ElliPro: a new structure-based tool for the prediction of antibody epitopes

By Julia V. Ponomarenko, H. Bui, Wei Li, Nicholas Fusseder, Philip E. Bourne, Alessandro Sette, Björn Peters. BMC Bioinformatics, 2008

1,634 citations recorded by the source corpus.

BackgroundReliable prediction of antibody, or B-cell, epitopes remains challenging yet highly desirable for the design of vaccines and immunodiagnostics. A correlation between antigenicity, solvent accessibility, and flexibility in proteins was demonstrated. Subsequently, Thornton and colleagues proposed a method for identifying continuous epitopes in the protein regions protruding from the protein's globular surface. The aim of this work was to implement that method as a web-tool and evaluate its performance on discontinuous epitopes known from the structures of antibody-protein complexes.ResultsHere we present ElliPro, a web-tool that implements Thornton's method and, together with a residue clustering algorithm, the MODELLER program and the Jmol viewer, allows the prediction and visualization of antibody epitopes in a given protein sequence or structure. ElliPro has been tested on a benchmark dataset of discontinuous epitopes inferred from 3D structures of antibody-protein complexes. In comparison with six other structure-based methods that can be used for epitope prediction, ElliPro performed the best and gave an AUC value of 0.732, when the most significant prediction was considered for each protein. Since the rank of the best prediction was at most in the top three for more than 70% of proteins and never exceeded five, ElliPro is considered a useful research tool for identifying antibody epitopes in protein antigens. ElliPro is available at http://tools.immuneepitope.org/tools/ElliPro.ConclusionThe results from ElliPro suggest that further research on antibody epitopes considering more features that discriminate epitopes from non-epitopes may further improve predictions. As ElliPro is based on the geometrical properties of protein structure and does not require training, it might be more generally applied for predicting different types of protein-protein interactions.

Subfields: Molecular Biology, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/5093b4fb8927a20e3050a243ef0770125fc8a96a

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Citations in the corpus

The Immune Epitope Database and Analysis Resource in Epitope Discovery and Synthetic Vaccine Design (2017, methodology): “In this study, ElliPro had an AUC value of 0.69 and was outperformed by DiscoTope 1.1 (AUC = 0.71) and DiscoTope 2.0 (AUC = 0.73).”
Reliable B Cell Epitope Predictions: Impacts of Method Development and Improved Benchmarking (2012, methodology): “We investigate to what degree similar performance improvements were observed for the methods PEPITO, ElliPro and SEPPA when considering the ‘‘biological unit’’ for prediction and redefining the benchmark setup to accommodate multiple epitopes.”
Structural analysis of B-cell epitopes in antibody:protein complexes (2012, methodology): “…years, features of B-cell epitopes have extensively been utilized in computational mapping of B-cell epitopes (Andersen et al., 2006; Chen et al., 2007; Huang et al., 2007; Liang et al., 2010; Ponomarenko et al., 2008; Rubinstein et al., 2009; Sweredoski and Baldi, 2009, 2008; Zhao and Li, 2010).”
IEDB-AR: immune epitope database—analysis resource in 2019 (2019, background): “…epitope prediction tools, such as BepiPred (11), various amino acid physicochemical property based scales (http://tools.iedb.org/bcell/), and discontinuous B cell epitope prediction tools, such as Dis-coTope (http://tools.iedb.org/discotope/) (12) and ElliPro (http://tools.iedb.org/ellipro/) (13).”
Fundamentals and Methods for T- and B-Cell Epitope Prediction (2017, methodology): “Subsequently, more methods were developed, like ElliPro [121] that aims to identify protruding regions in antigen surfaces and PEPITO [122] and SEPPA [123] that combine single physicochemical properties of amino acids and geometrical structure properties.”
Immune epitope database analysis resource (2012, methodology): “Details on the comparison of ElliPro with other structure-based epitope prediction methods can be found in (23).”