

doHtmfil
DO filter the membrane prediction (default)

doHtmisit
DO check strength of predicted membrane helix (default)

doHtmref
DO refine the membrane prediction (default)

doHtmtop
DO membrane helix topology (default)

dssp
convert PROF into DSSP format

expand
expand insertions when converting output to MSF format

fast
PROF with lowest accuracy and highest speed

fileCasp
name of PROF output in CASP format (file.caspProf)

fileDssp
name of PROF output in DSSP format (file.dsspProf)

fileHtml
name of PROF output in HTML format (file.htmlProf)

fileMsf
name of PROF output in MSF format (file.msfProf)

fileNotHtm
name of file flagging that no membrane helix was found

fileOut
name of PROF output in RDB format (file.rdbProf)

Known to work.

fileProf
name of PROF output in human readable format (file.prof)

Broken.

fileRdb
name of PROF output in RDB format (file.rdbProf)

Known to work.

fileSaf
name of PROF output in SAF format (file.safProf)

filter
filter the input HSSP file (excluding some pairs)

good
PROF with good accuracy and moderate speed

graph
add ASCII graph to 'human-readable' PROF output file(s)

htm use: 'htm=<N|0.N>' gives minimal transmembrane helix detected default is 'htm=8'
(resp. htm=0.8) smaller numbers more false positives and fewer false negatives!

html argument
'hmtl' or 'html=<all|body|head>' write HTML format of prediction 'html' will result in
that the PROF output is converted to HTML 'html=body' restricts HTML file to the
HTML_BODY tag part 'html=head' restricts HTML file to the HTML_HEADER tag part
'html=all' gives both HEADER and BODY

keepConv
keep the conversion of the input file to HSSP format

keepFilter argument
<*|doKeepFilter=1> keep the filtered HSSP file

keepHssp argument
<*|doKeepHssp=1> keep the intermediate HSSP file

keepNetDb argument
<*|doKeepNetDb=1> keep the intermediate DbNet file(s)

list argument
<*|isList=1> input file is list of files

msf convert PROF into MSF format

nice
give 'nice-D' to set the nice value (priority) of the job

noProfHead
do NOT copy file with tables into local directory

noSearch
short for doSearchFile=0, i.e. no searching of DB files

noascii
surpress writing ASCII (i.e. human readable) result files

nohtml
surpress writing HTML result files

nonice
job will not be niced, i.e. not run with lower priority

notEval
DO NOT check accuracy even when known structures

notHtmfil
do NOT filter the membrane prediction

notHtmisit
do NOT check whether or not membrane helix strong enough

notHtmref
do NOT refine the membrane prediction

notHtmtop
do NOT membrane helix topology

nresPerLineAli
Number of characters used for MSF file. Default: 50.

numresMin
Minimal number of residues to run network, otherwise prd=symbolPrdShort. Default: 9.

optJury
Adds PHD to jury. Default: `normal,usePHD'.

Many other parameters change the default for this one as a side-effect, the list is
not comprehensive:

phd, nophd, /^para(3|Both|Sec|Acc|Htm|CapH|CapE|CapHE)/, /^para?/, jct

para3
Parameter file for sec+acc+htm. Default: `<DIRPROF>/net/PROFboth_best.par'.

paraAcc
Parameter file for acc. Default: `<DIRPROF>/net/PROFacc_best.par'.

paraBoth
Parameter file for sec+acc. Default: `<DIRPROF>/net/PROFboth_best.par'.

paraSec
Parameter file for sec. Default: `<DIRPROF>/net/PROFsec_best.par'.

riSubAcc
Minimal reliability index (RI) for subset PROFacc. Default: 4.

riSubSec
Minimal reliability index (RI) for subset PROFsec. Default: 5.

riSubSym
Symbol for residues predicted with RI < riSubSec/Acc. Default: `.'.

s_k_i_p
problems, manual, hints, notation, txt, known, DONE, Date, date, aa, Lhssp, numaa,
code

saf convert PROF into SAF format

scrAddHelp
scrGoal
neural network switching

scrHelpTxt
Input file formats accepted:
hssp,dssp,msf,saf,fastamul,pirmul,fasta,pir,gcg,swiss

scrIn
list_of_files (or single file) parameter_file

scrName
prof

scrNarg
2

sec predict secondary structure, only

silent
no information written to screen - this is the default

skipMissing
do not abort if input file missing!

sourceFile
prof

test
is just a test (faster)

translate-jobid-in-param-values
String 'jobid' gets substituted with $par{jobid}

tst quick run through program, low accuracy

user
user name

--version
Print version

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