PRECOG: PREdicting COupling probabilities of G-protein coupled receptors

Reduced Protein Stability of 11 Pathogenic Missense STXBP1/MUNC18-1 Variants and Improved Disease Prediction

BACKGROUND

Pathogenic variants in STXBP1/MUNC18-1 cause severe encephalopathies that are among the most common in genetic neurodevelopmental disorders. Different molecular disease mechanisms have been proposed, and pathogenicity prediction is limited. In this study, we aimed to define a generalized disease concept for STXBP1-related disorders and improve prediction.

METHODS

A cohort of 11 disease-associated and 5 neutral variants (detected in healthy individuals) were tested in 3 cell-free assays and in heterologous cells and primary neurons. Protein aggregation was tested using gel filtration and Triton X-100 insolubility. PRESR (predicting STXBP1-related disorder), a machine learning algorithm that uses both sequence- and 3-dimensional structure-based features, was developed to improve pathogenicity prediction using 231 known disease-associated variants and comparison to our experimental data.

RESULTS

Disease-associated variants, but none of the neutral variants, produced reduced protein levels. Cell-free assays demonstrated directly that disease-associated variants have reduced thermostability, with most variants denaturing around body temperature. In addition, most disease-associated variants impaired SNARE-mediated membrane fusion in a reconstituted assay. Aggregation/insolubility was observed for none of the variants in vitro or in neurons. PRESR outperformed existing tools substantially: Matthews correlation coefficient = 0.71 versus <0.55.

CONCLUSIONS

These data establish intrinsic protein instability as the generalizable, primary cause for STXBP1-related disorders and show that protein-specific ortholog and 3-dimensional information improve disease prediction. PRESR is a publicly available diagnostic tool.

The landscape of cancer-rewired GPCR signaling axes

We explored the dysregulation of G-protein-coupled receptor (GPCR) ligand systems in cancer transcriptomics datasets to uncover new therapeutics opportunities in oncology. We derived an interaction network of receptors with ligands and their biosynthetic enzymes. Multiple GPCRs are differentially regulated together with their upstream partners across cancer subtypes and are associated to specific transcriptional programs and to patient survival patterns. The expression of both receptor-ligand (or enzymes) partners improved patient stratification, suggesting a synergistic role for the activation of GPCR networks in modulating cancer phenotypes. Remarkably, we identified many such axes across several cancer molecular subtypes, including many involving receptor-biosynthetic enzymes for neurotransmitters. We found that GPCRs from these actionable axes, including, e.g., muscarinic, adenosine, 5-hydroxytryptamine, and chemokine receptors, are the targets of multiple drugs displaying anti-growth effects in large-scale, cancer cell drug screens, which we further validated. We have made the results generated in this study freely available through a webapp (gpcrcanceraxes.bioinfolab.sns.it).

AI-driven GPCR analysis, engineering, and targeting

This article investigates the role of recent advances in Artificial Intelligence (AI) to revolutionise the study of G protein-coupled receptors (GPCRs). AI has been applied to many areas of GPCR research, including the application of machine learning (ML) in GPCR classification, prediction of GPCR activation levels, modelling GPCR 3D structures and interactions, understanding G-protein selectivity, aiding elucidation of GPCRs structures, and drug design. Despite progress, challenges in predicting GPCR structures and addressing the complex nature of GPCRs remain, providing avenues for future research and development.

The landscape of cancer rewired GPCR signaling axes

We explored the dysregulation of GPCR ligand signaling systems in cancer transcriptomics datasets to uncover new therapeutics opportunities in oncology. We derived an interaction network of receptors with ligands and their biosynthetic enzymes, which revealed that multiple GPCRs are differentially regulated together with their upstream partners across cancer subtypes. We showed that biosynthetic pathway enrichment from enzyme expression recapitulated pathway activity signatures from metabolomics datasets, providing valuable surrogate information for GPCRs responding to organic ligands. We found that several GPCRs signaling components were significantly associated with patient survival in a cancer type-specific fashion. The expression of both receptor-ligand (or enzymes) partners improved patient stratification, suggesting a synergistic role for the activation of GPCR networks in modulating cancer phenotypes. Remarkably, we identified many such axes across several cancer molecular subtypes, including many pairs involving receptor-biosynthetic enzymes for neurotransmitters. We found that GPCRs from these actionable axes, including e.g., muscarinic, adenosine, 5-hydroxytryptamine and chemokine receptors, are the targets of multiple drugs displaying anti-growth effects in large-scale, cancer cell drug screens. We have made the results generated in this study freely available through a webapp (gpcrcanceraxes.bioinfolab.sns.it).

The GPCR-Gαs-PKA signaling axis promotes T cell dysfunction and cancer immunotherapy failure

Immune checkpoint blockade (ICB) targeting PD-1 and CTLA-4 has revolutionized cancer treatment. However, many cancers do not respond to ICB, prompting the search for additional strategies to achieve durable responses. G-protein-coupled receptors (GPCRs) are the most intensively studied drug targets but are underexplored in immuno-oncology. Here, we cross-integrated large singe-cell RNA-sequencing datasets from CD8+ T cells covering 19 distinct cancer types and identified an enrichment of Gαs-coupled GPCRs on exhausted CD8+ T cells. These include EP2, EP4, A2AR, β1AR and β2AR, all of which promote T cell dysfunction. We also developed transgenic mice expressing a chemogenetic CD8-restricted Gαs-DREADD to activate CD8-restricted Gαs signaling and show that a Gαs-PKA signaling axis promotes CD8+ T cell dysfunction and immunotherapy failure. These data indicate that Gαs-GPCRs are druggable immune checkpoints that might be targeted to enhance the response to ICB immunotherapies.

GPCRome-wide analysis of G-protein-coupling diversity using a computational biology approach

GPCRs are master regulators of cell signaling by transducing extracellular stimuli into the cell via selective coupling to intracellular G-proteins. Here we present a computational analysis of the structural determinants of G-protein-coupling repertoire of experimental and predicted 3D GPCR-G-protein complexes. Interface contact analysis recapitulates structural hallmarks associated with G-protein-coupling specificity, including TM5, TM6 and ICLs. We employ interface contacts as fingerprints to cluster G_s vs G_i complexes in an unsupervised fashion, suggesting that interface residues contribute to selective coupling. We experimentally confirm on a promiscuous receptor (CCKAR) that mutations of some of these specificity-determining positions bias the coupling selectivity. Interestingly, G_s-GPCR complexes have more conserved interfaces, while G_i/o proteins adopt a wider number of alternative docking poses, as assessed via structural alignments of representative 3D complexes. Binding energy calculations demonstrate that distinct structural properties of the complexes are associated to higher stability of G_s than G_i/o complexes. AlphaFold2 predictions of experimental binary complexes confirm several of these structural features and allow us to augment the structural coverage of poorly characterized complexes such as G_12/13.

Multi-omics approach to identifying isoform variants as therapeutic targets in cancer patients

Cancer-specific alternatively spliced events (ASE) play a role in cancer pathogenesis and can be targeted by immunotherapy, oligonucleotide therapy, and small molecule inhibition. However, identifying actionable ASE targets remains challenging due to the uncertainty of its protein product, structure impact, and proteoform (protein isoform) function. Here we argue that an integrated multi-omics profiling strategy can overcome these challenges, allowing us to mine this untapped source of targets for therapeutic development. In this review, we will provide an overview of current multi-omics strategies in characterizing ASEs by utilizing the transcriptome, proteome, and state-of-art algorithms for protein structure prediction. We will discuss limitations and knowledge gaps associated with each technology and informatics analytics. Finally, we will discuss future directions that will enable the full integration of multi-omics data for ASE target discovery.

Keratinocyte-derived defensins activate neutrophil-specific receptors Mrgpra2a/b to prevent skin dysbiosis and bacterial infection

Healthy skin maintains a diverse microbiome and a potent immune system to fight off infections. Here, we discovered that the epithelial-cell-derived antimicrobial peptides defensins activated orphan G-protein-coupled receptors (GPCRs) Mrgpra2a/b on neutrophils. This signaling axis was required for effective neutrophil-mediated skin immunity and microbiome homeostasis. We generated mutant mouse lines lacking the entire Defensin (Def) gene cluster in keratinocytes or Mrgpra2a/b. Def and Mrgpra2 mutant animals both exhibited skin dysbiosis, with reduced microbial diversity and expansion of Staphylococcus species. Defensins and Mrgpra2 were critical for combating S. aureus infections and the formation of neutrophil abscesses, a hallmark of antibacterial immunity. Activation of Mrgpra2 by defensin triggered neutrophil release of IL-1β and CXCL2 which are vital for proper amplification and propagation of the antibacterial immune response. This study demonstrated the importance of epithelial-neutrophil signaling via the defensin-Mrgpra2 axis in maintaining healthy skin ecology and promoting antibacterial host defense.

What Makes GPCRs from Different Families Bind to the Same Ligand?

G protein-coupled receptors (GPCRs) are the largest class of cell-surface receptor proteins with important functions in signal transduction and often serve as therapeutic drug targets. With the rapidly growing public data on three dimensional (3D) structures of GPCRs and GPCR-ligand interactions, computational prediction of GPCR ligand binding becomes a convincing option to high throughput screening and other experimental approaches during the beginning phases of ligand discovery. In this work, we set out to computationally uncover and understand the binding of a single ligand to GPCRs from several different families. Three-dimensional structural comparisons of the GPCRs that bind to the same ligand revealed local 3D structural similarities and often these regions overlap with locations of binding pockets. These pockets were found to be similar (based on backbone geometry and side-chain orientation using APoc), and they correlate positively with electrostatic properties of the pockets. Moreover, the more similar the pockets, the more likely a ligand binding to the pockets will interact with similar residues, have similar conformations, and produce similar binding affinities across the pockets. These findings can be exploited to improve protein function inference, drug repurposing and drug toxicity prediction, and accelerate the development of new drugs.

CCR6 activation links innate immune responses to mucosa-associated lymphoid tissue lymphoma development

The genesis of extranodal marginal zone lymphoma of mucosa-associated lymphoid tissue (MALT) is driven by oncogenic co-operation among immunological stimulations and acquired genetic changes. We previously identified recurrent CCR6 mutations in MALT lymphoma, with majority predicted to result in truncated proteins lacking the phosphorylation motif important for receptor desensitization. Functional consequences of these mutational changes, the molecular mechanisms of CCR6 activation and how this receptor signaling contributes to MALT lymphoma development remain to be investigated. In the present study, we demonstrated that these mutations impaired CCR6 receptor internalization and were activating changes, being more potent in apoptosis resistance, malignant transformation, migration and intracellular signaling, particularly in the presence of the ligands CCL20, HBD2 (human b defensin 2) and HD5 (human a defensin 5). CCR6 was highly expressed in malignant B cells irrespective of the lymphoma sites. HBD2 and CCL20 were constitutively expressed by the duct epithelial cells of salivary glands, and also those involved in lymphoepithelial lesions (LEL) in salivary gland MALT lymphoma. While in the gastric setting, HBD2, and HD5, to a less extent CCL20, were highly expressed in epithelial cells of pyloric and intestinal metaplasia respectively including those involved in LEL, which are adaptive responses to chronic Helicobacter pylori infection. These findings suggest that CCR6 signaling is most likely active in MALT lymphoma, independent of its mutation status. The observations explain why the emergence of malignant B cells and their clonal expansion in MALT lymphoma are typically around LEL, linking the innate immune responses to lymphoma genesis.

PRECOGx: exploring GPCR signaling mechanisms with deep protein representations

In this study we show that protein language models can encode structural and functional information of GPCR sequences that can be used to predict their signaling and functional repertoire. We used the ESM1b protein embeddings as features and the binding information known from publicly available studies to develop PRECOGx, a machine learning predictor to explore GPCR interactions with G protein and β-arrestin, which we made available through a new webserver (https://precogx.bioinfolab.sns.it/). PRECOGx outperformed its predecessor (e.g. PRECOG) in predicting GPCR-transducer couplings, being also able to consider all GPCR classes. The webserver also provides new functionalities, such as the projection of input sequences on a low-dimensional space describing essential features of the human GPCRome, which is used as a reference to track GPCR variants. Additionally, it allows inspection of the sequence and structural determinants responsible for coupling via the analysis of the most important attention maps used by the models as well as through predicted intramolecular contacts. We demonstrate applications of PRECOGx by predicting the impact of disease variants (ClinVar) and alternative splice forms from healthy tissues (GTEX) of human GPCRs, revealing the power to dissect system biasing mechanisms in both health and disease.

Agonist-Dependent Coupling of the Promiscuous Adenosine A2B Receptor to Gα Protein Subunits

The adenosine A_2B receptor (A_2BAR) belongs to the rhodopsin-like G protein-coupled receptor (GPCR) family. It is upregulated under hypoxic conditions, in inflammation and cancer. Previous studies indicated the coupling of the A_2BAR to different G proteins, mainly G_s, but in some cases G_q/11 or G_i, depending on the cell type. We have now utilized novel technologies, (i) heterologous expression of individual members of the Gα_q/11 protein family (Gα_q, Gα₁₁, Gα₁₄, and Gα₁₅) in Gα_q/11 knockout cells, and (ii) the TRUPATH platform, allowing the direct observation of Gα protein activation for each of the Gα subunits by bioluminescence resonance energy transfer (BRET) measurements. Three structurally diverse A_2BAR agonists were studied: the cognate agonist adenosine, its metabolically stable analog NECA, and the non-nucleosidic partial agonist BAY 60-6583. Adenosine and NECA activated most members of all four Gα protein families (Gα_s, Gα_q/11, Gα_i, and Gα_12/13). Significant differences in potencies and efficacies were observed; the highest efficacies were determined at the Gα₁₅, Gα_s, and Gα₁₂ proteins, and for NECA additionally at the Gα_i2 protein. In contrast, the partial agonist BAY 60-6583 only activated Gα₁₅, Gα_s, and Gα₁₂ proteins. Adenosine deaminase, an allosteric modulator of ARs, selectively increased the potency and efficacy of NECA and BAY 60-6583 at the Gα₁₅ protein, while it had no effect or decreased efficacy at the other Gα proteins. We conclude that the A_2BAR is preferably coupled to the Gα₁₅, Gα_s, and Gα₁₂ proteins. Upon upregulation of receptor or Gα protein expression, coupling to further Gα proteins likely occurs. Importantly, different agonists can display different activation profiles.

The G protein database, GproteinDb

Two-thirds of signaling substances, several sensory stimuli and over one-third of drugs act via receptors coupling to G proteins. Here, we present an online platform for G protein research with reference data and tools for analysis, visualization and design of scientific studies across disciplines and areas. This platform may help translate new pharmacological, structural and genomic data into insights on G protein signaling vital for human physiology and medicine. The G protein database is accessible at https://gproteindb.org.

GPR34 activation potentially bridges lymphoepithelial lesion to genesis of salivary gland MALT lymphoma

GPR34 translocation and mutation are specifically associated with salivary gland MALT lymphoma (SG-MALT-Lymphoma). Majority of GPR34 mutations are clustered in its C-terminus, resulting in truncated proteins lacking the phosphorylation motif important for receptor desensitization. It is unclear why GPR34 genetic changes associate with SG-MALT-Lymphoma and how these mutations contribute to the lymphoma development. We generated isogenic Flp-InTRex293 cell lines that stably expressed a single copy of GPR34 or its various mutants, and performed a range of in vitro assays. We showed that the GPR34 Q340X truncation, but not R84H and D151A mutants conferred a significantly increased resistance to apoptosis, and greater transforming potential than the GPR34 wild type. The GPR34 truncation mutant had a significantly delayed internalization than the wild type following ligand (lysophosphatidylserine) stimulation. Among 9 signaling pathways examined, the GPR34 Q340X truncation, to a lesser extent the D151A mutant, significantly activated CRE, NFkB and AP1 reporter activities, particularly in the presence of ligand stimulation. We further demonstrated enhanced activities of phospholipase-A1/2 in the culture supernatant of Flp-InTRex293 cells that expressed the GPR34 Q340X mutant, and their potential to catalyze the synthesis of lysophosphatidylserine from phosphatidylserine. Importantly, phospholipase-A1 was abundantly expressed in the duct epithelium of salivary glands and those involved in lymphoepithelial lesions (LELs). Our findings advocate a model of paracrine stimulation of malignant B-cells via GPR34, in which PLA is released by LELs, and hydrolyzes the phosphatidylserine exposed on apoptotic cells, generating lysophosphatidylserine, the ligand for GPR34. Thus, GPR34 activation potentially bridges LELs to genesis of SG-MALT-Lymphoma.

Structural dynamics bridge the gap between the genetic and functional levels of GPCRs

G protein-coupled receptors (GPCRs) are implicated in nearly all physiological processes in the human body and represent an important drug targeting class. The genes encoding the different GPCR (sub)types determine their specific functionality, which can be altered by natural genetic variants and isoforms. Deciphering the molecular link between sequence diversity and its functional consequences is a current challenge and critical for the comprehension of the physiological response of GPCRs. It requires a global understanding of how protein sequence translates into protein structure, how this impacts the structural motions of the protein, and, finally, how all these factors determine the receptor functionality. Here, we discuss available resources and state-of-the-art computational approaches to address this question.

The N-terminus of GPR37L1 is proteolytically processed by matrix metalloproteases

GPR37L1 is an orphan G protein-coupled receptor expressed exclusively in the brain and linked to seizures, neuroprotection and cardiovascular disease. Based upon the observation that fragments of the GPR37L1 N-terminus are found in human cerebrospinal fluid, we hypothesized that GPR37L1 was subject to post-translational modification. Heterologous expression of GPR37L1-eYFP in either HEK293 or U87 glioblastoma cells yielded two cell surface species of approximately equivalent abundance, the larger of which is N-glycosylated at Asn¹⁰⁵. The smaller species is produced by matrix metalloprotease/ADAM-mediated proteolysis (shown by the use of pharmacological inhibitors) and has a molecular weight identical to that of a mutant lacking the entire N-terminus, Δ122 GPR37L1. Serial truncation of the N-terminus prevented GPR37L1 expression except when the entire N-terminus was removed, narrowing the predicted site of N-terminal proteolysis to residues 105–122. Using yeast expressing different G protein chimeras, we found that wild type GPR37L1, but not Δ122 GPR37L1, coupled constitutively to Gpa1/Gαs and Gpa1/Gα16 chimeras, in contrast to previous studies. We tested the peptides identified in cerebrospinal fluid as well as their putative newly-generated N-terminal ‘tethered’ counterparts in both wild type and Δ122 GPR37L1 Gpa1/Gαs strains but saw no effect, suggesting that GPR37L1 does not signal in a manner akin to the protease-activated receptor family. We also saw no evidence of receptor activation or regulation by the reported GPR37L1 ligand, prosaptide/TX14A. Finally, the proteolytically processed species predominated both in vivo and ex vivo in organotypic cerebellar slice preparations, suggesting that GPR37L1 is rapidly processed to a signaling-inactive form. Our data indicate that the function of GPR37L1 in vivo is tightly regulated by metalloprotease-dependent N-terminal cleavage.