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Abstract
REFERENCE
Reliable B cell epitope predictions: Impacts of method development and improved benchmarking
Jens Vindahl Kringelum, Claus Lundegaard, Ole Lund, and Morten Nielsen
Plos Computational Biology, 2012
Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark
Abstract
The interaction between antibodies and antigens is one of the most
important immune system mechanisms for clearing infectious organisms
from the host. Antibodies bind to antigens at sites referred to
as B-cell epitopes. Identification of the exact location of B-cell
epitopes is essential in several biomedical applications such as;
rational vaccine design, development of disease diagnostics and
immunotherapeutics. However, experimental mapping of epitopes is
resource intensive making in silico methods an appealing complementary
approach.
To date, the reported performance of methods for in silico
mapping of B-cell epitopes has been moderate. Several issues regarding
the evaluation data sets may however have led to the performance values
being underestimated: Rarely, all potential epitopes have been mapped on
an antigen, and antibodies are generally raised against the antigen in
a given biological context not against the antigen monomer. Improper
dealing with these aspects leads to many artificial false positive
predictions and hence to incorrect low performance values.
To demonstrate
the impact of proper benchmark definitions, we here present an updated
version of the DiscoTope method incorporating a novel spatial neighborhood
definition and half-sphere exposure as surface measure. Compared to other
state-of-the-art prediction methods, Discotope-2.0 displayed improved
performance both in cross-validation and in independent evaluations. Using
DiscoTope-2.0, we assessed the impact on performance when using proper
benchmark definitions. For 13 proteins in the training data set where
sufficient biological information was available to make a proper
benchmark redefinition, the average AUC performance was improved from
0.791 to 0.824. Similarly, the average AUC performance on an independent
evaluation data set improved from 0.712 to 0.727
Our results thus demonstrate that given proper benchmark definitions,
B-cell epitope prediction methods achieve highly significant predictive
performances suggesting these tools to be a powerful asset in rational
epitope discovery.
The updated version of DiscoTope is available at www.cbs.dtu.dk/services/DiscoTope-2.0.
Link to Paper
CORRESPONDENCE
Morten Nielsen,
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