Predicting Interaction Sites from the Energetics of Isolated Proteins: A New Approach to Epitope Mapping

An increasing number of functional studies of proteins have shown that
sequence and structural similarities alone may not be sufficient for
reliable prediction of their interaction properties. This is
particularly true for proteins recognizing specific antibodies, where
the prediction of antibody-binding sites, called epitopes, has proven
challenging. The antibody-binding properties of an antigen depend on its
structure and related dynamics. Aiming to predict the antibody-binding
regions of a protein, we investigate a new approach based on the
integrated analysis of the dynamical and energetic properties of
antigens, to identify nonoptimized, low-intensity energetic interaction
networks in the protein structure isolated in solution. The method is
based on the idea that recognition sites may correspond to localized
regions with low-intensity energetic couplings with the rest of the
protein, which allows them to undergo conformational changes, to be
recognized by a binding partner, and to tolerate mutations with minimal
energetic expense. Upon analyzing the results on isolated proteins and
benchmarking against antibody complexes, it is found that the method
successfully identifies binding sites located on the protein surface
that are accessible to putative binding partners. The combination of
dynamics and energetics can thus discriminate between epitopes and other
substructures based only on physical properties. We discuss implications
for vaccine design.