Dengue virus antibody database: Systematically linking serotype-specificity with epitope mapping in dengue virus

<div><p>Background</p><p>A majority infections caused by dengue virus (DENV) are asymptomatic, but a higher incidence of severe illness, such as dengue hemorrhagic fever, is associated with secondary infections, suggesting that pre-existing immunity plays a central role in dengue pathogenesis. Primary infections are typically associated with a largely serotype-specific antibody response, while secondary infections show a shift to a broadly cross-reactive antibody response.</p><p>Methods/Principal findings</p><p>We hypothesized that the basis for the shift in serotype-specificity between primary and secondary infections can be found in a change in the antibody fine-specificity. To investigate the link between epitope- and serotype-specificity, we assembled the Dengue Virus Antibody Database, an online repository containing over 400 DENV-specific mAbs, each annotated with information on <i>1</i>) its origin, including the immunogen, host immune history, and selection methods, <i>2</i>) binding/neutralization data against all four DENV serotypes, and <i>3</i>) epitope mapping at the domain or residue level to the DENV E protein. We combined epitope mapping and activity information to determine a residue-level index of epitope propensity and cross-reactivity and generated detailed composite epitope maps of primary and secondary antibody responses. We found differing patterns of epitope-specificity between primary and secondary infections, where secondary responses target a distinct subset of epitopes found in the primary response. We found that secondary infections were marked with an enhanced response to cross-reactive epitopes, such as the fusion-loop and E-dimer region, as well as increased cross-reactivity in what are typically more serotype-specific epitope regions, such as the domain I-II interface and domain III.</p><p>Conclusions/Significance</p><p>Our results support the theory that pre-existing cross-reactive memory B cells form the basis for the secondary antibody response, resulting in a broadening of the response in terms of cross-reactivity, and a focusing of the response to a subset of epitopes, including some, such as the fusion-loop region, that are implicated in poor neutralization and antibody-dependent enhancement of infection.</p></div

Differences in epitope fine-specificity between mouse and human.

<p>Mapping of epitope propensity on to the structure of the DENV E protein dimer for mAbs from mouse (A) and human (B). Spheres correspond to epitope residues. The size of the sphere corresponds to its epitope propensity, as described previously. C. Difference in epitope propensity between mouse and human across the E protein. Residue color corresponds to domain—purple, cyan, and magenta, for DI, DII, and DIII, respectively.</p

Serotype-specificity and epitope mapping in primary and secondary dengue infections.

<p>A) Histograms of human mAbs in the primary (left) and secondary infection (right) data sets. B) Epitope propensity in primary (left) and secondary (right) infections across E protein amino acid sequence. Points are colored with respect to epitope cross-reactivity, or the proportion of mAbs that are associated with a given epitope residue that are classified as ‘complex’: red (>60%), orange (30–60%), or yellow (< 30%). C) A composite map of epitope propensity and cross-reactivity on the structure of the DENV E protein dimer for mAbs from primary (left) and secondary (right) infections. Epitope regions DI/DII interface, dimer interface, fusion loop, DII/DIII interface, and DIII-lateral ridge (LR) are highlighted. Spheres correspond to epitope residues. The size of the sphere corresponds to its epitope propensity: low propensity (<5%, small spheres), medium propensity (>5% and <10%; medium spheres), and high propensity (>10%, large spheres). The color of the sphere corresponds to the epitope cross-reactivity as described above.</p

Dengue virus antibody database.

<p>Each monoclonal antibody in the database is annotated with information about its origin and selection, activity against all four dengue serotypes, epitope mapping, and relevant references.</p

Sequence variation and serotype specificity in DENV mAbs.

<p>A) Histogram of sequence conservation among DENV 1–4 E protein epitope residues for type-specific and complex mAbs from primary and secondary infections, compared with all residues in the E protein. B) Sequence variation between consensus sequences of DENV1-4, at the epitope level measured by the average <i>p</i>_{<i>epitope</i>} for type-specific mAbs from primary infection (<i>N</i> = 45), complex mAbs from primary infection (<i>N</i> = 24), and complex mAbs from secondary infections (<i>N</i> = 25). Only mAbs with epitope definitions consisting of at least five residues were considered. Error bars correspond to the standard deviation of <i>p</i>_{<i>epitope</i>} values. A statistically significant difference is indicated by ‘*’, corresponding to p < 0.001.</p

Database composition.

<p>Database composition.</p

Quantitative Predictions of Binding Free Energy Changes in Drug-Resistant Influenza Neuraminidase

<div><p>Quantitatively predicting changes in drug sensitivity associated with residue mutations is a major challenge in structural biology. By expanding the limits of free energy calculations, we successfully identified mutations in influenza neuraminidase (NA) that confer drug resistance to two antiviral drugs, zanamivir and oseltamivir. We augmented molecular dynamics (MD) with Hamiltonian Replica Exchange and calculated binding free energy changes for H274Y, N294S, and Y252H mutants. Based on experimental data, our calculations achieved high accuracy and precision compared with results from established computational methods. Analysis of 15 µs of aggregated MD trajectories provided insights into the molecular mechanisms underlying drug resistance that are at odds with current interpretations of the crystallographic data. Contrary to the notion that resistance is caused by mutant-induced changes in hydrophobicity of the binding pocket, our simulations showed that drug resistance mutations in NA led to subtle rearrangements in the protein structure and its dynamics that together alter the active-site electrostatic environment and modulate inhibitor binding. Importantly, different mutations confer resistance through different conformational changes, suggesting that a generalized mechanism for NA drug resistance is unlikely.</p> </div

Representative structures for zanamivir (A, B and C) and oseltamivir (D, E and F) bound to WT and mutant NAs from the SRSM/HREX simulations.

<p>Salt-bridges and hydrogen bonds are depicted as magenta and orange dashed lines, respectively. Positively charged, negatively charged, and uncharged polar groups are noted as blue, red, and purple circles, respectively, and residues of interest are labeled. Mutated residues are underlined.</p

Alchemical thermodynamic paths using SRMM (A) and SRSM (B) in the bound state between wild type (<i>wt</i>) and a mutant (<i>mut¹</i>).

<p>The paths (arrows) between end states (squares) going through nonphysical reference states (ovals) are shown. The SRMM uses a common reference state ‘hub’ for all mutations and ligands (RS^1*2*3* L^*); SRSM uses a mutation and ligand-specific reference state (RS^1* L^X). Decoupled residues and ligands are noted by an ‘*’. Thermodynamic paths in the unbound state have a similar form but without the ligand.</p

Comparison of WT and mutant dynamics.

<p>For WT and H274Y, N294S, and Y252H, distance distributions between the atoms C_δ of E276 and N_ε of R292 and between the atoms C_δ of E277 and N_ε of R292 are shown for oseltamivir (<b>A, C</b>) and zanamivir (<b>B, D</b>), respectively.</p