Future Discovery Research Articles

Analysis and Prediction of Chymotrypsin Substrate Preferences through Large Data Acquisition with Target-Free mRNA Display.

Oral delivery of peptide therapeutics is limited by degradation by gut proteases like chymotrypsin. Existing databases of peptidases are limited in size and do not enable systematic analyses of protease substrate preferences, especially for non-natural amino acids. Thus, stability optimization of hit compounds is time and resource intensive. To accelerate the stability optimization of peptide ligands, we generated large datasets of chymotrypsin-resistant peptides via mRNA display to create a predictive model for chymotrypsin-resistant sequences. Through analysis of enriched motifs, we recapitulate known chymotrypsin cleavage sites, reveal positionally dependent effects of monomers on peptide cleavage, and report previously unidentified protective and destabilizing residues. We then developed a machine-learning-based modelpredicting peptide resistance to chymotrypsin cleavage and validated both model performance and the NGS experimental data by measuring chymotrypsin half-lives for a subset of peptides. Finally, we simulated stability predictions on non-natural amino acids through a leucine hold-out model and observed robust performance. Overall, we demonstrate the utility of mRNA display as a tool for big data generation and show that pairing mRNA display with machine learning yields valuable predictions for chymotrypsin cleavage. Expansion of this workflow to additional proteases could provide complementary predictive models that focus future peptide drug discovery efforts.

Advantages of Metabolomics-Based Multivariate Machine Learning to Predict Disease Severity: Example of COVID

The COVID-19 outbreak caused saturations of hospitals, highlighting the importance of early patient triage to optimize resource prioritization. Herein, our objective was to test if high definition metabolomics, combined with ML, can improve prognostication and triage performance over standard clinical parameters using COVID infection as an example. Using high resolution mass spectrometry, we obtained metabolomics profiles of patients and combined them with clinical parameters to design machine learning (ML) algorithms predicting severity (herein determined as the need for mechanical ventilation during patient care). A total of 64 PCR-positive COVID patients at the Poitiers CHU were recruited. Clinical and metabolomics investigations were conducted 8 days after the onset of symptoms. We show that standard clinical parameters could predict severity with good performance (AUC of the ROC curve: 0.85), using SpO2, first respiratory rate, Horowitz quotient and age as the most important variables. However, the performance of the prediction was substantially improved by the use of metabolomics (AUC = 0.92). Our small-scale study demonstrates that metabolomics can improve the performance of diagnosis and prognosis algorithms, and thus be a key player in the future discovery of new biological signals. This technique is easily deployable in the clinic, and combined with machine learning, it can help design the mathematical models needed to advance towards personalized medicine.

Cannabinoid-like compounds found in non-cannabis plants exhibit antiseizure activity in genetic mouse models of drug-resistant epilepsy.

The cannabinoid cannabidiol has established antiseizure effects in drug-resistant epilepsies such as Dravet syndrome and Lennox-Gastaut syndrome. Amorfrutin 2, honokiol, and magnolol are structurally similar to cannabinoids (cannabis-like drugs) but derive from non-cannabis plants. We aimed to study the antiseizure potential of these compounds in various mouse seizure models. In addition, we aimed to characterize their molecular pharmacology at cannabinoid CB1 and CB2 receptors and at T-type calcium channels, which are known targets of the cannabinoids. Brain and plasma pharmacokinetic profiles were determined. Antiseizure activity was assessed against hyperthermia-induced seizures in a Scn1a+/- mouse model of Dravet syndrome. We then elaborated on the most promising compounds in the maximal electroshock (MES) test in mice and the Gabrb3+/D120N mouse model of Lennox-Gastaut syndrome. Fluorescence-based assays were used to examine modulatory activity at cannabinoid CB1 and CB2 receptors and T-type calcium channel subtypes CaV3.1, CaV3.2, and CaV3.3 overexpressed in mammalian cells. Automated patch-clamp electrophysiology was then used to confirm inhibitory activity on CaV3.1, CaV3.2, and CaV3.3 channels. Magnolol and honokiol had high brain-to-plasma ratios (3.55 and 7.56, respectively), unlike amorfrutin 2 (0.06). Amorfrutin 2 and magnolol but not honokiol significantly increased the body temperature threshold at which Scn1a+/- mice had a generalized tonic-clonic seizure. Both amorfrutin 2 and magnolol significantly decreased the proportion of mice exhibiting hindlimb extension in the MES test. Furthermore, magnolol reduced the number and duration of atypical absence seizures in Gabrb3+/D120N mice. The three compounds inhibited all T-type calcium channel subtypes but were without specific activity at cannabinoid receptors. We show for the first time that amorfrutin 2 and magnolol display novel antiseizure activity in mouse drug-resistant epilepsy models. Our results justify future drug discovery campaigns around these structural scaffolds that aim to develop novel antiseizure drugs for intractable epilepsies.

Potassium channels in depression: emerging roles and potential targets.

Potassium ion channels play a fundamental role in regulating cell membrane repolarization, modulating the frequency and shape of action potentials, and maintaining the resting membrane potential. A growing number of studies have indicated that dysfunction in potassium channels associates with the pathogenesis and treatment of depression. However, the involvement of potassium channels in the onset and treatment of depression has not been thoroughly summarized. In this review, we performed a comprehensive analysis of the association between multiple potassium channels and their roles in depression, and compiles the SNP loci of potassium channels associated with depression, as well as antidepressant drugs that target these channels. We discussed the pivotal role of potassium channels in the treatment of depression, provide valuable insights into new therapeutic targets for antidepressant treatment and critical clues to future drug discovery.

Structural basis of the mechanism and inhibition of a human ceramide synthase.

Ceramides are bioactive sphingolipids crucial for regulating cellular metabolism. Ceramides and dihydroceramides are synthesized by six ceramide synthase (CerS) enzymes, each with specificity for different acyl-CoA substrates. Ceramide with a 16-carbon acyl chain (C16 ceramide) has been implicated in obesity, insulin resistance and liver disease and the C16 ceramide-synthesizing CerS6 is regarded as an attractive drug target for obesity-associated disease. Despite their importance, the molecular mechanism underlying ceramide synthesis by CerS enzymes remains poorly understood. Here we report cryo-electron microscopy structures of human CerS6, capturing covalent intermediate and product-bound states. These structures, along with biochemical characterization, reveal that CerS catalysis proceeds through a ping-pong reaction mechanism involving a covalent acyl-enzyme intermediate. Notably, the product-bound structure was obtained upon reaction with the mycotoxin fumonisin B1, yielding insights into its inhibition of CerS. These results provide a framework for understanding CerS function, selectivity and inhibition and open routes for future drug discovery.

Unlocking Potential: A Comprehensive Overview of Cell Culture Banks and Their Impact on Biomedical Research

Cell culture banks play a crucial role in advancing biomedical research by providing standardized, reproducible biological materials essential for various applications, from drug development to regenerative medicine. This opinion article presents a comprehensive overview of cell culture banks, exploring their establishment, maintenance, and characterization processes. The significance of ethical considerations and regulatory frameworks governing the use of cell lines is discussed, emphasizing the importance of quality control and validation in ensuring the integrity of research outcomes. Additionally, the diverse types of cell culture banks—primary cells, immortalized cell lines, and stem cells—and their specific contributions to different fields such as cancer research, virology, and tissue engineering are examined. The impact of technological advancements on cell banking practices is also highlighted, including automation and biobanking software that enhance efficiency and data management. Furthermore, challenges faced by researchers in accessing high-quality cell lines are addressed, along with proposed strategies for improving collaboration between academic institutions and commercial entities. By unlocking the potential of cell culture banks through these discussions, this article aims to underline their indispensable role in driving innovation within biomedical research and fostering future discoveries that could lead to significant therapeutic breakthroughs.

Structural insights into the agonist selectivity of the adenosine A3 receptor

Adenosine receptors play pivotal roles in physiological processes. Adenosine A3 receptor (A3R), the most recently identified adenosine receptor, is expressed in various tissues, exhibiting important roles in neuron, heart, and immune cells, and is often overexpressed in tumors, highlighting the therapeutic potential of A3R-selective agents. Recently, we identified RNA-derived N6-methyladenosine (m6A) as an endogenous agonist for A3R, suggesting the relationship between RNA-derived modified adenosine and A3R. Despite extensive studies on the other adenosine receptors, the selectivity mechanism of A3R, especially for A3R-selective agonists such as m6A and namodenoson, remained elusive. Here, we identify tRNA-derived N6-isopentenyl adenosine (i6A) as an A3R-selective ligand via screening of modified nucleosides against the adenosine receptors. Like m6A, i6A is found in the human body and may be an endogenous A3R ligand. Our cryo-EM analyses elucidate the A3R-Gi complexes bound to adenosine, 5’-N-ethylcarboxamidoadenosine (NECA), m6A, i6A, and namodenoson at overall resolutions of 3.27 Å (adenosine), 2.86 Å (NECA), 3.19 Å (m6A), 3.28 Å (i6A), and 3.20 Å (namodenoson), suggesting the selectivity and activation mechanism of A3R. We further conduct structure-guided engineering of m6A-insensitive A3R, which may aid future research targeting m6A and A3R, providing a molecular basis for future drug discovery.

Single-cell transcriptome unveils unique transcriptomic signatures of human organ-specific endothelial cells.

The heterogeneity of endothelial cells (ECs) across humantissues remains incompletely inventoried. We constructed an atlas of > 210,000 ECs derivedfrom 38 regions across 24 human tissues. Our analysis reveals significant differences in transcriptome, phenotype, metabolism and transcriptional regulationamong ECs from various tissues. Notably,arterial, venous, and lymphatic ECs shared more commonmarkers in multiple tissues than capillary ECs, which exhibited higher heterogeneity.This diversity in capillary ECs suggests their greater potential as targets for drug development. ECs from different tissues and vascular beds were found to be associated with specific diseases. Importantly,tissue specificity of EC senescence is moredetermined by somatic site than by tissue type (e.g. subcutaneus adipose tissue andvisceral adipose tissue). Additionally, sex-specific differences in brain EC senescencewere observed. Our EC atlas offers valuble resoursce for identifying EC subclusters in single-cell datasets from body tissues or organoids, facilitating thescreen oftissue-specific targeted therapies, and serving as a powerful tool for future discoveries.

Chromosome architecture as a determinant for biosynthetic diversity in Micromonospora.

Natural products - small molecules generated by organisms to facilitate ecological interactions - are of great importance to society and are used as antibacterial, antiviral, antifungal and anticancer drugs. However, the role and evolution of these molecules and the fitness benefits they provide to their hosts in their natural habitat remain an outstanding question. In bacteria, the genes that encode the biosynthetic proteins that generate these molecules are organised into discrete loci termed biosynthetic gene clusters (BGCs). In this work, we asked the following question: How are biosynthetic gene clusters organised at the chromosomal level? We sought to answer this using publicly available high-quality assemblies of Micromonospora, an actinomycete genus with members responsible for biosynthesizing notable natural products, such as gentamicin and calicheamicin. By orienting the Micromonospora chromosome around the origin of replication, we demonstrated that Micromonospora has a conserved origin-proximal region, which becomes progressively more disordered towards the antipodes of the origin. We then demonstrated through genome mining of these organisms that the conserved origin-proximal region and the origin-distal region of Micromonospora have distinct populations of BGCs and, in this regard, parallel the organization of Streptomyces, which possesses linear chromosomes. Specifically, the origin-proximal region contains highly syntenous, conserved BGCs predicted to biosynthesize terpenes and a type III polyketide synthase. In contrast, the ori-distal region contains a highly diverse population of BGCs, with many BGCs belonging to unique gene cluster families. These data highlight that genomic plasticity in Micromonospora is locus-specific, and highlight the importance of using high-quality genome assemblies for natural product discovery and guide future natural product discovery by highlighting that biosynthetic novelty may be enriched in specific chromosomal neighbourhoods.

CRISPRi/a screens in human iPSC-cardiomyocytes identify glycolytic activation as a druggable target for doxorubicin-induced cardiotoxicity.

Doxorubicin is limited in its therapeutic utility due to its life-threatening cardiovascular side effects. Here, we present an integrated drug discovery pipeline combining human induced pluripotent stem cell (iPSC)-derived cardiomyocytes (iCMs), CRISPR interference and activation (CRISPRi/a) bidirectional pooled screens, and a small-molecule screening to identify therapeutic targets mitigating doxorubicin-induced cardiotoxicity (DIC) without compromising its oncological effects. The screens revealed several previously unreported candidate genes contributing to DIC, including carbonic anhydrase 12 (CA12). Genetic inhibition of CA12 protected iCMs against DIC by improving cell survival, sarcomere structural integrity, contractile function, and calcium handling. Indisulam, a CA12 antagonist, can effectively attenuate DIC in iCMs, engineered heart tissue, and animal models. Mechanistically, doxorubicin-induced CA12 potentiated a glycolytic activation in cardiomyocytes, contributing to DIC by interfering with cellular metabolism and functions. Collectively, our study provides a roadmap for future drug discovery efforts, potentially leading to more targeted therapies with minimal off-target toxicity.

Full-Body Impressions: A category of trace fossils unique to exceptionally preserved bedding planes and indicators of true substrates

Certain biogenic sedimentary structures can be considered to be reliable indicators of true substrates. Full-body impressions, or FBIs, are trace fossils that are shallow, highly-detailed impressions of the ventral axial anatomy of low body mass animals made while living . Their mode of preservation makes FBIs distinct from undertracks, body moulds, or passive tool marks. FBIs are made at the air- or water-substrate interface during sedimentary stasis. Associated trace fossils, like those that exhibit excavations with preserved waste mounds and very near-surface burrow roofs, located on the same bedding plane, can support the interpretation of true substrate preservation. Integration of the biogenic and sedimentological data from both Carboniferous and Pleistocene sites with well-preserved bedding-plane trace fossil assemblages has confirmed the conditions under which true substrates are preserved. These include periods (as brief as days to weeks) of sedimentary stasis, followed by gentle deposition without erosion, and without the need to invoke biofilms or biomats as consolidants. The potential for these taphonomic conditions exist in both alluvial and lacustrine environments, as well as intertidal-estuarine valleys, as described by other published examples of FBI preservation. Future FBI discoveries will prove useful in identifying true substrates across a range of time periods and environments.

L858R/L718Q and L858R/L792H Mutations of EGFR Inducing Resistance Against Osimertinib by Forming Additional Hydrogen Bonds.

Acquired resistance to first-line treatments in various cancers both promotes cancer recurrence as well as limits effective treatment. This is true for epidermal growth factor receptor (EGFR) mutations, for which secondary EGFR mutations are one of the principal mechanisms conferring resistance to the covalent inhibitor osimertinib. Thus, it is very important to develop a deeper understanding of the secondary mutational resistance mechanisms associated with EGFR mutations arising in tumors treated with osimertinib to expedite the development of innovative therapeutic drugs to overcome acquired resistance. This work uses all-atom molecular dynamics (MD) simulations to investigate the conformational variation of two reported EGFR mutants (L858R/L718Q and L858R/L792H) that resist osimertinib. The wild-type EGFR kinase domain and the L858R mutant are used as the reference. Our MD simulation results revealed that both the L718Q and L792H secondary mutations induce additional hydrogen bonds between the residues in the active pocket and the residues with the water molecules. These additional hydrogen bonds reduce the exposure area of C797, the covalent binding target of osimertinib. The additional hydrogen bonds also influence the binding affinity of the EGFR kinase domain by altering the secondary structure and flexibility of the amino acid residues in the domain. Our work highlights how the two reported mutations may alter both residue-residue and residue-solvent hydrogen bonds, affecting protein binding properties, which could be helpful for future drug discovery.

Physics, AI, and the future of discovery

Leaders from industry, government, and academia discuss the potential impact of AI on physics—including neutrinos, exoplanets, term papers, outreach, and workforce gaps—and of physics on AI.

The influence of parasitic modes on stable lattice Boltzmann schemes and weakly unstable multi-step Finite Difference schemes

Numerical analysis for linear constant-coefficient multi-step Finite Difference schemes is a longstanding topic, developed approximately fifty years ago. It relies on the stability of the scheme, and thus—within the L2 setting—on the absence of multiple roots of the amplification polynomial on the unit circle. This allows for the decoupling, while discussing the convergence of the method, of the study of the consistency of the scheme from the precise knowledge of its parasitic/spurious modes, so that the methods can be essentially studied as if they had only one step. Furthermore, stability alleviates the need to delve into the complexities of floating-point arithmetic on computers, which can be challenging topics to address. In this paper, we demonstrate that in the case of “weakly” unstable Finite Difference schemes with multiple roots on the unit circle, although the schemes may remain stable, considering parasitic modes is essential in studying their consistency and, consequently, their convergence. This research was prompted by unexpected numerical results on stable lattice Boltzmann schemes, which can be rewritten in terms of multi-step Finite Difference schemes. Unlike Finite Difference schemes, rigorous numerical analysis for lattice Boltzmann schemes is a contemporary topic with much left for future discoveries. Initial expectations suggested that third-order initialization schemes would suffice to maintain the accuracy of fourth-order schemes. However, this assumption proved incorrect for weakly unstable Finite Difference schemes and for stable lattice Boltzmann methods. This borderline scenario underscores that particular care must be adopted for lattice Boltzmann schemes, and the significance of genuine stability in facilitating the construction of Lax-Richtmyer-like theorems and in mastering the impact of round-off errors concerning Finite Difference schemes. Despite the simplicity and apparent lack of practical usage of the linear transport equation at constant velocity considered throughout the paper, we demonstrate that high-order lattice Boltzmann schemes for this equation can be used to tackle nonlinear systems of conservation laws relying on a Jin-Xin approximation and high-order splitting formulæ.

Triazole scaffold-based DPP-IV Inhibitors for the management of Type-II Diabetes Mellitus: Insight into Molecular Docking and SAR.

Diabetes mellitus, characterized as a chronic metabolic disorder or a polygenic syndrome; is increasing at a very fast pace among every group of the population worldwide. It arises due to the inability of the body to produce enough insulin (the hormone responsible for controlling blood sugar levels) or inability to utilize the insulin, leading to hyperglycaemic condition, which, if left uncontrolled gives rise to chronic microvascular and macrovascular complications like retinopathy, neuropathy, nephropathy, coronary artery disease, cognitive impairment, etc. Several therapeutic approaches are available for the treatment of diabetes; among which dipeptidyl peptidase (DPP-IV) inhibitors (gliptins) hold a significant place. DPP-IV is a multifunctional enzyme or a serine exopeptidase that plays an imperative role in cleaving bioactive molecules. DPP-IV causes the breakdown of incretin hormone (GLP-1: Glucagon-like peptide 1 and GIP: Glucose-dependent insulinotropic peptide) that is essential for controlling glycaemic levels in the body. Inhibition of DPP-IV enzyme (DPP-IV inhibitors: Sitagliptin, Saxagliptin, Linagliptin, Alogliptin) prevents this breakdown, thereby controlling blood glucose levels and saving the patients from deleterious effects of prolonged hyperglycaemic conditions. Triazole-based DPP-IV inhibitors are a significant class of drugs used to treat Type 2 diabetes mellitus in a dose-dependent manner. Clinical trials have demonstrated their efficacy as monotherapy or in combination with other antidiabetic agents. This review highlights the molecular docking studies and structure-activity relationship of potential synthetic derivatives that may act as lead molecules for future drug discovery and yield drug molecules with enhanced efficacy, potency and reduced toxicity profile.

Elucidating Antibiotic Permeation through the Escherichia coli Outer Membrane: Insights from Molecular Dynamics.

Antibiotic resistance represents a critical public health threat, with an increasing number of Gram-negative pathogens demonstrating resistance to a broad range of clinical drugs. A primary challenge in enhancing antibiotic efficacy is overcoming the robust barrier presented by the bacterial outer membrane. Our research addresses a longstanding question: What is the rate of antibiotic permeation across the outer membrane (OM) of Gram-negative bacteria? Utilizing molecular dynamics (MD) simulations, we assess the passive permeability profiles of four commercially available antibiotics─gentamicin, novobiocin, rifampicin, and tetracycline across an asymmetric atomistic model of the Escherichia coli (E. coli) OM, employing the inhomogeneous solubility-diffusion model. Our examination of the interactions between these drugs and their environmental context during OM permeation reveals that extended hydrogen bond formation and drug-cation interactions significantly hinder the energetics of passive permeation, notably affecting novobiocin. Our MD simulations corroborate well with experimental data and reveal new implications of solvation on drug permeability, overall advancing the possible use of computational prediction of membrane permeability in future antibiotic discovery.

Exploring the Cosmos: Impact and Significance of the James Webb Space Telescope

The James Webb Space Telescope (JWST) marks a pivotal advancement in astronomical research, building upon the legacy of its predecessors by enhancing the observational capabilities and expanding the understanding of the universe. This study explores the transformative impact of JWST, emphasizing its role in studying the formation and evolution of early galaxies, stars, and planetary systems. By utilizing its advanced infrared capabilities, JWST can penetrate cosmic dust and observe celestial phenomena that were previously obscured, thereby providing unprecedented insights into the early universe and the origins of life’s building blocks. The findings from JWST are expected to challenge existing theories and assumptions in cosmology and astrophysics, facilitating a paradigm shift in the comprehension of cosmic structures and the fundamental processes governing them. Furthermore, the telescope’s ability to analyze exoplanetary atmospheres will contribute significantly to the search for life beyond Earth. Ultimately, the JWST not only represents a technological marvel but also serves as a cornerstone for future astronomical discoveries, shaping the conception of the cosmos for generations to come.

In silico-guided synthesis of a new, highly soluble, and anti-melanoma flavone glucoside: Skullcapflavone II-6'-O-β-glucoside.

Guided by in silico analysis tools and biotransformation technology, new derivatives of natural compounds with heightened bioactivities can be explored and synthesized efficiently. In this study, in silico data mining and molecular docking analysis predicted that glucosides of skullcapflavone II (SKII) were new flavonoid compounds and had higher binding potential to oncogenic proteins than SKII. These benefits guided us to perform glycosylation of SKII by utilizing four glycoside hydrolases and five glycosyltransferases (GTs). Findings unveiled that exclusive glycosylation of SKII was achieved solely through the action of GTs, with Bacillus subtilis BsUGT489 exhibiting the highest catalytic glycosylation efficacy. Structure analysis determined the glycosylated product as a novel compound, skullcapflavone II-6'-O-β-glucoside (SKII-G). Significantly, the aqueous solubility of SKII-G exceeded its precursor, SKII, by 272-fold. Furthermore, SKII-G demonstrated noteworthy anti-melanoma activity against human A2058 cells, exhibiting an IC50 value surpassing that of SKII by 1.4-fold. Intriguingly, no substantial cytotoxic effects were observed in a murine macrophage cell line, RAW 264.7. This promising anti-melanoma activity without adverse effects on macrophages suggests that SKII-G could be a potential candidate for further preclinical and clinical studies. The in silico tool-guided synthesis of a new, highly soluble, and potent anti-melanoma glucoside, SKII-G, provides a rational design to facilitate the future discovery of new and bioactive compounds.

Thermal Quenching Mechanism of Mn4+ in Na2SiF6, NaKSiF6, and K2SiF6 Phosphors: Insights from the First-Principles Analysis.

This study aims to identify the key factors governing the thermal quenching of Mn4+ ion luminescence in fluoride-based phosphor materials used as red emitters in modern-day phosphor-converted LED devices. Here, we employ first-principles calculations for Mn4+-doped Na2SiF6, NaKSiF6, and K2SiF6 hosts to explore how host properties and local coordination environments influence thermal quenching behavior. The ΔSCF method was used to model the geometric structures of the Mn4+4A2 (ground) and 2E, 4T2 (excited) states and the energies of the optical transitions between these states. Our results reveal that thermal quenching in Na2SiF6 and K2SiF6 phosphors occurs through thermally activated 2E → 4T2 → 4A2 crossover. In contrast, thermal quenching in NaKSiF6 is due to other nonradiative decay pathways. Investigations of the mechanical stability of these fluorides show that NaKSiF6 is mechanically unstable. We suggest that this property of the host limits the luminescence efficiency of the embedded Mn4+ ions. We also determined the reason for the difference in the intensity of the 2E → 4A2 emission transition (ZPL) in the systems. These findings advance our fundamental understanding of the thermal quenching mechanism of Mn4+ ion luminescence in fluorides, and the results can aid future discoveries of technologically useful phosphors through high-throughput design methodologies.

Orphan GPCRs in Neurodegenerative Disorders: Integrating Structural Biology and Drug Discovery Approaches.

Neurodegenerative disorders, particularly Alzheimer's and Parkinson's diseases, continue to challenge modern medicine despite therapeutic advances. Orphan G-protein-coupled receptors (GPCRs) have emerged as promising targets in the central nervous system, offering new avenues for drug development. This review focuses on the structural biology of orphan GPCRs implicated in these disorders, providing a comprehensive analysis of their molecular architecture and functional mechanisms. We examine recent breakthroughs in structural determination techniques, such as cryo-electron microscopy and X-ray crystallography, which have elucidated the intricate conformations of these receptors. The review highlights how structural insights inform our understanding of orphan GPCR activation, ligand binding and signaling pathways. By integrating structural data with molecular pharmacology, we explore the potential of structure-guided approaches in developing targeted therapeutics toward orphan GPCRs. This structural-biology-centered perspective aims to deepen our comprehension of orphan GPCRs and guide future drug discovery efforts in neurodegenerative disorders.