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Protein oligomerization regulates many critical physiological processes, and its dysregulation can contribute to dysfunction and diseases. Elucidating the assembly pathways and quantifying their underlying thermodynamic and kinetic parameters are crucial for a comprehensive understanding of biological processes and for advancing therapeutics targeting abnormal protein oligomerization. Established binding assays, with limited mass precision, often rely on simplified models for data interpretation. In contrast, high-resolution native mass spectrometry (nMS) can directly determine the stoichiometry of biomolecular complexes in vitro. However, quantification is hindered by the fact that the relative abundances of gas-phase ions generally do not reflect solution concentrations due to nonuniform response factors. Recently, slow mixing mode (SLOMO)-nMS, which can quantify the relative response factors of interacting species, has been demonstrated to reliably measure the affinity ( K d ) of binary biomolecular complexes. Here, we introduce an extended form of SLOMO-nMS that enables simultaneous quantification of the thermodynamics in multistep association reactions. Application of this method to homo-oligomerization of concanavalin A and insulin confirmed the reliability of the assay and uncovered details about the assembly processes that had previously resisted elucidation. Results acquired using SLOMO-nMS implemented with charge detection shed new light on the binding of recombinant human angiotensin-converting enzyme 2 and the SARS-CoV-2 spike protein. Importantly, new assembly pathways were uncovered, and the affinities of these interactions, which regulate host cell infection, were quantified. Together, these findings highlight the tremendous potential of SLOMO-nMS to accelerate the characterization of protein assembly pathways and thermodynamics and, in so doing, enhance fundamental biological understanding and facilitate therapeutic development. https://orcid.org/0000-0002-3389-7112.

Interactions between glycan-binding proteins (GBPs) and glycosphingolipids (GSLs) present in cell membranes are implicated in a wide range of biological processes. However, studying GSL binding is hindered by the paucity of purified GSLs and the weak affinities typical of monovalent GBP-GSL interactions. Native mass spectrometry (nMS) performed using soluble model membranes is a promising approach for the discovery of GBP ligands, but the detection of weak interactions remains challenging. The present work introduces ME mbrane AN chor-assisted nMS (MEAN-nMS) for the detection of low-affinity GBP-GSL complexes. The assay utilizes a membrane anchor, produced by covalent cross-linking of the GBP and a lipid in the membrane, to localize the GBP on the surface and promote GSL binding. Ligands are identified by nMS detection of intact GBP-GSL complexes (MEAN-nMS) or using a catch-and-release (CaR) strategy, wherein GSLs are released from GBP-GSL complexes upon collisional activation and detected (MEAN-CaR-nMS). To establish reliability, a library of purified gangliosides incorporated into nanodiscs was screened against human immune lectins, and the results compared with affinities of the corresponding ganglioside oligosaccharides. Without a membrane anchor, nMS analysis yielded predominantly false negatives. In contrast, all ligands were identified by MEAN-(CaR)-nMS, with no false positives. To highlight the potential of MEAN-CaR-nMS for ligand discovery, a natural library of GSLs was incorporated into nanodiscs and screened against human and viral proteins to uncover elusive ligands. Finally, nMS-based detection of GSL ligands directly from cells is demonstrated. This breakthrough paves the way for shotgun glycomics screening using intact cells.

Electrospray ionization mass spectrometry (ESI-MS) is a powerful label-free assay for detecting noncovalent biomolecular complexes in vitro and is increasingly used to quantify binding thermochemistry. A common assumption made in ESI-MS affinity measurements is that the relative ion signals of free and bound species quantitatively reflect their relative concentrations in solution. However, this is valid only when the interacting species and their complexes have similar ESI-MS response factors (RFs). For many biomolecular complexes, such as protein-protein interactions, this condition is not satisfied. Existing strategies to correct for nonuniform RFs are generally incompatible with static nanoflow ESI (nanoESI) sources, which are typically used for biomolecular interaction studies, thereby significantly limiting the utility of ESI-MS. Here, we introduce slow mixing mode (SLOMO) nanoESI-MS, a direct technique that allows both the RF and affinity ( K d ) for a biomolecular interaction to be determined from a single measurement using static nanoESI. The approach relies on the continuous monitoring of interacting species and their complexes under nonhomogeneous solution conditions. Changes in ion signals of free and bound species as the system approaches or moves away from a steady-state condition allow the relative RFs of the free and bound species to be determined. Combining the relative RF and the relative abundances measured under equilibrium conditions enables the K d to be calculated. The reliability of SLOMO and its ease of use is demonstrated through affinity measurements performed on peptide-antibiotic, protease-protein inhibitor, and protein oligomerization systems. Finally, affinities measured for the binding of human and bacterial lectins to a nanobody, a viral glycoprotein, and glycolipids displayed within a model membrane highlight the tremendous power and versatility of SLOMO for accurately quantifying a wide range of biomolecular interactions important to human health and disease., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

Mass spectrometry-based shotgun glycomics (MS-SG) is a rapid, sensitive, label-, and immobilization-free approach for the discovery of natural ligands of glycan-binding proteins (GBPs). To perform MS-SG, natural libraries of glycans derived from glycoconjugates in cells or tissues are screened against a target GBP using catch-and-release electrospray ionization mass spectrometry (CaR-ESI-MS). Because glycan concentrations are challenging to determine, ligand affinities cannot be directly measured. In principle, relative affinities can be ranked by combining CaR-ESI-MS data with relative concentrations established by hydrophilic interaction liquid chromatography (HILIC) performed on the fluorophore-labeled glycan library. To validate this approach, as well as the feasibility of performing CaR-ESI-MS directly on labeled glycans, libraries of labeled N -glycans extracted from the human monocytic U937 cells or intestinal tissues were labeled with 2-aminobenzamide (2-AB), 2-aminobenzoic acid (2-AA), or procainamide (proA). The libraries were screened against plant and human GBPs with known specificities for α2-3- and α2-6-linked sialosides and quantified by HILIC. Dramatic differences, in some cases, were found for affinity rankings obtained with libraries labeled with different fluorophores, as well as those produced using the combined unlabeled/labeled library approach. The origin of these differences could be explained by differential glycan labeling efficiencies, the impact of specific labels on glycan affinities for the GBPs, and the relative efficiency of release of ligands from GBPs in CaR-ESI-MS. Overall, the results of this study suggest that the 2-AB(CaR-ESI-MS)/2-AB(HILIC) combination provides the most reliable description of the binding specificities of GBPs for N -glycans and is recommended for MS-SG applications.