Experimentally validated computational docking to characterize protein- protein interactions

Each biomolecule in a living organism needs to adopt a specific threedimensional conformation to function properly. Function itself is usually achieved by specific interactions between biomolecular units. Structural knowledge at atomic level of biomolecules and their interaction is important to understand the mechanisms leading to biological response and to develop strategies to interfere with them when necessary. Antibodies are molecules of the immune system playing an ever more prominent role in basic research as well as in the biotechnology and pharmaceutical sectors. Characterizing their region of interaction with other proteins (epitopes) is useful for purposes ranging from molecular biology research to vaccine design. During my PhD studies I used a combination of solution NMR mapping, molecular biology and computational docking to provide a structural and biophysical characterization of new neutralizing antibodies from Dengue virus recovered subjects, comparing the binding of the same antibody to the four Dengue serotypes and the binding of different antibodies to the same serotype. We were able to rationally mutate an antibody to first alter its selectivity for different viral strains and then increase its neutralization by ~40 folds. For the first time, this was achieved without the availability of an x-ray structure. In a second sub-project, I investigated the interaction of the chemokine CXCL12 with the chromatin-associated protein HMGB1, confirming their direct interaction (only proposed but never proved before) and providing a structural explanation for the HMGB1 dependent increase of CXCL12 cellular activity. High profile publications resulted from the two above projects. The above mentioned projects relied heavily on solution NMR spectroscopy, which is ideally suited to the atomic level characterization of intermolecular interfaces and, as a consequence, to antibody epitope discovery. Having provided a residue-level description of a protein-protein interface by NMR, we subsequently used this experimental information to guide and validate computational docking experiments aimed at providing a three dimensional structure of the protein-protein (or antibody-protein) complex of interest. In collaboration with other members of my research group I validated the use of NMR and computational simulations to study antibody-antigen interactions, publishing two reviews in collaboration with other members of my research group

Computational docking of antibody-antigen complexes, opportunities and pitfalls illustrated by influenza hemagglutinin

Antibodies play an increasingly important role in both basic research and the pharmaceutical industry. Since their efficiency depends, in ultimate analysis, on their atomic interactions with an antigen, studying such interactions is important to understand how they function and, in the long run, to design new molecules with desired properties. Computational docking, the process of predicting the conformation of a complex from its separated components, is emerging as a fast and affordable technique for the structural characterization of antibody-antigen complexes. In this manuscript, we first describe the different computational strategies for the modeling of antibodies and docking of their complexes, and then predict the binding of two antibodies to the stalk region of influenza hemagglutinin, an important pharmaceutical target. The purpose is two-fold: on a general note, we want to illustrate the advantages and pitfalls of computational docking with a practical example, using different approaches and comparing the results to known experimental structures. On a more specific note, we want to assess if docking can be successful in characterizing the binding to the same influenza epitope of other antibodies with unknown structure, which has practical relevance for pharmaceutical and biological research. The paper clearly shows that some of the computational docking predictions can be very accurate, but the algorithm often fails to discriminate them from inaccurate solutions. It is of paramount importance, therefore, to use rapidly obtained experimental data to validate the computational results

Rational engineering of a human anti-dengue antibody through experimentally validated computational docking

Antibodies play an increasing pivotal role in both basic research and the biopharmaceutical sector, therefore technology for characterizing and improving their properties through rational engineering is desirable. This is a difficult task thought to require high-resolution x-ray structures, which are not always available. We, instead, use a combination of solution NMR epitope mapping and computational docking to investigate the structure of a human antibody in complex with the four Dengue virus serotypes. Analysis of the resulting models allows us to design several antibody mutants altering its properties in a predictable manner, changing its binding selectivity and ultimately improving its ability to neutralize the virus by up to 40 fold. The successful rational design of antibody mutants is a testament to the accuracy achievable by combining experimental NMR epitope mapping with computational docking and to the possibility of applying it to study antibody/pathogen interactions

HMGB1 promotes recruitment of inflammatory cells to damaged tissues by forming a complex with CXCL12 and signaling via CXCR4

After tissue damage, inflammatory cells infiltrate the tissue and release proinflammatory cytokines. HMGB1 (high mobility group box 1), a nuclear protein released by necrotic and severely stressed cells, promotes cytokine release via its interaction with the TLR4 (Toll-like receptor 4) receptor and cell migration via an unknown mechanism. We show that HMGB1- induced recruitment of inflammatory cells depends on CXCL12. HMGB1 and CXCL12 form a heterocomplex, which we characterized by nuclear magnetic resonance and surface plasmon resonance, that acts exclusively through CXCR4 and not through other HMGB1 receptors. Fluorescence resonance energy transfer data show that the HMGB1–CXCL12 heterocomplex promotes different conformational rearrangements of CXCR4 from that of CXCL12 alone. Mononuclear cell recruitment in vivo into air pouches and injured muscles depends on the heterocomplex and is inhibited by AMD3100 and glycyrrhizin. Thus, inflammatory cell recruitment and activation both depend on HMGB1 via different mechanisms

Rational Engineering of a Human Anti-Dengue Antibody through Experimentally Validated Computational Docking

<div><p>Antibodies play an increasing pivotal role in both basic research and the biopharmaceutical sector, therefore technology for characterizing and improving their properties through rational engineering is desirable. This is a difficult task thought to require high-resolution x-ray structures, which are not always available. We, instead, use a combination of solution NMR epitope mapping and computational docking to investigate the structure of a human antibody in complex with the four Dengue virus serotypes. Analysis of the resulting models allows us to design several antibody mutants altering its properties in a predictable manner, changing its binding selectivity and ultimately improving its ability to neutralize the virus by up to 40 fold. The successful rational design of antibody mutants is a testament to the accuracy achievable by combining experimental NMR epitope mapping with computational docking and to the possibility of applying it to study antibody/pathogen interactions.</p> </div

Antibody DV32.6 binds the four Dengue serotypes with different affinity.

<p>SPR sensorgrams showing association and dissociation of DV32.6 to DIII of each Dengue serotype. The antibody was immobilized on the sensor surface, followed by injection of DIII at the concentrations indicated in the figure. The line fitted to the experimental data and used to calculate the binding affinities is drawn in gray. KD values are 145±9 nM for DenV1; 7±0.2 nM for DenV2; 73±16 nM for DenV3; 34±7 nM for DenV4. Despite binding more weakly to DenV1 and DenV3 than DenV4, the antibody neutralizes those serotypes better than DenV4.</p

Antibody DV32.6 interaction with the four Dengue serotypes.

<p>NMR epitope mapping results (a, b): residues whose NMR signal is affected by antibody binding are indicated in red on the sequence (a) and on the surface representation (b) of DIII of each DenV serotype. Residues for which no NMR information is available are coloured gray in the sequence. The discontinuous epitope shows slight variations amongst serotypes both in sequence and structure, including some conserved residues and others that are not. The former explain why DV32.6 can bind to all four serotypes, the latter are likely responsible for the different binding and neutralization properties. Computational docking results (c). Surface representation of the antigen binding site of DV32.6. Antibody residues predicted to interact with DenV are shown in blue; light and heavy chains are in light and dark gray, respectively. Both antibody chains contribute to the binding interface in DenV1 and DenV3 whereas only the light chain and the H3 loop bind to DenV2 and DenV4. Some of the residues mutated to alter the antibody properties in a predictable way (see text) are indicated by red circles and labelled on DenV1.</p