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. 2016 Feb 12;7:126. doi: 10.3389/fpls.2016.00126

Table 2.

Features of the most common computational tools available for the prediction of trans-membrane (TM) domains.

Tools Important features Website/reference
TMHMM Server v. 2.0 Predicts trans-membrane (TM) domains; a common mistake by the program consists in reversing the direction of proteins with one TM segment www.cbs.dtu.dk/services/TMHMM/
TMpred Predicts TM regions and orientation. The TMpred program makes a prediction of membrane-spanning regions and their orientation www.ch.embnet.org
Hofman, 1993
TMbase Offers a good database of TM proteins and their helical membrane- spanning domains; TMbase was originally meant as a tool for analyzing the properties of TM proteins www.ch.embnet.org
Hofman, 1993
HMMTOP Serves as automatic server for predicting TM helices and topology of proteins Tusnady and Simon, 2001 www.enzim.hu/hmmtop/
PredictProtein Predicts secondary structures Rost et al., 2004 www.predictprotein.org/
SOSUI Classifies and predicts secondary structures of membrane proteins http://harrier.nagahama-i-bio.ac.jp/sosui/
TopPred 1.10 Predicts topology of membrane proteins http://mobyle.pasteur.fr/cgi-bin/portal.py?\#forms::toppred
DAS-TMfilter server Filters false positive TM protein predictions http://mendel.imp.ac.at/sat/DAS/DAS.html
CCTOP (Consensus Constrained TOPology prediction) Performs TM topology predictions http://cctop.enzim.ttk.mta.hu/
MetaTM Predicts TM topologies through a consensus method Klammer et al., 2009 http://metatm.sbc.su.se/
MINNOU Predicts membrane proteins with and without explicit use of hydropathy profiles and alignments http://minnou.cchmc.org/
PHDhtm Predicts the location of helical TM segments in integral membrane proteins through a neural network system https://npsa-prabi.ibcp.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_htm.html
Phobius Combines TM topology and signal peptide predictions Käll et al., 2007
http://phobius.sbc.su.se/poly.html
PRED-TMR Refines a standard hydrophobicity with a detection of potential edges Pasquier et al., 1999
http://athina.biol.uoa.gr/
SCAMPI Uses position-specific amino acid contributions to the free energy of membrane insertion and also uses the current best statistics-based topology predictors Bernsel et al., 2008 http://scampi.cbr.su.se/
SOMRuler Offers an interpretable TM helices predictor Yu et al., 2011 www.csbio.sjtu.edu.cn/bioinf/SOMRuler/
ConPred Predicts TM topology based on a consensus approach by combining the results of several methods Arai et al., 2004
http://bioinfo.si.hirosaki-u.ac.jp/ConPred2/
TMBB-DB Compiles the predictions made by the Freeman–Wimley algorithm http://beta-barrel.tulane.edu/
TMalphaDB Quantifies the structural distortion induced by a sequence motif in alpha TM segments http://lmc.uab.cat/TMalphaDB/
TMexpo Predicts rotational preferences of TM helices to facilitate structural modeling. TMexpo calculates rotational angles of TMHs based on the predicted relative accessible surface area http://bio-cluster.iis.sinica.edu.tw/TMexpo/
TMMOD Uses an improved hidden Markov model for the identification and topology prediction of TM proteins http://liao.cis.udel.edu/website/servers/TMMOD/scripts/frame.php?p=submit
Asymmetric Ez Assesses the energy and positions of protein sequences or structures in and on the membrane through a knowledge-based potential http://ez.degradolab.org/ez/