Table 1 Conformational epitope prediction system or algorithm analysis
From: Conformational epitope matching and prediction based on protein surface spiral features
System name | Instructions | year | published | Features and method | Feature classify |
|---|---|---|---|---|---|
CEP | Web system http://196.1.114.49/cgi-bin/cep.pl | 2005 | Nucleic Acids Research | relative solvent accessibility | Physical |
DiscoTope 1.0 | Web system | 2006 | Protein Science | Amino acid log-odds and contact numbers | Physical |
Rapberger’s | Algorithm | 2007 | Journal of Molecular Recognition | solvent accessibility, shape complementarity and binding energies | Physical +Chemical |
BEpro (PEPITO) | Web system http://pepito.proteomics.ics.uci.edu | 2008 | Bioinformatics | DiscoTope features and side chain direction RSA and HSE | Physical |
ElliPro | Web system http://tools.immuneepitope.org/ellipro | 2008 | BMC Bioinformatics | Protrusion index (Elliptical surface) | Physical |
PEPOP | 2008 | BMC Bioinformatics | ASA and epitope sequence | Physical | |
SEPPA | Web system http://lifecenter.sgst.cn/seppa/ | 2009 | Nucleic Acids Research | Amino acid propensity, clustering coefficient, ASA | Physical +Chemical +Triangulation |
Epitopia | Web system http://epitopia.tau.ac.il | 2009 | BMC Bioinformatics | 44 structure features and 41sequence feature with Naïve Bayes classifier | Physical +Chemical + machine learning |
EPCES | Web system http://sysbio.unl.edu/EPCES/ | 2009 | BMC Bioinformatics | residue epitope propensity, conservation score, sidechain energy score, contact number, surface planarity score, and secondary structure composition. | Physical +Chemical |
Soga’s | Algorithm | 2010 | Protein Engineering | Amino acid propensity, ASEP | Physical |
Bepar | Algorithm | 2010 | BMC Structural Biology | paratope-epitope interacting biclique and cooccurrent pattern of interacting residue pairs | Physical +Antibody info. |
CBTOPE | Web system | 2010 | Immunome Research | Binary profile of patterns (BPP) + Physico-chemical profile of patterns (PPP) + Composition profile of patterns (CPP) with SVM | Physical +Chemical |
EPSVR | Web system http://sysbio.unl.edu/services/ | 2010 | BMC Bioinformatics | EPCES feature with SVR | Physical +Chemical + machine learning |
EPMeta | Software | 2010 | BMC Bioinformatics | Combine EPSVR and others 5 system | Multiple system |
Bpredictor | Software | 2011 | BMC Bioinformatics | thick surface patch and amino acid frequency with random forest (RF) algorithm | Physical + machine learning |
Liu’s | Algorithm | 2011 | Journal of Proteomics & Bioinformatics | relative solvent accessibility and b factor with logistic regression | Physical |
ABepar | 2011 | Computational Biology Bioinformatics | Amino Acid pair and contact residue pairs with HMM | Physical + Antibody info. + machine learning | |
DiscoTope 2.0 | Web system www.cbs.dtu.dk/services/DiscoTope/ | 2012 | PLOS ONE | Amino Acid pair and RSA | Physical + different host |
Wen Zhang’s | 2012 | PLOS ONE | Combine 6 CE systems and 4 LE systems | Multiple system | |
PatchTope | 2012 | American Journal of Bioinformatics Research | Surface patch for RSA and b factor with SVM | Physical +Chemical + machine learning | |
CE-KEG | Web system http://cekeg.cs.ntou.edu.tw | 2013 | BMC Bioinformatics | Energy and amino acid pair | Physical +Chemical |
SEPPA2.0 | Web system http://lifecenter.sgst.cn/seppa2/ | 2014 | Nucleic Acids Research | RSA, clustering coefficient, ASA, AAindex for ANN with logistic regression | Physical +Chemical |
EpiPred | Web system http://opig.stats.ox.ac.uk/webapps/sabdab-sabpred/EpiPred.php | 2014 | Structure Bioinformatics | geometric fitting and knowledge-based asymmetric antibody-antigen scoring,then using docking program to enhance prediction ability | Physical +Chemical +docking program |
Hu’s | Algorithm | 2014 | BMC Bioinformatics | Combine 4 CE systems and 4 LE systems | Multiple system |
CBEP | 2014 | BioMed Research International | evolutionary profile, secondary structure, disorder zone, dipeptide composition and physicochemical properties with multiple ML | Multiple system + multiple machine learning | |
CeePre | Algorithm | 2014 | BMC Bioinformatics | B factor, Evolutionary, Amino acid log-odds with random forest | Physical +Chemical +machine learning |
PEASE | Web system http://www.ofranlab.org/PEASE | 2015 | Structural bioinformatics | surface accessibility, secondary structure, predicted disorder, predicted interaction hotspots, the amino acid considered, and amino acids neighboring in sequence with Random Forest | Physical + machine learning + Antibody info. |
Sun’s | Algorithm | 2015 | Bio Research International | EPCES features and mimotope knowledge to enhance prediction ability | Physical +chemical + mimotope |
PUPre | Algorithm | 2015 | BMC Bioinformatics | 209 features +PU learning | Physical +Chemical + machine learning |
SePre | Algorithm | 2017 | BMC Genomics | 239 features + two staged heterogenous learning method | Physical +Chemical + multiple machine learning |
SEPIa | Algorithm | 2017 | BMC Bioinformatics | 13 sequence-based features with naïve Bayesian and random forest classifier | Physical +Chemical + multiple machine learning |