Generation of a Deep Mouse Brain Spectral Library for Transmembrane Proteome Profiling in Mental Disease Models.

Transmembrane (TM) proteins constitute over 30% of the mammalian proteome and play essential roles in mediating cell-cell communication, synaptic transmission, and plasticity in the central nervous system. Many of these proteins, especially the G protein-coupled receptors (GPCRs), are validated or candidate drug targets for therapeutic development for mental diseases, yet their expression profiles are underrepresented in most global proteomic studies. Herein, we establish a brain TM protein-enriched spectral library based on 136 data-dependent acquisition runs acquired from various brain regions of both naïve mice and mental disease models. This spectral library comprises 3043 TM proteins including 171 GPCRs, 231 ion channels, and 598 transporters. Leveraging this library, we analyzed the data-independent acquisition data from different brain regions of two mouse models exhibiting depression- or anxiety-like behaviors. By integrating multiple informatics workflows and library sources, our study significantly expanded the mental stress-perturbed TM proteome landscape, from which a new GPCR regulator of depression was verified by in vivo pharmacological testing. In summary, we provide a high-quality mouse brain TM protein spectral library to largely increase the TM proteome coverage in specific brain regions, which would catalyze the discovery of new potential drug targets for the treatment of mental disorders.

Acquisition and Analysis of DIA-Based Proteomic Data: A Comprehensive Survey in 2023.

Data-independent acquisition (DIA) mass spectrometry (MS) has emerged as a powerful technology for high-throughput, accurate, and reproducible quantitative proteomics. This review provides a comprehensive overview of recent advances in both the experimental and computational methods for DIA proteomics, from data acquisition schemes to analysis strategies and software tools. DIA acquisition schemes are categorized based on the design of precursor isolation windows, highlighting wide-window, overlapping-window, narrow-window, scanning quadrupole-based, and parallel accumulation-serial fragmentation-enhanced DIA methods. For DIA data analysis, major strategies are classified into spectrum reconstruction, sequence-based search, library-based search, de novo sequencing, and sequencing-independent approaches. A wide array of software tools implementing these strategies are reviewed, with details on their overall workflows and scoring approaches at different steps. The generation and optimization of spectral libraries, which are critical resources for DIA analysis, are also discussed. Publicly available benchmark datasets covering global proteomics and phosphoproteomics are summarized to facilitate performance evaluation of various software tools and analysis workflows. Continued advances and synergistic developments of versatile components in DIA workflows are expected to further enhance the power of DIA-based proteomics.

Identification of Spiro[chromene-2,4'-piperidine]s as Potent, Selective, and Gq-Biased 5-HT2C Receptor Partial Agonists.

A series of spiropiperidines was designed and synthesized by structural modifications based on our previous lead compound 1 and evaluated with cellular signaling assays for the discovery of 5-HT2C receptor (5-HT2CR) selective agonists with a Gq bias. Structure-activity relationship (SAR) studies of spiropiperidines uncovered spiro[chromene-2,4'-piperidine]s as a novel chemotype of 5-HT2CR selective agonists. Among this new series, the 7-chloro analogue 8 was identified as the most potent and selective 5-HT2CR partial agonist (Emax = 71.09%) with an EC50 value of 121.5 nM and no observed activity toward 5-HT2AR or 5-HT2BR. Moreover, compound 8 exhibited no recruitment activity for ß-arrestin and showed low inhibition of hERG at 10 µM. These findings may pave the way to develop more potent Gq-biased 5-HT2CR partial agonists as useful pharmacological tool compounds or potential drug candidates.

Conformational Dynamics of the Activated GLP-1 Receptor-Gs Complex Revealed by Cross-Linking Mass Spectrometry and Integrative Structure Modeling.

Despite advances in characterizing the structures and functions of G protein-coupled receptors (GPCRs), our understanding of GPCR activation and signaling is still limited by the lack of information on conformational dynamics. It is particularly challenging to study the dynamics of GPCR complexes with their signaling partners because of their transient nature and low stability. Here, by combining cross-linking mass spectrometry (CLMS) with integrative structure modeling, we map the conformational ensemble of an activated GPCR-G protein complex at near-atomic resolution. The integrative structures describe heterogeneous conformations for a high number of potential alternative active states of the GLP-1 receptor-Gs complex. These structures show marked differences from the previously determined cryo-EM structure, especially at the receptor-Gs interface and in the interior of the Gs heterotrimer. Alanine-scanning mutagenesis coupled with pharmacological assays validates the functional significance of 24 interface residue contacts only observed in the integrative structures, yet absent in the cryo-EM structure. Through the integration of spatial connectivity data from CLMS with structure modeling, our study provides a new approach that is generalizable to characterizing the conformational dynamics of GPCR signaling complexes.

Affinity selection of double-click triazole libraries for rapid discovery of allosteric modulators for GLP-1 receptor.

The recently developed double-click reaction sequence [G. Meng et al., Nature 574, 86-89 (2019)] is expected to vastly expand the number and diversity of synthetically accessible 1,2,3-triazole derivatives. However, it remains elusive how to rapidly navigate the extensive chemical space created by double-click chemistry for bioactive compound discovery. In this study, we selected a particularly challenging drug target, the glucagon-like-peptide-1 receptor (GLP-1R), to benchmark our new platform for the design, synthesis, and screening of double-click triazole libraries. First, we achieved a streamlined synthesis of customized triazole libraries on an unprecedented scale (composed of 38,400 new compounds). By interfacing affinity-selection mass spectrometry and functional assays, we identified a series of positive allosteric modulators (PAMs) with unreported scaffolds that can selectively and robustly enhance the signaling activity of the endogenous GLP-1(9-36) peptide. Intriguingly, we further revealed an unexpected binding mode of new PAMs which likely act as a molecular glue between the receptor and the peptide agonist. We anticipate the merger of double-click library synthesis with the hybrid screening platform allows for efficient and economic discovery of drug candidates or chemical probes for various therapeutic targets.

Benchmarking commonly used software suites and analysis workflows for DIA proteomics and phosphoproteomics.

A plethora of software suites and multiple classes of spectral libraries have been developed to enhance the depth and robustness of data-independent acquisition (DIA) data processing. However, how the combination of a DIA software tool and a spectral library impacts the outcome of DIA proteomics and phosphoproteomics data analysis has been rarely investigated using benchmark data that mimics biological complexity. In this study, we create DIA benchmark data sets simulating the regulation of thousands of proteins in a complex background, which are collected on both an Orbitrap and a timsTOF instruments. We evaluate four commonly used software suites (DIA-NN, Spectronaut, MaxDIA and Skyline) combined with seven different spectral libraries in global proteome analysis. Moreover, we assess their performances in analyzing phosphopeptide standards and TNF-α-induced phosphoproteome regulation. Our study provides a practical guidance on how to construct a robust data analysis pipeline for different proteomics studies implementing the DIA technique.

Nanobodies and chemical cross-links advance the structural and functional analysis of PI3Kα.

Nanobodies and chemical cross-linking were used to gain information on the identity and positions of flexible domains of PI3Kα. The application of chemical cross-linking mass spectrometry (CXMS) facilitated the identification of the p85 domains BH, cSH2, and SH3 as well as their docking positions on the PI3Kα catalytic core. Binding of individual nanobodies to PI3Kα induced activation or inhibition of enzyme activity and caused conformational changes that could be correlated with enzyme function. Binding of nanobody Nb3-126 to the BH domain of p85α substantially improved resolution for parts of the PI3Kα complex, and binding of nanobody Nb3-159 induced a conformation of PI3Kα that is distinct from known PI3Kα structures. The analysis of CXMS data also provided mechanistic insights into the molecular underpinning of the flexibility of PI3Kα.

Structural optimizations and bioevaluation of N-H aporphine analogues as Gq-biased and selective serotonin 5-HT2C receptor agonists.

The concept of subtype selectivity and functional bias has recently reshaped current GPCR drug discovery for G protein-coupled receptors. A series of new N-H aporphines with A-ring modifications have been synthesized, and their efficacy on 5-HT2 receptor activation was evaluated. SAR analysis led to the discovery of several more potent and selective 5-HT2C receptor agonists (e.g., 11b and 11f) with low nanomolar activity. Molecular docking analysis of this series of aporphines was in accordance with our SAR results. The functional selectivity of specific compounds was tested via both Gq-mediated calcium flux and ß-arrestin recruitment assays, which revealed that these compounds exhibited no ß-arrestin recruitment activity. Further ADMET study combined with behavioral assessment using a methamphetamine-induced hyperactivity model identified compound 11b and 11f possessing promising drug-like profiles and having antipsychotic potential. These agonists with an exclusive bias toward Gq signaling may serve as valuable pharmacological probes to facilitate the elucidation of therapeutically relevant 5-HT2C signaling pathways and the development of alternative antipsychotic medications.

Structural basis of tethered agonism of the adhesion GPCRs ADGRD1 and ADGRF1.

Adhesion G protein-coupled receptors (aGPCRs) are essential for a variety of physiological processes such as immune responses, organ development, cellular communication, proliferation and homeostasis1-7. An intrinsic manner of activation that involves a tethered agonist in the N-terminal region of the receptor has been proposed for the aGPCRs8,9, but its molecular mechanism remains elusive. Here we report the G protein-bound structures of ADGRD1 and ADGRF1, which exhibit many unique features with regard to the tethered agonism. The stalk region that proceeds the first transmembrane helix acts as the tethered agonist by forming extensive interactions with the transmembrane domain; these interactions are mostly conserved in ADGRD1 and ADGRF1, suggesting that a common stalk-transmembrane domain interaction pattern is shared by members of the aGPCR family. A similar stalk binding mode is observed in the structure of autoproteolysis-deficient ADGRF1, supporting a cleavage-independent manner of receptor activation. The stalk-induced activation is facilitated by a cascade of inter-helix interaction cores that are conserved in positions but show sequence variability in these two aGPCRs. Furthermore, the intracellular region of ADGRF1 contains a specific lipid-binding site, which proves to be functionally important and may serve as the recognition site for the previously discovered endogenous ADGRF1 ligand synaptamide. These findings highlight the diversity and complexity of the signal transduction mechanisms of the aGPCRs.

Post-Translational Modifications of G Protein-Coupled Receptors Revealed by Proteomics and Structural Biology.

G protein-coupled receptors (GPCRs) are a protein superfamily comprising >800 members that regulate numerous cellular and physiologic responses. GPCRs represent the largest class of therapeutic targets with implications in various diseases. Although advances in GPCR structural and pharmacological research have significantly improved our knowledge of GPCR signaling mechanisms, mapping diverse post-translational modifications (PTMs) of GPCR proteins and understanding their regulatory roles have received much less attention. Mass spectrometry-based proteomics has become the most popular technology for profiling protein PTMs in a systematic manner. Herein we provide an overview of PTM types, locations, crosstalk and dynamic regulation for different GPCRs that are characterized using proteomic and/or biochemical approaches. Our main focus is on glycosylation, phosphorylation, ubiquitination and palmitoylation that are known to modulate receptor folding, biosynthesis, trafficking, dimerization and signaling. Furthermore, we discuss the locations of specific PTM sites in the structure of a given GPCR and its signaling complex to highlight the importance of PTM regulation in the molecular basis of GPCRs, which may shed new light on structure-based drug discovery.

DeepPhospho accelerates DIA phosphoproteome profiling through in silico library generation.

Phosphoproteomics integrating data-independent acquisition (DIA) enables deep phosphoproteome profiling with improved quantification reproducibility and accuracy compared to data-dependent acquisition (DDA)-based phosphoproteomics. DIA data mining heavily relies on a spectral library that in most cases is built on DDA analysis of the same sample. Construction of this project-specific DDA library impairs the analytical throughput, limits the proteome coverage, and increases the sample size for DIA phosphoproteomics. Herein we introduce a deep neural network, DeepPhospho, which conceptually differs from previous deep learning models to achieve accurate predictions of LC-MS/MS data for phosphopeptides. By leveraging in silico libraries generated by DeepPhospho, we establish a DIA workflow for phosphoproteome profiling which involves DIA data acquisition and data mining with DeepPhospho predicted libraries, thus circumventing the need of DDA library construction. Our DeepPhospho-empowered workflow substantially expands the phosphoproteome coverage while maintaining high quantification performance, which leads to the discovery of more signaling pathways and regulated kinases in an EGF signaling study than the DDA library-based approach. DeepPhospho is provided as a web server as well as an offline app to facilitate user access to model training, predictions and library generation.

Discovery of Novel Allosteric Modulators Targeting an Extra-Helical Binding Site of GLP-1R Using Structure- and Ligand-Based Virtual Screening.

Allosteric modulators have emerged with many potential pharmacological advantages as they do not compete the binding of agonist or antagonist to the orthosteric sites but ultimately affect downstream signaling. To identify allosteric modulators targeting an extra-helical binding site of the glucagon-like peptide-1 receptor (GLP-1R) within the membrane environment, the following two computational approaches were applied: structure-based virtual screening with consideration of lipid contacts and ligand-based virtual screening with the maintenance of specific allosteric pocket residue interactions. Verified by radiolabeled ligand binding and cAMP accumulation experiments, two negative allosteric modulators and seven positive allosteric modulators were discovered using structure-based and ligand-based virtual screening methods, respectively. The computational approach presented here could possibly be used to discover allosteric modulators of other G protein-coupled receptors.

Multiregional profiling of the brain transmembrane proteome uncovers novel regulators of depression.

Transmembrane proteins play vital roles in mediating synaptic transmission, plasticity, and homeostasis in the brain. However, these proteins, especially the G protein-coupled receptors (GPCRs), are underrepresented in most large-scale proteomic surveys. Here, we present a new proteomic approach aided by deep learning models for comprehensive profiling of transmembrane protein families in multiple mouse brain regions. Our multiregional proteome profiling highlights the considerable discrepancy between messenger RNA and protein distribution, especially for region-enriched GPCRs, and predicts an endogenous GPCR interaction network in the brain. Furthermore, our new approach reveals the transmembrane proteome remodeling landscape in the brain of a mouse depression model, which led to the identification of two previously unknown GPCR regulators of depressive-like behaviors. Our study provides an enabling technology and rich data resource to expand the understanding of transmembrane proteome organization and dynamics in the brain and accelerate the discovery of potential therapeutic targets for depression treatment.

Affinity Mass Spectrometry-Based Fragment Screening Identified a New Negative Allosteric Modulator of the Adenosine A2A Receptor Targeting the Sodium Ion Pocket.

Allosteric ligands provide new opportunities to modulate G protein-coupled receptor (GPCR) function and present therapeutic benefits over orthosteric molecules. Negative allosteric modulators (NAMs) can inhibit the activation of a receptor and downstream signal transduction. Screening NAMs for a GPCR target is particularly challenging because of the difficulty in distinguishing NAMs from antagonists bound to the orthosteric site as they both show inhibitory effects in receptor signaling assays. Here we report an affinity mass spectrometry (MS)-based approach tailored to screening potential NAMs of a GPCR target especially from fragment libraries. Compared to regular surface plasmon resonance or NMR-based methods for fragment screening, our approach features a reduction of the protein and compound consumption by 2-4 orders of magnitude and an increase in the data acquisition speed by 2-3 orders of magnitude. Our affinity MS-based fragment screening led to the identification of a new NAM of the adenosine A2A receptor (A2AAR) bearing an unprecedented azetidine moiety predicted to occupy the allosteric sodium binding site. Molecular dynamics simulations, ligand structure-activity relationship (SAR) studies, and in-solution NMR analyses further revealed the unique binding mode and antagonistic property of this compound that differs considerably from HMA (5-(N,N-hexamethylene)amiloride), a well-characterized NAM of A2AAR. Taken together, our work would facilitate fragment-based screening of allosteric modulators, as well as guide the design of novel NAMs acting at the sodium ion pocket of class A GPCRs.

G protein-coupled receptors: structure- and function-based drug discovery.

As one of the most successful therapeutic target families, G protein-coupled receptors (GPCRs) have experienced a transformation from random ligand screening to knowledge-driven drug design. We are eye-witnessing tremendous progresses made recently in the understanding of their structure-function relationships that facilitated drug development at an unprecedented pace. This article intends to provide a comprehensive overview of this important field to a broader readership that shares some common interests in drug discovery.

Targeted Proteomics Combined with Affinity Mass Spectrometry Analysis Reveals Antagonist E7 Acts As an Intracellular Covalent Ligand of Orphan Receptor GPR52.

The GPR52, a class A orphan G protein-coupled receptor (GPCR), is regarded as a promising therapeutic target for the treatment of Huntington's disease and multiple psychiatric disorders. Although the recently solved structure of GPR52 has revealed a binding mechanism likely shared by all reported agonists, the small molecule antagonist E7 cannot fit into this agonist-binding pocket, and its interaction mode with the receptor remains unknown. Here, we employed targeted proteomics and affinity mass spectrometry approaches to uncover a unique binding mode of E7 which acts as a covalent and allosteric ligand of GPR52. Among three Cys residues identified in this study to form covalent conjugates with E7, the intracellular C1564.40 makes the most significant contribution to the antagonism activity of E7. Discovery of this novel intracellular site for covalent attachment of an antagonist would facilitate the design of GPR52-selective negative allosteric modulators which could serve as potential therapeutics for treating Huntington's disease.

Organized cannabinoid receptor distribution in neurons revealed by super-resolution fluorescence imaging.

G-protein-coupled receptors (GPCRs) play important roles in cellular functions. However, their intracellular organization is largely unknown. Through investigation of the cannabinoid receptor 1 (CB1), we discovered periodically repeating clusters of CB1 hotspots within the axons of neurons. We observed these CB1 hotspots interact with the membrane-associated periodic skeleton (MPS) forming a complex crucial in the regulation of CB1 signaling. Furthermore, we found that CB1 hotspot periodicity increased upon CB1 agonist application, and these activated CB1 displayed less dynamic movement compared to non-activated CB1. Our results suggest that CB1 forms periodic hotspots organized by the MPS as a mechanism to increase signaling efficacy upon activation.

Correction to "A Novel G Protein-Biased and Subtype-Selective Agonist for a G Protein-Coupled Receptor Discovered from Screening Herbal Extracts".

[This corrects the article DOI: 10.1021/acscentsci.9b01125.].