Hydrogen Deuterium Exchange and other Mass Spectrometry-based Approaches for Epitope Mapping

Next-Generation Therapeutic Antibodies for Cancer Treatment: Advancements, Applications, and Challenges

The field of cancer treatment has evolved significantly over the last decade with the emergence of next-generation therapeutic antibodies. Conventional treatments like chemotherapy pose significant challenges, including adverse side effects. Monoclonal antibodies have paved the way for more targeted and effective interventions. The evolution from chimeric to humanized and fully human antibodies has led to a reduction in immunogenicity and enhanced tolerance in vivo. The advent of next-generation antibodies, including bispecific antibodies, nanobodies, antibody-drug conjugates, glyco-engineered antibodies, and antibody fragments, represents a leap forward in cancer therapy. These innovations offer increased potency, adaptability, and reduced drug resistance. Challenges such as target validation, immunogenicity, and high production costs exist. However, technological advancements in antibody engineering techniques provide optimism for addressing these issues. The future promises a paradigm shift, where ongoing research will propel these powerful antibodies to the forefront, revolutionizing the fight against cancer and creating new preventive and curative treatments. This review provides an overview of three next-generation antibody-based molecules, namely bispecific antibodies, antibody-drug conjugates, and nanobodies that have shown promising results in cancer treatment. It discusses the evolution of antibodies from conventional forms to next-generation molecules, along with their applications in cancer treatment, production methods, and associated challenges. The review aims to offer researchers insights into the evolving landscape of next-generation antibody-based cancer therapeutics and their potential to revolutionize treatment strategies.

Integrating Dynamic Network Analysis with AI for Enhanced Epitope Prediction in PD-L1:Affibody Interactions

Understanding binding epitopes involved in protein-protein interactions and accurately determining their structure are long-standing goals with broad applicability in industry and biomedicine. Although various experimental methods for binding epitope determination exist, these approaches are typically low throughput and cost-intensive. Computational methods have potential to accelerate epitope predictions; however, recently developed artificial intelligence (AI)-based methods frequently fail to predict epitopes of synthetic binding domains with few natural homologues. Here we have developed an integrated method employing generalized-correlation-based dynamic network analysis on multiple molecular dynamics (MD) trajectories, initiated from AlphaFold2Multimer structures, to unravel the structure and binding epitope of the therapeutic PD-L1:Affibody complex. Both AlphaFold2 and conventional molecular dynamics trajectory analysis were ineffective in distinguishing between two proposed binding models, parallel and perpendicular. However, our integrated approach, utilizing dynamic network analysis, demonstrated that the perpendicular mode was significantly more stable. These predictions were validated using a suite of experimental epitope mapping protocols, including cross-linking mass spectrometry and next-generation sequencing-based deep mutational scanning. Conversely, AlphaFold3 failed to predict a structure bound in the perpendicular pose, highlighting the necessity for exploratory research in the search for binding epitopes and challenging the notion that AI-generated protein structures can be accepted without scrutiny. Our research underscores the potential of employing dynamic network analysis to enhance AI-based structure predictions for more accurate identification of protein-protein interaction interfaces.

Structural Characterization of Monoclonal Antibodies and Epitope Mapping by FFAP Footprinting

Covalent labeling in combination with mass spectrometry is a powerful approach used in structural biology to study protein structures, interactions, and dynamics. Recently, the toolbox of covalent labeling techniques has been expanded with fast fluoroalkylation of proteins (FFAP). FFAP is a novel radical labeling method that utilizes fluoroalkyl radicals generated from hypervalent Togni reagents for targeting aromatic residues. This report further demonstrates the benefits of FFAP as a new method for structural characterization of therapeutic antibodies and interaction interfaces of antigen-antibody complexes. The results obtained from human trastuzumab and its complex with human epidermal growth factor receptor 2 (HER2) correlate well with previously published structural data and demonstrate the potential of FFAP in structural biology.

Single-domain antibodies reveal unique borrelicidal epitopes on the Lyme disease vaccine antigen, outer surface protein A (OspA)

Camelid-derived, single-domain antibodies (VHHs) have proven to be extremely powerful tools in defining the antigenic landscape of immunologically heterogeneous surface proteins. In this report, we generated a phage-displayed VHH library directed against the candidate Lyme disease vaccine antigen, outer surface protein A (OspA). Two alpacas were immunized with recombinant OspA serotype 1 from Borrelia burgdorferi sensu stricto strain B31, in combination with the canine vaccine RECOMBITEK Lyme containing lipidated OspA. The phage library was subjected to two rounds of affinity enrichment ("panning") against recombinant OspA, yielding 21 unique VHHs within two epitope bins, as determined through competition enzyme linked immunosorbent assays (ELISAs) with a panel of OspA-specific human monoclonal antibodies. Epitope refinement was conducted by hydrogen exchange-mass spectrometry. Six of the monovalent VHHs were expressed as human IgG1-Fc fusion proteins and shown to have functional properties associated with protective human monoclonal antibodies, including B. burgdorferi agglutination, outer membrane damage, and complement-dependent borreliacidal activity. The VHHs displayed unique reactivity profiles with the seven OspA serotypes associated with B. burgdorferi genospecies in the United States and Europe consistent with there being unique epitopes across OspA serotypes that should be considered when designing and evaluating multivalent Lyme disease vaccines.

Epitope Mapping of Japanese Encephalitis Virus Neutralizing Antibodies by Native Mass Spectrometry and Hydrogen/Deuterium Exchange

Japanese encephalitis virus (JEV) remains a global public health concern due to its epidemiological distribution and the existence of multiple strains. Neutralizing antibodies against this infection have shown efficacy in in vivo studies. Thus, elucidation of the epitopes of neutralizing antibodies can aid in the design and development of effective vaccines against different strains of JEV. Here, we describe a combination of native mass spectrometry (native-MS) and hydrogen/deuterium exchange mass spectrometry (HDX-MS) to complete screening of eight mouse monoclonal antibodies (MAbs) against JEV E-DIII to identify epitope regions. Native-MS was used as a first pass to identify the antibodies that formed a complex with the target antigen, and it revealed that seven of the eight monoclonal antibodies underwent binding. Native mass spectra of a MAb (JEV-27) known to be non-binding showed broad native-MS peaks and poor signal, suggesting the protein is a mixture or that there are impurities in the sample. We followed native-MS with HDX-MS to locate the binding sites for several of the complex-forming antibodies. This combination of two mass spectrometry-based approaches should be generally applicable and particularly suitable for screening of antigen-antibody and other protein-protein interactions when other traditional approaches give unclear results or are difficult, unavailable, or need to be validated.

Precision engineering for localization, validation, and modification of allergenic epitopes

The allergen-IgE interaction is essential for the genesis of allergic responses, yet investigation of the molecular basis of these interactions is in its infancy. Precision engineering has unveiled the molecular features of allergen-antibody interactions at the atomic level. High-resolution technologies, including x-ray crystallography, nuclear magnetic resonance spectroscopy, and cryo-electron microscopy, determine allergen-antibody structures. X-ray crystallography of an allergen-antibody complex localizes in detail amino acid residues and interactions that define the epitope-paratope interface. Multiple structures involving murine IgG mAbs have recently been resolved. The number of amino acids forming the epitope broadly correlates with the epitope area. The production of human IgE mAbs from B cells of allergic subjects is an exciting recent development that has for the first time enabled an actual IgE epitope to be defined. The biologic activity of defined IgE epitopes can be validated in vivo in animal models or by measuring mediator release from engineered basophilic cell lines. Finally, gene-editing approaches using the Clustered Regularly Interspaced Short Palindromic Repeats technology to either remove allergen genes or make targeted epitope engineering at the source are on the horizon. This review presents an overview of the identification and validation of allergenic epitopes by precision engineering.

Integrating Dynamic Network Analysis with AI for Enhanced Epitope Prediction in PD-L1:Affibody Interactions

Understanding binding epitopes involved in protein-protein interactions and accurately determining their structure is a long standing goal with broad applicability in industry and biomedicine. Although various experimental methods for binding epitope determination exist, these approaches are typically low throughput and cost intensive. Computational methods have potential to accelerate epitope predictions, however, recently developed artificial intelligence (AI)-based methods frequently fail to predict epitopes of synthetic binding domains with few natural homologs. Here we have developed an integrated method employing generalized-correlation-based dynamic network analysis on multiple molecular dynamics (MD) trajectories, initiated from AlphaFold2 Multimer structures, to unravel the structure and binding epitope of the therapeutic PD-L1:Affibody complex. Both AlphaFold2 and conventional molecular dynamics trajectory analysis alone each proved ineffectual in differentiating between two putative binding models referred to as parallel and perpendicular. However, our integrated approach based on dynamic network analysis showed that the perpendicular mode was significantly more stable. These predictions were validated using a suite of experimental epitope mapping protocols including cross linking mass spectrometry and next-generation sequencing-based deep mutational scanning. Our research highlights the potential of deploying dynamic network analysis to refine AI-based structure predictions for precise predictions of protein-protein interaction interfaces.

Mass Spectrometric ITEM-ONE and ITEM-TWO Analyses Confirm and Refine an Assembled Epitope of an Anti-Pertuzumab Affimer

Intact Transition Epitope Mapping-One-step Non-covalent force Exploitation (ITEM-ONE) analysis reveals an assembled epitope on the surface of Pertuzumab, which is recognized by the anti-Pertuzumab affimer 00557_709097. It encompasses amino acid residues NSGGSIYNQRFKGR, which are part of CDR2, as well as residues FTLSVDR, which are located on the variable region of Pertuzumab's heavy chain and together form a surface area of 1381.46 Å2. Despite not being part of Pertuzumab's CDR2, the partial sequence FTLSVDR marks a unique proteotypic Pertuzumab peptide. Binding between intact Pertuzumab and the anti-Pertuzumab affimer was further investigated using the Intact Transition Epitope Mapping-Thermodynamic Weak-force Order (ITEM-TWO) approach. Quantitative analysis of the complex dissociation reaction in the gas phase afforded a quasi-equilibrium constant (KD m0g#) of 3.07 × 10-12. The experimentally determined apparent enthalpy (ΔHm0g#) and apparent free energy (ΔGm0g#) of the complex dissociation reaction indicate that the opposite reaction-complex formation-is spontaneous at room temperature. Due to strong binding to Pertuzumab and because of recognizing Pertuzumab's unique partial amino acid sequences, the anti-Pertuzumab affimer 00557_709097 is considered excellently suitable for implementation in Pertuzumab quantitation assays as well as for the accurate therapeutic drug monitoring of Pertuzumab in biological fluids.

Hydrophilic Interaction Liquid Chromatography at Subzero Temperature for Hydrogen-Deuterium Exchange Mass Spectrometry

Chromatographic separations at subzero temperature significantly improve the precision of back-exchange-corrected hydrogen-deuterium exchange mass spectrometry (HDX-MS) determinations. Our previously reported dual-enzyme HDX-MS analysis instrument used reversed phase liquid chromatography (RPLC) at -30 °C, but high backpressures limited flow rates and required materials and equipment rated for very high pressures. Here, we report the design and performance of a dual-enzyme HDX-MS analysis instrument comprising a RPLC trap column and a hydrophilic interaction liquid chromatography (HILIC) analytical column in a two-dimensional RPLC-HILIC configuration at subzero temperature. During operation at -30 °C, the HILIC column manifests greatly reduced backpressure, which enables faster analytical flow rates and the use of materials rated for lower maximum pressures. The average peptide eluted from a HILIC column during a 40 min gradient at -30 °C contained ≈13% more deuterium than peptides eluted from a tandem RPLC-RPLC apparatus using a conventional 8 min gradient at 0 °C. A subset of peptides eluted from the HILIC apparatus contained ≈24% more deuterium.