Collision-Induced Affinity Selection Mass Spectrometry for Identification of Ligands

Decoding the molecular interplay in the central dogma: An overview of mass spectrometry-based methods to investigate protein-metabolite interactions

With the emergence of next-generation nucleotide sequencing and mass spectrometry-based proteomics and metabolomics tools, we have comprehensive and scalable methods to analyze the genes, transcripts, proteins, and metabolites of a multitude of biological systems. Despite the fascinating new molecular insights at the genome, transcriptome, proteome and metabolome scale, we are still far from fully understanding cellular organization, cell cycles and biology at the molecular level. Significant advances in sensitivity and depth for both sequencing as well as mass spectrometry-based methods allow the analysis at the single cell and single molecule level. At the same time, new tools are emerging that enable the investigation of molecular interactions throughout the central dogma of molecular biology. In this review, we provide an overview of established and recently developed mass spectrometry-based tools to probe metabolite-protein interactions-from individual interaction pairs to interactions at the proteome-metabolome scale.

Advancing Kir4.2 Channel Ligand Identification through Collision-Induced Affinity Selection Mass Spectrometry

The inwardly rectifying potassium Kir4.2 channel plays a crucial role in regulating membrane potentials and maintaining potassium homeostasis. Kir4.2 has been implicated in various physiological processes, including insulin secretion, gastric acid regulation, and the pathogenesis of central nervous system diseases. Despite its significance, the number of identified ligands for Kir4.2 remains limited. In this study, we established a method to directly observe ligands avoiding a requirement to observe the high-mass ligand-membrane protein-detergent complexes. This method used collision-induced affinity selection mass spectrometry (CIAS-MS) to identify ligands dissociated from the Kir4.2 channel-detergent complex. The CIAS-MS approach integrated all stages of affinity selection within the mass spectrometer, offering advantages in terms of time efficiency and cost-effectiveness. Additionally, we explored the effect of collisional voltage ramps on the dissociation behavior of the ligand and the ligand at different concentrations, demonstrating dose dependency.

Identification of Ligands for Ion Channels: TRPM2

Transient receptor potential melastatin 2 (TRPM2) is a calcium-permeable, nonselective cation channel with a widespread distribution throughout the body. It is involved in many pathological and physiological processes, making it a potential therapeutic target for various diseases, including Alzheimer's disease, Parkinson's disease, and cancers. New analytical techniques are beneficial for gaining a deeper understanding of its involvement in disease pathogenesis and for advancing the drug discovery for TRPM2-related diseases. In this work, we present the application of collision-induced affinity selection mass spectrometry (CIAS-MS) for the direct identification of ligands binding to TRPM2. CIAS-MS circumvents the need for high mass detection typically associated with mass spectrometry of large membrane proteins. Instead, it focuses on the detection of small molecules dissociated from the ligand-protein-detergent complexes. This affinity selection approach consolidates all affinity selection steps within the mass spectrometer, resulting in a streamlined process. We showed the direct identification of a known TRPM2 ligand dissociated from the protein-ligand complex. We demonstrated that CIAS-MS can identify binding ligands from complex mixtures of compounds and screened a compound library against TRPM2. We investigated the impact of voltage increments and ligand concentrations on the dissociation behavior of the binding ligand, revealing a dose-dependent relationship.

Discovery of Anti-SARS-CoV-2 Nsp9 Binders from Natural Products by a Native Mass Spectrometry Approach

The search for effective antiviral agents against SARS-CoV-2 remains a critical global endeavor. In this study, we focused on the viral nucleocapsid protein Nsp9, which is a key player in viral RNA replication and an attractive drug target. Employing a two-pronged approach, an in-house natural product library was screened using native mass spectrometry to identify compounds capable of binding to Nsp9. From the initial screening, apart from the previously reported hit oridonin (protein binding ratio of 0.56 in the initial screening, Kd = 7.2 ± 1.0 μM), we have identified a second Nsp9-interacting compound, the diterpenoid ryanodine, with a protein binding ratio of 0.3 and a Kd of 48.05 ± 5.03 μM. To gain deeper insights into the binding interactions and to explore potential structural requirements, the collision-induced affinity selection mass spectrometry (CIAS-MS) approach allowed us to identify six known oridonin analogues produced by the plant Rabdosia rubescens, each with varying affinities to Nsp9. Native MS validation of their individual binding activities to Nsp9 revealed that all analogues exhibited reduced affinity compared to oridonin. Structural-activity relationship analysis highlighted key functional groups, including 1-OH, 6-OH, 7-OH, and the enone moiety, which are crucial for Nsp9 binding. Combined data from our native mass spectrometry and CIAS-MS approaches provide valuable insights into the molecular interactions between Nsp9 and these compounds.

Dissecting the structural heterogeneity of proteins by native mass spectrometry

A single gene yields many forms of proteins via combinations of post-transcriptional/post-translational modifications. Proteins also fold into higher-order structures and interact with other molecules. The combined molecular diversity leads to the heterogeneity of proteins that manifests as distinct phenotypes. Structural biology has generated vast amounts of data, effectively enabling accurate structural prediction by computational methods. However, structures are often obtained heterologously under homogeneous states in vitro. The lack of native heterogeneity under cellular context creates challenges in precisely connecting the structural data to phenotypes. Mass spectrometry (MS) based proteomics methods can profile proteome composition of complex biological samples. Most MS methods follow the "bottom-up" approach, which denatures and digests proteins into short peptide fragments for ease of detection. Coupled with chemical biology approaches, higher-order structures can be probed via incorporation of covalent labels on native proteins that are maintained at the peptide level. Alternatively, native MS follows the "top-down" approach and directly analyzes intact proteins under nondenaturing conditions. Various tandem MS activation methods can dissect the intact proteins for in-depth structural elucidation. Herein, we review recent native MS applications for characterizing heterogeneous samples, including proteins binding to mixtures of ligands, homo/hetero-complexes with varying stoichiometry, intrinsically disordered proteins with dynamic conformations, glycoprotein complexes with mixed modification states, and active membrane protein complexes in near-native membrane environments. We summarize the benefits, challenges, and ongoing developments in native MS, with the hope to demonstrate an emerging technology that complements other tools by filling the knowledge gaps in understanding molecular heterogeneity of proteins. This article is protected by copyright. All rights reserved.

Identification of Plant-Derived Bioactive Compounds Using Affinity Mass Spectrometry and Molecular Networking

Affinity selection-mass spectrometry (AS-MS) is a label-free binding assay system that uses UHPLC-MS size-based separation methods to separate target-compound complexes from unbound compounds, identify bound compounds, classify compound binding sites, quantify the dissociation rate constant of compounds, and characterize affinity-extracted ligands. This label-free binding assay, in contrast to conventional biochemical (i.e., high-throughput screening (HTS)) approaches, is applicable to any drug target, and is also concise, accurate, and adaptable. Although AS-MS is an innovative approach for identifying lead compounds, the possibilities of finding bioactive compounds are limited by competitive binding, which occurs during the equilibration of extracts with the target protein(s). Here, we discuss the potential for metabolite profiling complemented with molecular networking to be used alongside AS-MS to improve the identification of bioactive compounds in plant extracts. AS-MS has gained significant prominence in HTS labs and shows potential to emerge as the driving force behind novel drug development in the future.