Inferring molecular inhibition potency with AlphaFold predicted structures.

Even though in silico drug ligand-based methods have been successful in predicting interactions with known target proteins, they struggle with new, unassessed targets. To address this challenge, we propose an approach that integrates structural data from AlphaFold 2 predicted protein structures into machine learning models. Our method extracts 3D structural protein fingerprints and combines them with ligand structural data to train a single machine learning model. This model captures the relationship between ligand properties and the unique structural features of various target proteins, enabling predictions for never before tested molecules and protein targets. To assess our model, we used a dataset of 144 Human G-protein Coupled Receptors (GPCRs) with over 140,000 measured inhibition constants (Ki) values. Results strongly suggest that our approach performs as well as state-of-the-art ligand-based methods. In a second modeling approach that used 129 targets for training and a separate test set of 15 different protein targets, our model correctly predicted interactions for 73% of targets, with explained variances exceeding 0.50 in 22% of cases. Our findings further verified that the usage of experimentally determined protein structures produced models that were statistically indistinct from the Alphafold synthetic structures. This study presents a proteo-chemometric drug screening approach that uses a simple and scalable method for extracting protein structural information for usage in machine learning models capable of predicting protein-molecule interactions even for orphan targets.

Bitter taste receptor activation by cholesterol and an intracellular tastant.

Bitter taste sensing is mediated by type 2 taste receptors (TAS2Rs (also known as T2Rs)), which represent a distinct class of G-protein-coupled receptors1. Among the 26 members of the TAS2Rs, TAS2R14 is highly expressed in extraoral tissues and mediates the responses to more than 100 structurally diverse tastants2-6, although the molecular mechanisms for recognizing diverse chemicals and initiating cellular signalling are still poorly understood. Here we report two cryo-electron microscopy structures for TAS2R14 complexed with Ggust (also known as gustducin) and Gi1. Both structures have an orthosteric binding pocket occupied by endogenous cholesterol as well as an intracellular allosteric site bound by the bitter tastant cmpd28.1, including a direct interaction with the α5 helix of Ggust and Gi1. Computational and biochemical studies validate both ligand interactions. Our functional analysis identified cholesterol as an orthosteric agonist and the bitter tastant cmpd28.1 as a positive allosteric modulator with direct agonist activity at TAS2R14. Moreover, the orthosteric pocket is connected to the allosteric site via an elongated cavity, which has a hydrophobic core rich in aromatic residues. Our findings provide insights into the ligand recognition of bitter taste receptors and suggest activities of TAS2R14 beyond bitter taste perception via intracellular allosteric tastants.

G protein-coupled receptors (GPCRs): advances in structures, mechanisms, and drug discovery.

G protein-coupled receptors (GPCRs), the largest family of human membrane proteins and an important class of drug targets, play a role in maintaining numerous physiological processes. Agonist or antagonist, orthosteric effects or allosteric effects, and biased signaling or balanced signaling, characterize the complexity of GPCR dynamic features. In this study, we first review the structural advancements, activation mechanisms, and functional diversity of GPCRs. We then focus on GPCR drug discovery by revealing the detailed drug-target interactions and the underlying mechanisms of orthosteric drugs approved by the US Food and Drug Administration in the past five years. Particularly, an up-to-date analysis is performed on available GPCR structures complexed with synthetic small-molecule allosteric modulators to elucidate key receptor-ligand interactions and allosteric mechanisms. Finally, we highlight how the widespread GPCR-druggable allosteric sites can guide structure- or mechanism-based drug design and propose prospects of designing bitopic ligands for the future therapeutic potential of targeting this receptor family.

Predicting FFAR4 agonists using structure-based machine learning approach based on molecular fingerprints.

Free Fatty Acid Receptor 4 (FFAR4), a G-protein-coupled receptor, is responsible for triggering intracellular signaling pathways that regulate various physiological processes. FFAR4 agonists are associated with enhancing insulin release and mitigating the atherogenic, obesogenic, pro-carcinogenic, and pro-diabetogenic effects, normally associated with the free fatty acids bound to FFAR4. In this research, molecular structure-based machine-learning techniques were employed to evaluate compounds as potential agonists for FFAR4. Molecular structures were encoded into bit arrays, serving as molecular fingerprints, which were subsequently analyzed using the Bayesian network algorithm to identify patterns for screening the data. The shortlisted hits obtained via machine learning protocols were further validated by Molecular Docking and via ADME and Toxicity predictions. The shortlisted compounds were then subjected to MD Simulations of the membrane-bound FFAR4-ligand complexes for 100 ns each. Molecular analyses, encompassing binding interactions, RMSD, RMSF, RoG, PCA, and FEL, were conducted to scrutinize the protein-ligand complexes at the inter-atomic level. The analyses revealed significant interactions of the shortlisted compounds with the crucial residues of FFAR4 previously documented. FFAR4 as part of the complexes demonstrated consistent RMSDs, ranging from 3.57 to 3.64, with minimal residue fluctuations 5.27 to 6.03 nm, suggesting stable complexes. The gyration values fluctuated between 22.8 to 23.5 nm, indicating structural compactness and orderliness across the studied systems. Additionally, distinct conformational motions were observed in each complex, with energy contours shifting to broader energy basins throughout the simulation, suggesting thermodynamically stable protein-ligand complexes. The two compounds CHEMBL2012662 and CHEMBL64616 are presented as potential FFAR4 agonists, based on these insights and in-depth analyses. Collectively, these findings advance our comprehension of FFAR4's functions and mechanisms, highlighting these compounds as potential FFAR4 agonists worthy of further exploration as innovative treatments for metabolic and immune-related conditions.

GPCR-IPL score: multilevel featurization of GPCR-ligand interaction patterns and prediction of ligand functions from selectivity to biased activation.

G-protein-coupled receptors (GPCRs) mediate diverse cell signaling cascades after recognizing extracellular ligands. Despite the successful history of known GPCR drugs, a lack of mechanistic insight into GPCR challenges both the deorphanization of some GPCRs and optimization of the structure-activity relationship of their ligands. Notably, replacing a small substituent on a GPCR ligand can significantly alter extracellular GPCR-ligand interaction patterns and motion of transmembrane helices in turn to occur post-binding events of the ligand. In this study, we designed 3D multilevel features to describe the extracellular interaction patterns. Subsequently, these 3D features were utilized to predict the post-binding events that result from conformational dynamics from the extracellular to intracellular areas. To understand the adaptability of GPCR ligands, we collected the conformational information of flexible residues during binding and performed molecular featurization on a broad range of GPCR-ligand complexes. As a result, we developed GPCR-ligand interaction patterns, binding pockets, and ligand features as score (GPCR-IPL score) for predicting the functional selectivity of GPCR ligands (agonism versus antagonism), using the multilevel features of (1) zoomed-out 'residue level' (for flexible transmembrane helices of GPCRs), (2) zoomed-in 'pocket level' (for sophisticated mode of action) and (3) 'atom level' (for the conformational adaptability of GPCR ligands). GPCR-IPL score demonstrated reliable performance, achieving area under the receiver operating characteristic of 0.938 and area under the precision-recall curve of 0.907 (available in gpcr-ipl-score.onrender.com). Furthermore, we used the molecular features to predict the biased activation of downstream signaling (Gi/o, Gq/11, Gs and ß-arrestin) as well as the functional selectivity. The resulting models are interpreted and applied to out-of-set validation with three scenarios including the identification of a new MRGPRX antagonist.

The Molecular Theory of Sweet Taste: Revisit, Update, and Beyond.

The molecular origin of the sweet taste is still elusive. Herein, the canonical AH-B-X theory of sweet taste is extended by resurveying various sweeteners, which provides deeper insights into an analogous intramolecular connectivity pattern of both glucophores in sweeteners and their interaction counterparts in sweet taste receptor TAS1R2/TAS1R3: electrostatic complementarity and topochemical compatibility. Furthermore, their complementary interaction is elaborately illustrated, accounting for the common molecular feature of eliciting sweetness. Moreover, it highlights that multiple glucophores in a topological system synergistically mediate the elicitation and performance of sweetness. This perspective presents a meaningful framework for the structure-activity relationship-based molecular design and modification of sweeteners and sheds light on the mechanism of molecular evolution of TAS1R2s/TAS1R3s. The link between palatability of sweeteners and harmony relationships between their structural components via stereochemistry and network has significant implications to illuminate the underlying mechanisms by which nature designs chemical reactions to elicit the most important taste.

GPCR-BERT: Interpreting Sequential Design of G Protein-Coupled Receptors Using Protein Language Models.

With the rise of transformers and large language models (LLMs) in chemistry and biology, new avenues for the design and understanding of therapeutics have been opened up to the scientific community. Protein sequences can be modeled as language and can take advantage of recent advances in LLMs, specifically with the abundance of our access to the protein sequence data sets. In this letter, we developed the GPCR-BERT model for understanding the sequential design of G protein-coupled receptors (GPCRs). GPCRs are the target of over one-third of Food and Drug Administration-approved pharmaceuticals. However, there is a lack of comprehensive understanding regarding the relationship among amino acid sequence, ligand selectivity, and conformational motifs (such as NPxxY, CWxP, and E/DRY). By utilizing the pretrained protein model (Prot-Bert) and fine-tuning with prediction tasks of variations in the motifs, we were able to shed light on several relationships between residues in the binding pocket and some of the conserved motifs. To achieve this, we took advantage of attention weights and hidden states of the model that are interpreted to extract the extent of contributions of amino acids in dictating the type of masked ones. The fine-tuned models demonstrated high accuracy in predicting hidden residues within the motifs. In addition, the analysis of embedding was performed over 3D structures to elucidate the higher-order interactions within the conformations of the receptors.

Heterotrimeric G protein signaling without GPCRs: The Gα-binding-and-activating (GBA) motif.

Heterotrimeric G proteins (Gαßγ) are molecular switches that relay signals from 7-transmembrane receptors located at the cell surface to the cytoplasm. The function of these receptors is so intimately linked to heterotrimeric G proteins that they are named G protein-coupled receptors (GPCRs), showcasing the interdependent nature of this archetypical receptor-transducer axis of transmembrane signaling in eukaryotes. It is generally assumed that activation of heterotrimeric G protein signaling occurs exclusively by the action of GPCRs, but this idea has been challenged by the discovery of alternative mechanisms by which G proteins can propagate signals in the cell. This review will focus on a general principle of G protein signaling that operates without the direct involvement of GPCRs. The mechanism of G protein signaling reviewed here is mediated by a class of G protein regulators defined by containing an evolutionarily conserved sequence named the Gα-binding-and-activating (GBA) motif. Using the best characterized proteins with a GBA motif as examples, Gα-interacting vesicle-associated protein (GIV)/Girdin and dishevelled-associating protein with a high frequency of leucine residues (DAPLE), this review will cover (i) the mechanisms by which extracellular cues not relayed by GPCRs promote the coupling of GBA motif-containing regulators with G proteins, (ii) the structural and molecular basis for how GBA motifs interact with Gα subunits to facilitate signaling, (iii) the relevance of this mechanism in different cellular and pathological processes, including cancer and birth defects, and (iv) strategies to manipulate GBA-G protein coupling for experimental therapeutics purposes, including the development of rationally engineered proteins and chemical probes.

Scaling up Functional Analyses of the G Protein-Coupled Receptor Rhodopsin.

Eukaryotic cells use G protein-coupled receptors (GPCRs) to convert external stimuli into internal signals to elicit cellular responses. However, how mutations in GPCR-coding genes affect GPCR activation and downstream signaling pathways remain poorly understood. Approaches such as deep mutational scanning show promise in investigations of GPCRs, but a high-throughput method to measure rhodopsin activation has yet to be achieved. Here, we scale up a fluorescent reporter assay in budding yeast that we engineered to study rhodopsin's light-activated signal transduction. Using this approach, we measured the mutational effects of over 1200 individual human rhodopsin mutants, generated by low-frequency random mutagenesis of the GPCR rhodopsin (RHO) gene. Analysis of the data in the context of rhodopsin's three-dimensional structure reveals that transmembrane helices are generally less tolerant to mutations compared to flanking helices that face the lipid bilayer, which suggest that mutational tolerance is contingent on both the local environment surrounding specific residues and the specific position of these residues in the protein structure. Comparison of functional scores from our screen to clinically identified rhodopsin disease variants found many pathogenic mutants to be loss of function. Lastly, functional scores from our assay were consistent with a complex counterion mechanism involved in ligand-binding and rhodopsin activation. Our results demonstrate that deep mutational scanning is possible for rhodopsin activation and can be an effective method for revealing properties of mutational tolerance that may be generalizable to other transmembrane proteins.

The repertoire and structure of adhesion GPCR transcript variants assembled from publicly available deep-sequenced human samples.

Alternative splicing and multiple transcription start and termination sites can produce a diverse repertoire of mRNA transcript variants from a given gene. While the full picture of the human transcriptome is still incomplete, publicly available RNA datasets have enabled the assembly of transcripts. Using publicly available deep sequencing data from 927 human samples across 48 tissues, we quantified known and new transcript variants, provide an interactive, browser-based application Splice-O-Mat and demonstrate its relevance using adhesion G protein-coupled receptors (aGPCRs) as an example. On average, 24 different transcript variants were detected for each of the 33 human aGPCR genes, and several dominant transcript variants were not yet annotated. Variable transcription starts and complex exon-intron structures encode a flexible protein domain architecture of the N- and C termini and the seven-transmembrane helix domain (7TMD). Notably, we discovered the first GPCR (ADGRG7/GPR128) with eight transmembrane helices. Both the N- and C terminus of this aGPCR were intracellularly oriented, anchoring the N terminus in the plasma membrane. Moreover, the assessment of tissue-specific transcript variants, also for other gene classes, in our application may change the evaluation of disease-causing mutations, as their position in different transcript variants may explain tissue-specific phenotypes.

Probing Activation and Conformational Dynamics of the Vesicle-Reconstituted ß2 Adrenergic Receptor at the Single-Molecule Level.

G-protein-coupled receptors (GPCRs) are structurally flexible membrane proteins that mediate a host of physiological responses to extracellular ligands like hormones and neurotransmitters. Fine features of their dynamic structural behavior are hypothesized to encode the functional plasticity seen in GPCR activity, where ligands with different efficacies can direct the same receptor toward different signaling phenotypes. Although the number of GPCR crystal structures is increasing, the receptors are characterized by complex and poorly understood conformational landscapes. Therefore, we employed a fluorescence microscopy assay to monitor conformational dynamics of single ß2 adrenergic receptors (ß2ARs). To increase the biological relevance of our findings, we decided not to reconstitute the receptor in detergent micelles but rather lipid membranes as proteoliposomes. The conformational dynamics were monitored by changes in the intensity of an environmentally sensitive boron-dipyrromethene (BODIPY 493/503) fluorophore conjugated to an endogenous cysteine (located at the cytoplasmic end of the sixth transmembrane helix of the receptor). Using total internal reflection fluorescence microscopy (TIRFM) and a single small unilamellar liposome assay that we previously developed, we followed the real-time dynamic properties of hundreds of single ß2ARs reconstituted in a native-like environment─lipid membranes. Our results showed that ß2AR-BODIPY fluctuates between several states of different intensity on a time scale of seconds, compared to BODIPY-lipid conjugates that show almost entirely stable fluorescence emission in the absence and presence of the full agonist BI-167107. Agonist stimulation changes the ß2AR dynamics, increasing the population of states with higher intensities and prolonging their durations, consistent with bulk experiments. The transition density plot demonstrates that ß2AR-BODIPY, in the absence of the full agonist, interconverts between states of low and moderate intensity, while the full agonist renders transitions between moderate and high-intensity states more probable. This redistribution is consistent with a mechanism of conformational selection and is a promising first step toward characterizing the conformational dynamics of GPCRs embedded in a lipid bilayer.

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.

A novel biomimetic electrochemical taste-biosensor based on conformational changes of the taste receptor.

Taste sensor, a useful tool which could detect and identify thousands of different chemical substances in liquid environments, has attracted continuous concern from beverage and foodstuff industry and its consumers. Although many taste sensing methods have been extensively developed, the assessment of tastant content remains challenging due to the limitations of sensor selectivity and sensitivity. Here we present a novel biomimetic electrochemical taste-biosensor based on bioactive sensing elements and immune amplification with nanomaterials carrier to address above concerns, while taking sweet taste perception as a model. The proposed biosensor based on ligand binding domain (T1R2 VFT) of human sweet taste receptor protein showed human mimicking character and initiated the application of immune recognition in gustation biosensor, which can precisely and sensitively distinguish sweet substances against other related gustation substances with detection limit of 5.1 pM, far less than that of taste sensors without immune amplification whose detection limit was 0.48 nM. The performance test demonstrated the biosensor has the capacity of monitoring the response of sweet substances in real food environments, which is crucial in practical. This biomimetic electrochemical taste-biosensor can work as a new screening platform for newly developed tastants and disclose sweet perception mechanism.

Biased Signaling in Mutated Variants of ß2-Adrenergic Receptor: Insights from Molecular Dynamics Simulations.

The molecular basis of receptor bias in G protein-coupled receptors (GPCRs) caused by mutations that preferentially activate specific intracellular transducers over others remains poorly understood. Two experimentally identified biased variants of ß2-adrenergic receptors (ß2AR), a prototypical GPCR, are a triple mutant (T68F, Y132A, and Y219A) and a single mutant (Y219A); the former bias the receptor toward the ß-arrestin pathway by disfavoring G protein engagement, while the latter induces G protein signaling explicitly due to selection against GPCR kinases (GRKs) that phosphorylate the receptor as a prerequisite of ß-arrestin binding. Though rigorous characterizations have revealed functional implications of these mutations, the atomistic origin of the observed transducer selectivity is not clear. In this study, we investigated the allosteric mechanism of receptor bias in ß2AR using microseconds of all-atom Gaussian accelerated molecular dynamics (GaMD) simulations. Our observations reveal distinct rearrangements in transmembrane helices, intracellular loop 3, and critical residues R1313.50 and Y3267.53 in the conserved motifs D(E)RY and NPxxY for the mutant receptors, leading to their specific transducer interactions. Moreover, partial dissociation of G protein from the receptor core is observed in the simulations of the triple mutant in contrast to the single mutant and wild-type receptor. The reorganization of allosteric communications from the extracellular agonist BI-167107 to the intracellular receptor-transducer interfaces drives the conformational rearrangements responsible for receptor bias in the single and triple mutants. The molecular insights into receptor bias of ß2AR presented here could improve the understanding of biased signaling in GPCRs, potentially opening new avenues for designing novel therapeutics with fewer side-effects and superior efficacy.

Molecular basis of human trace amine-associated receptor 1 activation.

The human trace amine-associated receptor 1 (hTAAR1, hTA1) is a key regulator of monoaminergic neurotransmission and the actions of psychostimulants. Despite preclinical research demonstrating its tractability as a drug target, its molecular mechanisms of activation remain unclear. Moreover, poorly understood pharmacological differences between rodent and human TA1 complicate the translation of findings from preclinical disease models into novel pharmacotherapies. To elucidate hTA1's mechanisms on the molecular scale and investigate the underpinnings of its divergent pharmacology from rodent orthologs, we herein report the structure of the human TA1 receptor in complex with a Gαs heterotrimer. Our structure reveals shared structural elements with other TAARs, as well as with its closest monoaminergic orthologue, the serotonin receptor 5-HT4R. We further find that a single mutation dramatically shifts the selectivity of hTA1 towards that of its rodent orthologues, and report on the effects of substituting residues to those found in serotonin and dopamine receptors. Strikingly, we also discover that the atypical antipsychotic medication and pan-monoaminergic antagonist asenapine potently and efficaciously activates hTA1. Together our studies provide detailed insight into hTA1 structure and function, contrast its molecular pharmacology with that of related receptors, and uncover off-target activities of monoaminergic drugs at hTA1.

Conformational transitions and activation of the adhesion receptor CD97.

Adhesion G protein-coupled receptors (aGPCRs) are evolutionarily ancient receptors involved in a variety of physiological and pathophysiological processes. Modulators of aGPCR, particularly antagonists, hold therapeutic promise for diseases like cancer and immune and neurological disorders. Hindered by the inactive state structural information, our understanding of antagonist development and aGPCR activation faces challenges. Here, we report the cryo-electron microscopy structures of human CD97, a prototypical aGPCR that plays crucial roles in immune system, in its inactive apo and G13-bound fully active states. Compared with other family GPCRs, CD97 adopts a compact inactive conformation with a constrained ligand pocket. Activation induces significant conformational changes for both extracellular and intracellular sides, creating larger cavities for Stachel sequence binding and G13 engagement. Integrated with functional and metadynamics analyses, our study provides significant mechanistic insights into the activation and signaling of aGPCRs, paving the way for future drug discovery efforts.

Molecular insights into atypical modes of ß-arrestin interaction with seven transmembrane receptors.

ß-arrestins (ßarrs) are multifunctional proteins involved in signaling and regulation of seven transmembrane receptors (7TMRs), and their interaction is driven primarily by agonist-induced receptor activation and phosphorylation. Here, we present seven cryo-electron microscopy structures of ßarrs either in the basal state, activated by the muscarinic receptor subtype 2 (M2R) through its third intracellular loop, or activated by the ßarr-biased decoy D6 receptor (D6R). Combined with biochemical, cellular, and biophysical experiments, these structural snapshots allow the visualization of atypical engagement of ßarrs with 7TMRs and also reveal a structural transition in the carboxyl terminus of ßarr2 from a ß strand to an α helix upon activation by D6R. Our study provides previously unanticipated molecular insights into the structural and functional diversity encoded in 7TMR-ßarr complexes with direct implications for exploring novel therapeutic avenues.

An image-based Abplex method for high-throughput GPCRs antibody discovery.

As the field of antibody therapeutics advances rapidly, membrane proteins, particularly G protein-coupled receptors (GPCRs), have emerged as highly sought-after drug targets. However, the challenges associated with extracting membrane proteins have created a demand for effective antibody screening systems targeting these proteins. In this study, we propose developing an innovative antibody screening strategy (Abplex) based on high-content imaging. This approach leverages intact cells that express target membrane proteins, facilitating the presentation of proteins in their native conformation. Furthermore, it acquires both specific and non-specific binding signals in a single well, thereby bolstering the robustness of the outcomes. The technique involves just one step and can be completed within 50 min, enabling the analysis of a single sample in just one second. The amalgamation of dependable experimental findings, a simplified workflow, reduced hands-on time, and a swift analytical pace positions our method for superior throughput and precision when juxtaposed with traditional techniques such as CbELISA and FACS. Moreover, we introduce the concept of cell barcoding, wherein cells are labeled with different fluorescence spatial patterns. This feature allows for multiplexed detection to meet the needs of various experiments. The characteristics of Abplex promise to expedite GPCR-targeting antibody discovery, advance therapeutics and enable new disease treatments.

GproteinDb in 2024: new G protein-GPCR couplings, AlphaFold2-multimer models and interface interactions.

G proteins are the major signal proteins of ∼800 receptors for medicines, hormones, neurotransmitters, tastants and odorants. GproteinDb offers integrated genomic, structural, and pharmacological data and tools for analysis, visualization and experiment design. Here, we present the first major update of GproteinDb greatly expanding its coupling data and structural templates, adding AlphaFold2 structure models of GPCR-G protein complexes and advancing the interactive analysis tools for their interfaces underlying coupling selectivity. We present insights on coupling agreement across datasets and parameters, including constitutive activity, agonist-induced activity and kinetics. GproteinDb is accessible at https://gproteindb.org.

GPR101: Modeling a constitutively active receptor linked to X-linked acrogigantism.

GPR101 is a G protein-coupled receptor (GPCR) implicated in a rare form of genetic gigantism known as X-linked acrogigantism, or X-LAG. In particular, X-LAG patients harbor microduplications in the long arm of the X-chromosome that invariably include the GPR101 gene. Duplications of the GPR101 gene lead to the formation of a new chromatin domain that causes over-expression of the receptor in the pituitary tumors of the patients. Notably, GPR101 is a constitutively active receptor, which stimulates cells to produce the second messenger cyclic AMP (cAMP) in the absence of ligands. Moreover, GPR101 was recently reported to constitutively activate not only the cAMP pathway via Gs, but also other G protein subunits (Gq/11 and G12/13). Hence, chemicals that block the constitutive activity of GPR101, known as inverse agonists, have the potential to be useful for the development of pharmacological tools for the treatment of X-LAG. In this study, we provide structural insights into the putative structure of GPR101 based on in-house built homology models, as well as third party models based on the machine learning methods AlphaFold and AlphaFold-Multistate. Moreover, we report a molecular dynamics study, meant to further probe the constitutive activity of GPR101. Finally, we provide a structural comparison with the closest GPCRs, which suggests that GPR101 does not share their natural ligands. While this manuscript was under review, cryo-electron microscopy structures of GPR101 were reported. These structures are expected to enable computer-aided ligand discovery efforts targeting GPR101.