Biology subjects

Sun, Q.

Publications and source records attributed to Sun, Q..

At least 19 recordsLinked to original sources

bioRxiv2026

A molecularly defined recurrent CA3 circuit regulates network dynamics and spatial working memory

The hippocampal CA3 region supports coordinated network activity and memory processes, but how molecularly distinct CA3 neuronal populations contribute to recurrent circuit function remains poorly understood. Here we identify St18 as a molecular marker of a distinct population of deep-layer, burst-firing CA3 pyramidal neurons and generate an St18-Cre mouse line for their selective genetic targeting. In contrast to canonical CA3 pyramidal neurons, St18 neurons preferentially innervate CA3 bilaterally, with only sparse projections to CA1. Moreover, St18 neurons are highly active during endogenous CA3 sharp-wave ripples, and their optogenetic activation evokes local ripple-like activity in CA3 but not in CA1. Furthermore, chemogenetic suppression markedly reduces CA3 ripple occurrence without significantly affecting CA1 ripple occurrence and selectively impairs spatial working memory performance. Together, these findings reveal the functional significance of a molecularly defined CA3 recurrent circuit, linking neuronal heterogeneity to hippocampal network dynamics and spatial working memory.

neuroscience↗

bioRxiv2026

LRRC37A is essential for acrosomal ion homeostasis and male fertility

Mammalian spermatozoa face various challenges during their long march to the destination. As a specialized membrane-bound organelle in the sperm head, the acrosome is particularly sensitive to changes in ionic and osmotic conditions, yet how acrosomal ion homeostasis is maintained remains largely unknown. Here, we show that LRRC37A is required for acrosomal ion homeostasis. Loss of Lrrc37a causes complete male infertility, accompanied by pronounced enlargement and deformation of the acrosome in the sperm head. Acrosome biogenesis was not affected by Lrrc37a knockout during the early stages of spermiogenesis, whereas acrosomal enlargement emerged at later stages and became more pronounced in the epididymis. LRRC37A localized to the outer acrosomal region and interacted with the Na/K-ATPase -subunit isoforms ATP1A1 and ATP1A4. Loss of LRRC37A disrupted the spatial distribution of both isoforms and was accompanied by increased Na within the acrosomal region. In addition, pharmacological perturbation of Na/K-ATPase activity or cellular ion homeostasis induced acrosomal swelling. These findings establish an essential role for LRRC37A in acrosomal ion homeostasis, suggesting that its deficiency may be associated with a distinct form of teratozoospermia characterized by acrosomal enlargement.

cell biology↗

bioRxiv2026

Sparse Linear Algebra Accelerates Genotype Representation Graph Computation at Biobank Scale

Biobank-scale genomic analyses are increasingly constrained by computational costs, as hundreds of thousands to millions of samples and variants must be analyzed together. The genotype representation graph (GRG) compactly encodes population genetic variation to accelerate computation, but the current approach does not exploit modern accelerator architectures. This work introduces Mikado, a new methodology for expressing GRG-based computation using sparse linear algebra primitives. Under a reverse topological ordering of the graph nodes, the GRG adjacency matrix is strictly block-lower-triangular, and the genotype matrix-vector product becomes a sparse triangular solve that can be further decomposed into a pipelined sequence of blocked sparse matrix-vector multiplies. By decoupling computation from graph representation, our approach exposes fine-grained parallelism and enables hardware-optimized sparse primitives on GPUs. Mikado achieves an order-of-magnitude speedup and cost savings for PCA and BOLT-LMM compared with the original GRG traversal approach, including on All of Us cohorts. It provides a scalable, hardware-portable, researcher-friendly tool for population genetics at biobank scale.

genomics↗

bioRxiv2026

Structural basis of endogenous inverse agonism and subtype selectivity at melanocortin receptors

Endogenous inverse agonists suppress constitutive G protein-coupled receptor (GPCR) signaling, but their mechanisms remain poorly understood. Here we report cryo-EM structures of melanocortin-1 receptor (MC1R) bound to its endogenous inverse agonist, agouti signaling protein (ASIP) and melanocortin-4 receptor (MC4R) bound to agouti-related protein (AgRP). Together with previously reported structures and those we determined using extracellular nanobodies developed here, these data delineate a conformational continuum underlying receptor activation and silencing. Both inverse agonists occlude the orthosteric pocket as molecular corks and drive a shared TM3-centered extracellular remodeling. Against this common mechanism, subtype selectivity is encoded not by the conserved orthosteric pocket but by the divergent extracellular receptor surface, engaged through an ASIP C-terminal loop-dependent clasp. These findings establish a mechanistic framework for endogenous inverse agonism and identify the receptor periphery as a tractable target for subtype-selective modulation.

biophysics↗

bioRxiv2026

Enhancing the Identification of NHS Ester-Mediated Lysine-Cysteine Cross-Linking via Reduced Trypsin Digestion Time

Abstract Chemical cross-linking mass spectrometry (XL-MS) is a powerful technique for elucidating protein structures and interactions, with NHS ester-based cross-linkers being the most widely used. Traditionally, NHS esters are considered highly specific for primary amines; although their reactivity toward cysteine thiols has been reported, it has not been systematically characterized in XL-MS due to the extreme lability of the resulting thioester bonds. Here, we demonstrate that NHS esters efficiently label cysteine residues and form stable lysine-cysteine (K-C) cross-links--species previously deemed labile in XL-MS. To preserve these thioester-based cross-linked sites , we optimized the standard XL-MS workflow and applied it to four model proteins. K-C cross-links constitute 23% to 59% of total detected cross-links, with C-C distances predominantly ranging from 12 to 40 [A], and 60% satisfying theoretical linker constraints -- confirming that K-C cross-links are as reliable as canonical lysine-lysine (K-K) cross-link sites. Cross-software validation and benchmarking against the heterobifunctional K-C cross-linker GMBS further demonstrated that our optimized workflow captures ~ 40% of GMBS-identified K-C cross-linked sites. Collectively, these findings expand the practical utility of NHS esters and enhance protein structural characterization by enabling simultaneous acquisition of K-K and K-C distance constraints.

biochemistry↗

bioRxiv2026

Human Osteocytes Express MHC ClassII and Act as Non-classical Antigen-Presenting Cells During Bacterial Infection

Osteocytes are the most abundant cells in bone and are increasingly recognised not only for their role in skeletal remodelling and inflammatory signalling but also for their potential involvement in immune responses. In this study, we searched available gene expression datasets of human primary osteocyte-like cells exposed acutely to Staphylococcus aureus and identified significantly induced expression of key genes related to antigen processing and presentation. We then confirmed that human bone explant-derived osteoblastic cells, representative of a mature osteoblast-pre-osteocyte stage, expressed, as expected, high cell surface levels of major histocompatibility complex (MHC) Class I but also, low basal levels of the MHC Class II family member, HLA-DR. However, confocal imaging revealed high expression of MHC Class II molecules and the peptide-loading chaperone HLA-DM within the lysosomal compartments, consistent with canonical antigen-processing machinery. Differentiation towards a mature osteocyte phenotype increased MHC Class II protein levels and maintained expression of intracellular HLA-DM. Exposure of mature osteocyte-like cells to S. aureus further up-regulated both intracellular and cell surface MHC Class II expression. Demonstrative of antigen presenting cell functionality, S. aureus-exposed osteocytes induced autologous CD4+ T cell proliferation. Furthermore, MHC Class II expression in osteocytes was detected in bone sampled from patients with periprosthetic joint infections, providing evidence that these mechanisms operate in vivo. Together, our findings reveal that human osteocytes are capable of inducible MHC Class II-associated antigen presentation in response to bacterial challenge, pointing to a novel role for osteocytes in adaptive immune surveillance within bone.

immunology↗

bioRxiv2026

Patterns and environmental drivers of amphibian alpha and beta diversity in the Huangshan Mountains, southern Anhui, China

Understanding the spatial patterns of biodiversity and their environmental determinants is fundamental to ecology and conservation, particularly in mountainous transitional zones where species assemblages can shift rapidly. Amphibians, as highly sensitive organisms, are excellent indicators of environmental change, yet quantitative assessments of their diversity in the Huangshan Mountains-a biodiversity hotspot at the junction of the Palaearctic and Oriental realms in southern Anhui, China-remain limited. We conducted systematic line-transect surveys across 200 grids (5 km x 5 km) during the spring and autumn of 2023 and 2024, recording a total of 10,342 individuals belonging to 23 species, 20 genera, 9 families, and 2 orders. Three species (Fejervarya multistriata, Microhyla fissipes, and Bufo gargarizans) were identified as dominant, and two nationally protected species (Hoplobatrachus chinensis and Andrias davidianus) were detected. Inter-annual alpha diversity did not differ significantly, but pronounced seasonal variation was observed, with spring supporting higher Shannon-Wiener and Pielou evenness than autumn in both years. Using generalized additive models and model averaging, we found that annual precipitation and the normalized difference vegetation index (NDVI) were consistently the strongest positive predictors of Shannon-Wiener diversity, Simpson dominance, and species richness, while species richness also declined significantly with increasing human footprint. Total beta diversity (Soerensen dissimilarity) was very high (0.981) and overwhelmingly driven by species turnover (97.86%) rather than nestedness. Partial Mantel tests and distance-based redundancy analysis further revealed that environmental distances-particularly annual precipitation-significantly shaped overall beta diversity and its turnover component after accounting for geographic distance. These results highlight the predominant role of climatic and vegetation gradients in structuring amphibian assemblages in this subtropical mountainous region, providing baseline data to inform local conservation strategies.

ecology↗

bioRxiv2026

Quantification of bone loss, periosteal bone formation and novel histopathological changes in a mouse implant-related Staphylococcus aureus infection model

Implant-associated bone infection involves a complex interplay between pathogenic stimuli and host cell responses, yet analysis in preclinical models has typically relied on qualitative or semi-quantitative measures. We aimed to establish a quantified evaluation framework to define host-pathogen relationships in a preclinical implant infection model. Staphylococcus aureus-coated stainless-steel implants were inserted trans-cortically in mouse tibiae and bone changes recorded longitudinally by in vivo micro-CT. An automated segmentation task list was developed to independently isolate and quantify cortical, periosteal-reactive, and trabecular bone compartments. RGB trichrome histomorphometry was used to quantify bone matrix integrity, osteocyte lacunar geometry, and osteoclastic activity. Droplet digital PCR was used to determine absolute bacterial and host genome copy number. Infected implants produced marked reductions in trabecular bone volume fraction, number, and bone mineral density (BMD), together with decreased cortical bone volume fraction and increased cortical porosity, accompanied by significant elevations in periosteal bone volume fraction. Histologically, infected bone exhibited increased eroded surface indicative of osteoclastic resorption, extensive degraded bone matrix and pathological remodelling of osteocyte lacunae towards circularity, consistent with an osteocytic osteolysis response. Infection-induced changes to cortical bone structure correlated mostly with host cell rather than bacterial load; however, cortical BMD negatively correlated with the bacterial:host genome ratio. This multifaceted, quantified framework reveals distinct pathobiological effects of implant-associated infection on trabecular, cortical, and periosteal bone compartments, bone matrix and osteocyte and osteoclast populations, consistent with reports in human patients, suggesting that major pathological changes are driven by the host bone cell response to infection.

pathology↗

bioRxiv2026

Pharmacological up-regulation of CALM1 restore endothelial cells in intracranial aneurysm pathogenesis

Subarachnoid hemorrhage (SAH) resulted from intracranial aneurysm (IA) rupture is an especially severe form of stroke. Endothelial dysfunction represents the initiating event of IA pathogenesis. Understanding the role of endothelial cells (ECs) underlying formation of IAs is helpful to seek for pharmaceutical treatment strategy. Based on single-cell RNA sequencing, proteomics, and metabolic analysis, we discovered a change in cell population in IA samples, majorly in ECs and macrophages (MPs). Abnormal ECs exhibit senescence and death in IA samples, which is absent in the control arterial samples. Cross-analysis of multi-omics revealed that CALM1, a calcium detector involved in mechanotransduction, is downregulated in the abnormal ECs. CALM1 knockdown leads to senescence and inhibits the proliferation and maturation of ECs under turbulent flow. Through high-throughput virtual screening, this work identified compound ZC04329651 as a potent CALM1 activator in maintaining the stability of endothelial cell junctions and attenuating cellular senescence. Thus, our findings showed compound ZC04329651 up-regulate the expression of CALM1 to restore ECs, which maybe a promising pharmacological treatment strategy for IAs.

cell biology↗

bioRxiv2026

Transfer learning reveals species-specific olfactory preferences in Diptera and informs pest management strategies

The interaction between volatile organic compounds (VOCs) and odorant receptors (ORs), termed VOI, constitutes the molecular basis for species to recognize chemical information in the environment. Characterization of subtle differences in VOI relationships among closely related species is crucial for understanding the rapid evolution of ORs and for identifying species-specific chemical cues relevant to pest management. However, progress in this field has been constrained by both the scarcity of experimental data and limitations in computational prediction accuracy. To address this, we developed a virtual screening-enhanced transfer learning strategy that integrates large-scale molecular docking data with sparse functional experimental data. The resulting VOI prediction model was validated through functional experiments on the pest species Bactrocera dorsalis, demonstrating its cross-species predictive capacity. Using this model, we investigated the relationship between ecological niches and olfactory sensitivity in Diptera insects from multiple perspectives, with an emphasis on patterns that may inform pest behavioral research. The models predictive reliability was further supported by its consistency with known olfactory trends: it recapitulated the preferential responses of fruit flies and mosquitoes to esters and aromatics, respectively, and reproduced the previously reported negative correlation between olfactory and visual capacities in Drosophila. As a proof-of-concept application, we compared hematophagous and non-hematophagous mosquitoes, revealing overlapping chemical spaces but distinct patterns in their specifically recognized compounds. This study provides a reliable VOI prediction framework that reveals species-level olfactory preference patterns in Diptera, offering a computational pipeline to accelerate the discovery of behaviorally active compounds for species-specific pest monitoring and control.

bioinformatics↗

bioRxiv2026

Discovery of ARQ-501 as a potent PafA inhibitor that elevates KatG levels to potentiate isoniazid in mycobacteria

The prokaryotic ubiquitin-like protein (Pup) conjugation system (PPS), which is essential for Mycobacterium tuberculosis (Mtb) virulence but absent in humans, presents an attractive drug target. Here, we report the discovery of ARQ-501, a quinone-based, covalent, substrate-competitive inhibitor of the Pup ligase PafA. ARQ-501 exhibited potent anti-mycobacterial activity against Mtb under host-mimicking stress conditions and within macrophages. We further identified the catalase-peroxidase KatG, essential for activation of the frontline prodrug isoniazid (INH), as a pupylation substrate. ARQ-501 inhibits KatG pupylation, causing its accumulation and creating a selective synergy with INH. This quantity over quality mechanism successfully rescued INH activation by the clinically prevalent KatG S315T mutant in enzymatic assays and enhanced INH efficacy against clinical S315T isolates to variable degrees. This work identifies a novel class of PafA inhibitors and a previously unrecognized role of pupylation in regulating KatG, offering a potential therapeutic avenue to combat drug-resistant tuberculosis.

microbiology↗

bioRxiv2026

Yawning reveals energy-dynamics mismatch and neural inertia across state transitions

Yawning is a highly conserved behavior, yet its neural dynamics across arousal state transitions remain poorly understood. Classical reflex models fail to account for the precise timing of yawns during large-scale changes in brain network organization. Here, we investigated the neural signatures of yawning using simultaneous electroencephalography (EEG), electromyography (EMG), and kinematic recordings in a beagle model during wakefulness and propofol anesthesia. Propofol-associated yawning exhibited marked temporal asymmetry, with 89.2% of events occurring during emergence from anesthesia. To resolve the fast neural dynamics surrounding these events, we applied empirical mode decomposition coupled with the Hilbert-Huang transform (EMD-HHT) analyses. Across induction, recovery, and wakefulness, yawning was consistently associated with a transient decoupling between local and global network dynamics: a brief increase in local {gamma}-band power coincided with a drop in network flexibility, quantified by instantaneous frequency volatility; IFV). We termed this reproducible motif as "Energy-Dynamics Mismatch" (EDM). A machine learning classifier leveraging EDM features reliably decoded the brain state immediately preceding yawning. We further validated the presence of this signature in an independent human cohort during anesthesia induction. These findings indicate that yawning is not a passive reflex, but is tightly linked to moments of network instability during state transitions. From a computational perspective, EDG may reflect a transient "control effort" that preserves information integration in the presence of "neural inertia." This dynamic signature may provide a quantitative biomarker for monitoring arousal transitions brain-computer interface (BCI) interface state-alerting. Significance StatementYawning is a ubiquitous and evolutionarily conserved behavior, yet its neural basis remains elusive. Using high-resolution neural recordings in a cross-species model, we show that yawning is not a passive reflex, but reliably coincides with a distinct, transient brain-state signature. Specifically, yawning occurs when local high-frequency cortical activity briefly increases while global network flexibility decreases - a pattern we term an "Energy-Dynamics Mismatch" (EDM). We propose that EDM reflects a compensatory neural process engaged during moments of network instability, consistent with overcoming neural inertia to preserve information integration. By identifying this conserved neural marker, this work advances the biological understanding of yawning and suggests a potential biomarker for detecting critical brain states in future BCI.

neuroscience↗

bioRxiv2026

Generalizable Finger Movement Decoding from Intracranial Recordings Across Static and Dynamic Actions

Reliable decoding of finger movements requires brain-computer interfaces (BCIs) that generalize across the diverse static and dynamic actions performed in daily life. Static postures and dynamic movement sequences rely on partially distinct neural representations, and the balance between these components varies widely across tasks. Yet most BCI decoding pipelines are optimized for a narrow task domain, limiting their ability to transfer to new scenarios. Here we show that standard intracranial decoding approaches show notable performance drops when applied to previously unseen finger tasks with different static-dynamic compositions, and that generalization critically depends on multiple elements of the decoding pipeline. High gamma features and short temporal windows yield the most robust cross task transfer. Although nonlinear models perform best when examples of all tasks are represented during training, linear decoders generalize better to novel, particularly dynamic, actions. We identify a consistent static-dynamic structure across tasks that may provide a useful basis for improving generalization. Finally, we show that anatomical heterogeneity between tasks also constrains generalization. Together, these results establish design principles for BCIs that generalize reliably across the rich repertoire of human finger movements.

neuroscience↗

bioRxiv2026

A Conserved Geometric Code: Extracellular Matrix Curvature Directs Cell Migration Strategy via Nuclear Mechanosensing

Cells navigate complex tissue microenvironments defined by intricate physical cues, yet how they interpret the three-dimensional geometry of the extracellular matrix (ECM) remains an open question. Current models often fail to account for the tortuous architectures found in physiological tissues. Here, we demonstrate that ECM curvature functions as a tissue-specific geometric code read by the cell nucleus. By mapping collagen architectures across cancers and tissues, we find unique curvature fingerprints preserved during metastasis. Using micro-engineered substrates, we show that high curvature imposes localized nuclear bending stress, triggering a Lamin A/C-cPLA2-Ca2+ mechanotransductive cascade. This sensor rewires the cytoskeleton from longitudinal stress fibers to a cortical actomyosin network, driving a sharp transition from fast mesenchymal migration to a slower, exploratory amoeboid phenotype. We term this "nuclear curvotaxis", establishing a physical principle linking static geometry to dynamic strategy, with implications for predicting metastatic risk, understanding immune exclusion, and designing bio-instructive scaffolds for tissue engineering.

biophysics↗

bioRxiv2026

Genetically Engineered Biomimetic Nanozymes Reprogram Immune Niches to Intercept Colitis-Carcinoma Transition

Colitis-associated colorectal cancer (CAC) arises from chronic inflammatory niches characterized by persistent oxidative stress and dysregulated immune cell recruitment. Current anti-inflammatory therapies provide only transient symptom relief and fail to prevent malignant progression due to their inability to simultaneously mitigate oxidative injury and immune chemotaxis. Our analysis of clinical samples revealed markedly elevated C-X-C motif chemokine ligand 2 (CXCL2) in intestinal tissues from patients with inflammatory bowel disease (IBD) and CAC, implicating the CXCL2-CXCR2 axis in driving excessive neutrophil and macrophage infiltration and fostering tumorigenesis. Herein, we report a biomimetic nanozymes (PB@ECM) that reprogram inflammatory immune niches to intercept CAC progression. PB@ECM integrates a Prussian blue nanozyme core with genetically engineered macrophage membranes, enabling concurrent scavenging of reactive oxygen species through superoxide dismutase- and catalase-like activities and sequestration of CXCL2 via membrane-displayed CXCR2 receptors. In murine models of colitis and CAC, PB@ECM significantly alleviated intestinal inflammation, suppressed neutrophil and macrophage infiltration, and effectively inhibited colitis-carcinoma transition. By disrupting the pathological crosstalk between oxidative stress and immune chemotaxis, this work establishes a biomimetic nanozyme strategy for preventing inflammation-driven carcinogenesis.

bioengineering↗

bioRxiv2026

Spin-State Modulation by Atom-Cluster Synergy Steers H2O2 Conversion toward a Catalase-like Decomposition Pathway for Anti-Inflammatory Therapy

Nanozymes have emerged as promising enzyme mimics for anti-inflammatory therapy. However, their catalytic efficiency and substrate selectivity generally remain inferior to those of natural enzymes. Single-atom nanozymes (SAzymes), with isolated metal centers resembling enzymatic active sites, represent an important advance toward rational design of nanozyme, but achieving enzyme-like selectivity remains challenging. Herein, we reported a spin-state modulation strategy to prepare Fe-N-C nanozyme with coexisting single atoms and nanoclusters (FeSA+NC) via reductive-gas pyrolysis. Experimental analyses and density functional theory calculations revealed that Fe nanoclusters induced local symmetry breaking and charge redistribution around FeN4 sites, shifting the Fe centers toward a higher spin configuration and thereby modulating the free energy changes of the H2O2 conversion pathway. As a result, FeSA+NC showed dramatically enhanced catalase (CAT)-like activity (333.79 U mg-1) and suppressed peroxidase (POD)-like activity (38.49 U mg-1), achieving superior selectivity compared to Fe SAzymes (FeSA), which showed comparable CAT- and POD-like activities (62.39 and 60.39 U mg-1, respectively). Moreover, FeSA+NC achieved a higher superoxide dismutase (SOD)-like activity (929.27 U mg-1) than FeSA (249.68 U mg-1), enabling efficient SOD-CAT cascade. FeSA+NC effectively scavenged excessive intracellular reactive oxygen species, suppressed M1 macrophage polarization, and enhanced the therapeutic efficacy of intra-articular stem cell injection in a rat model of rheumatoid arthritis, a representative chronic inflammatory disease. This work highlights an atom-cluster synergy strategy for steering H2O2 conversion towards antioxidant pathway, offering a general design principle for safer, more controllable and more efficient nanozyme-based anti-inflammatory therapeutics.

bioengineering↗

bioRxiv2026

Evaluating Limits of Machine Learning-Assisted Raman Spectroscopy in Classification of Biological Samples

Machine learning (ML)-assisted Raman spectroscopy has become a powerful analytical tool for the classification and identification of analytes; however, technical challenges impacting its detection accuracy have not been investigated. This study explores experimental factors affecting classification performance. Among the evaluated ML models, ML algorithms show minimal impacts on classification accuracy. Instead, experimental factors, including spectral similarity between tested samples and the data quality, dominate detection performance. Increases in spectral noises and spectral similarity significantly reduce classification accuracy. In well-controlled samples with low experimental noise, ML-assisted Raman spectroscopy can discriminate lipid mixtures with a composition difference of 1.85 mol%. To assess the effect of biological heterogeneity, we analyzed single-cell Raman spectra from Saccharomyces cerevisiae strains carrying single, double, or triple gene mutations. Intrinsic cell-to-cell variability introduced substantial spectral differences, severely reducing the accuracy of multiclass classification of these genetically similar strains at the single-cell level. Averaging Raman spectra across multiple cells improved classification accuracy by reducing this spectral variability. We also assess the effectiveness of transfer learning across different Raman spectrometers, specifically by applying a ML model trained on one instrument to another Raman spectrometer. Transfer learning can be improved with proper instrument calibration, highlighting the importance of instrument standardization. Overall, our results demonstrate that data quality and spectral similarity are the primary bottlenecks in ML-assisted Raman spectroscopy. Careful attention to sample preparation, data acquisition, measurement conditions, and instrument calibration is critical to achieving robust and reliable classification performance.

bioinformatics↗

bioRxiv2026

Structural Dynamics of the Dopamine D2 Receptor with a Non-Basic Ligand

Progress in understanding protein-ligand interactions is revolutionizing drug design, especially for G protein-coupled receptors (GPCRs), which are targets for 35% of marketed drugs.1 The dopamine D2 receptor (D2R) represents a key drug target in schizophrenia and Parkinsons disease.2 While structural studies have clarified its interactions with classical ligands, the behavior of atypical, non-basic ligands like D2AAK2 remains unclear. Notably, D2AAK2 shows strong selectivity for D2R over the closely related D3R, despite identical binding pocket composition. Here, we present a cryo-EM structure of D2AAK2 bound to D2R, showing that aspartate 3.32 serves as the main anchoring point, even though the compound lacks a basic nitrogen atom. Using enhanced sampling molecular dynamics simulations and experimental approaches, we uncover a complex binding energy landscape. Simulations suggest that D2AAK2 receptor subtype selectivity between identical binding sites arises from different energy barriers for their conformational changes. Non-basic ligands offer advantages such as better brain penetration and improved pharmacokinetics.3,4 This study provides the first structural insights into a non-basic ligand targeting D2R, paving the way for developing more effective, selective drugs.

pharmacology and toxicology↗