Biology subjects

Xu, Q.

Publications and source records attributed to Xu, Q..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

ProteinFlux: accurate, rapid and scalable generative prediction of protein dynamics driven by post-translational modifications

The function of proteins, the building blocks of life, in health and disease depends not only on their 3D-conformational states but most importantly on the dynamic transition between states controlled by a wide array of post-translational modifications (PTMs). Recent major advances have been made in our ability to predict static 3D structures; however, understanding and predicting the impact of PTMs on protein conformational dynamics remains a major question and challenge in the field. Molecular dynamics (MD) simulation remains the major computational approach for studying protein dynamics. However, the high computational cost, lack of integration of PTMs as conditioning inputs and inefficient generation of continuous protein dynamics largely precludes PTM-regulated conformational dynamics and the study of slow conformational processes. To address this critical bottleneck, we developed ProteinFlux, a flow-matching generative framework that links PTM-conditioned conformational dynamics to evolutionary constraints encoded by PTM sites. Evolutionary information plays a critical role in capturing conformational dynamics beyond sequence identity, and PTM sites inherently encode evolutionary constraints critical to protein functional regulation. We therefore built FluxSite, a dual-modal PTM site predictor that integrates sequence evolutionary information and 3D structural features to generate a continuous conditional signal encoding conservation and functional importance for each predicted site. FluxSite achieves robust generalization across 18 PTM types and 30 disease-associated proteomes. ProteinFlux generates phosphorylation-conditioned, all-atom conformational trajectories across diverse protein fold classes, faithfully reproducing both thermodynamic properties such as free energy landscapes and kinetic features such as conformational transition pathways. It outperforms state-of-the-art predictors while achieving inference speeds several orders of magnitude faster than traditional MD. In addition, we introduce DynaMo-phos, a benchmark dataset of phosphorylated protein MD simulations. Together, ProteinFlux, FluxSite and DynaMo-phos provide a scalable, high-throughput platform for elucidating PTM-driven conformational mechanisms, with potential applications across allosteric drug design, functional annotation of disease-associated modifications and mechanism-guided therapeutic development.

bioinformatics↗

bioRxiv2026

Cell membrane proteome profiling uncovers molecular signatures and GPCR regulators underlying diet-induced obesity and exercise-mediated adaptation

Cell membrane proteins (CMPs), notably G protein-coupled receptors (GPCRs) and receptor tyrosine kinases (RTKs), represent the largest class of druggable targets. Despite their therapeutic importance, how the CMP landscape is systemically remodeled during metabolic disease progression and in response to exercise remains poorly understood. Here, we constructed the most comprehensive CMP proteome atlas to date across 22 male mouse tissues and established the first multi-tissue map of GPCR-associated protein hormones/prohormones. Integrated CMP proteomic and transcriptomic analysis revealed that diet-induced obesity and its progression to type 2 diabetes remodel the CMP repertoire in patterns distinct from those induced by exercise. We found that numerous GPCRs and RTKs critical for energy homeostasis are dysregulated during obesity in a tissue-specific manner, and these alterations are reversed to varying extents by exercise training. Importantly, our CMP-centric omics study identified two parathyroid hormone receptors (PTHRs) in the hypothalamus as negative regulators of feeding and body weight. Genetically silencing these hypothalamic PTHRs led to severe obesity even on a chow diet and markedly blunted exercise-induced weight loss. Collectively, our study provides not only new insights into systematic CMP regulation underlying metabolic deterioration versus exercise adaptation, but also nominates potential receptor targets for obesity management.

biochemistry↗

bioRxiv2026

A global metagenomic atlas uncovers ubiquitous biosynthetic potential linked to adaptation in extreme environments

Extreme environments impose severe physicochemical stresses that drive microorganisms to evolve specialized survival strategies. Microbial secondary metabolites determined by biosynthetic gene clusters (BGCs) are recognized as important mediators of microbial adaptation to environmental stress. However, their ecological roles, particularly habitat-dependent preferences across different environments, remain poorly understood. Although extreme environments provide opportunities to mine microbiomes for unique adaptations, such research is hampered by a lack of systematic overview of its genomic diversity, BGC diversity, and the relationships between them. Here, we constructed a standardized extremophilic genomic catalogue (SEGC) from 1,462 metagenomic samples spanning seven representative extreme habitats. The catalogue comprised 54,661 metagenome-assembled genomes representing 21,805 species, 66.1% of which were previously uncharacterized. With this catalogue, we identified 162,855 BGCs distributed across 81.5% of MAGs. Gene cluster family analysis showed the strong habitat dependence largely explained by species-level habitat specificity. Terpene biosynthetic pathways illustrated habitat-linked adaptive strategies, with hopan-22-ol biosynthesis enriched in acid mine, deep sea and hydrothermal plume environments, while retinal-based phototrophy predominated in cryosphere and saline-alkaline habitats. Metatranscriptomic analyses supported in situ activity of these pathways. In conclusion, we presented a global atlas of biosynthetic potential across extreme-environment microbiota and revealed habitat-dependent patterns of secondary metabolism linked to microbial survival.

microbiology↗

bioRxiv2026

ECHOS enables spatial epigenome profiling at subcellular resolution

Biological structures and the epigenome are intertwined. For example, complex tissues are often the combined products of various groups of spatially patterned cell types with distinct epigenetic states. Furthermore, chromatin at various subnuclear locations within a cell often differ in their epigenetic properties. Thus, a systematic understanding of the relationship between the epigenome and its spatial distribution across biological scales would inform tissue and cellular functions as well as gene regulatory mechanisms. Yet, spatially resolved epigenome profiling--particularly at subcellular resolution--remains technically challenging. Here, we present Epigenetic CUT&Tag via High-resolution Optical Selection (ECHOS), a platform that combines high-resolution imaging and high-throughput sequencing to enable precise, spatially targeted epigenetic profiling across biological scales. At the cellular scale, ECHOS generates high-quality DNA-binding protein and histone modification datasets that show strong concordances with datasets from ChIP-seq and CUT&Tag experiments. Further optimization of ECHOS (ECHOS+) enables the characterization of the histone modification landscape of chromatin at the sub-micron resolution. Using ECHOS+, we revealed distinct gene regulatory logics at different layers of human ectocervical epithelium. We also showed that micronuclei--small nucleus-like structures formed by mitotic errors--exhibited a different epigenetic state from the same chromosome regions on the intact nuclei. Finally, we found that human aging altered the epigenetic state of the inactive X chromosome located in a subcellular nuclear structure called the Barr body, which may contribute to genes escaping X chromosome inactivation during female aging. Together, ECHOS and ECHOS+ represent a scalable and generalizable framework for spatial epigenomic analyses, with broad potential applications in various domains of biology.

genetics↗

bioRxiv2026

Reduced LACTB expression in myeloid cells is associated with elevated succinylcarnitine levels and reduced Alzheimers disease risk.

BackgroundLactamase {beta} (LACTB) is a serine {beta}-lactamase-like mitochondrial enzyme associated with cancer progression, obesity, and lipid metabolism. LACTB is located in an Alzheimers Disease (AD) risk locus and has been associated with AD in a proteomic study. MethodsWe performed Mendelian Randomization (MR) analysis to estimate the association between LACTB expression, succinylcarnitine levels, and AD risk. We generated LACTB knock-down (KD) THP1 macrophages, LACTB knock-out (KO) iPSC-derived microglia and LACTB enzymatically-dead (ED) mice. The impact of LACTB loss-of-function in myeloid cells was characterized via transcriptomics, metabolomics, lipidomics, and functional assays. Finally, human LACTB KO microglia precursors were xenotransplanted into the brains of mice with amyloid pathology to assess in vivo interactions with amyloid plaques. ResultsMR analyses revealed that lower LACTB expression in myeloid cells may lead to reduced AD risk and higher levels of succinylcarnitine, a metabolite associated with AD risk. We identified LACTB as a primary enzyme responsible for succinylcarnitine hydrolysis. Transcriptional and functional studies showed that loss of LACTB enhances OXPHOS, and reduces protein synthesis and triglycerides. LACTB expression was upregulated following interferon or TNF stimulation, and its loss modified efferocytosis- related functions under inflammatory conditions. In vivo, xenotransplanted human LACTB KO microglia exhibited enhanced association with amyloid plaques. ConclusionsOur findings define a previously unrecognized axis linking LACTB and succinylcarnitine to myeloid cell function and AD susceptibility. Given the druggability of LACTB and the potential for succinylcarnitine to serve as a translational biomarker, this enzyme represents a promising therapeutic target for modulation of neuroinflammation in AD.

neuroscience↗

bioRxiv2026

Eubiota: Modular Agentic AI for Autonomous Discovery in the Gut Microbiome

The gut microbiome regulates many aspects of human biology, including immunity and inflammatory diseases, yet mechanistic discovery and translation remain constrained by fragmented workflows and manual hypothesis integration. Here, we present Eubiota, an open-source modular agentic framework that decomposes microbiome inquiry using specialized agents for planning, execution, verification, and grounded synthesis. Coordinated through shared memory and domain-specific tools, Eubiota employs reinforcement learning to optimize multi-turn reasoning, achieving 87.7% benchmark accuracy and outperforming GPT-5.1 by 10.4%. Across four case studies, Eubiota enabled end-to-end discovery with experimental validation. Screening nearly 2,000 bacterial genes, Eubiota identified the uvr-ruv DNA repair axis as a fitness determinant under inflammatory stress, validated using transposon mutants and IBD metagenomes. It further designed a four-strain consortium that attenuated colitis severity in mice and generated a commensal-sparing antibiotic cocktail, demonstrating its utility in addressing community-level design challenges at cellular and molecular levels. Finally, Eubiota discovered diet-associated metabolites that suppress NF-{kappa}B signaling. Together, these results establish Eubiota as a scalable, tool-grounded scientific copilot for mechanistically driven microbiome discovery.

bioinformatics↗

bioRxiv2026

Defining the Active Conformation of Typical Protein Kinases Domains from Substrate-Bound PDB Structures Enables Active-State AlphaFold2 Models for All 437 Human Catalytic Protein Kinases

Humans have 437 catalytically competent protein kinase domains with the typical kinase fold, similar to the structure of Protein Kinase A (PKA). The active form of a kinase must satisfy requirements for binding ATP, magnesium, and substrate. From structural bioinformatics analysis of 248 crystal structures of 54 unique substrate-bound kinases, we derived structural criteria for the active form of typical protein kinases. We include well-known requirements on the DFG motif of the activation loop and the N-terminal domain salt bridge, but also on the positions of the N-terminal and C-terminal segments of the activation loop that must be placed appropriately to bind substrate. With these criteria, only 130 of the 437 human catalytic protein kinases (30%) are in the Protein Data Bank in their active form. Because the active forms of catalytic kinases are needed for understanding substrate specificity and the effects of mutations on catalytic activity in cancer and other diseases, we used AlphaFold2 to produce models of all 437 human protein kinases in the active form. This was accomplished with templates from the PDB that resemble substrate-bound structures, shallow multiple sequence alignments of orthologs and close paralogs of the query protein, and application of the active-kinase criteria to the output models. We selected models for each kinase based on intramolecular ipSAE scores of the activation loop residues of these models, demonstrating that the highest scoring models have the lowest or close to the lowest RMSD to 29 non-redundant substrate-bound structures in the PDB. A larger benchmark of 117 active kinase structures with solved activation loops in the PDB shows that 71% of the highest scoring AlphaFold2 models had backbone RMSD < 1.0 [A] to the benchmark structures and 92% were within 2.0 [A]. Models for all 437 catalytic kinases are available at https://dunbrack.fccc.edu/kincore/activemodels. We believe they may be useful for interpreting mutations leading to constitutive catalytic activity in cancer as well as for templates for modeling substrate and inhibitor binding for molecules which bind to the active state.

bioinformatics↗

bioRxiv2026

Microbiome depletion rejuvenates the aging brain

Aging is associated with cognitive decline and increased vulnerability to neurodegeneration driven by an array of molecular and cellular changes like impaired vascular integrity, demyelination, reduced neurogenesis, and chronic inflammation. Recent studies implicate the gut microbiome as a modulator of brain aging, but the underlying mechanisms remain elusive. Here, we show that depleting the gut microbiome by administering antibiotics to aged mice induces widespread molecular and structural rejuvenation in the brain. Our transcriptomic analyses by single-nucleus RNA sequencing revealed pronounced transcriptional shifts across multiple brain cell types. We confirmed that antibiotic treatment improves vascular density, promotes myelination, enhances neurogenesis, and reduces microglial reactivity. Functionally, microbiome-depleted mice showed improved hippocampal memory performance. Analyses of brain and plasma cytokine levels showed a decrease in several pro-inflammatory factors post-treatment and identified candidate factors, including the chemokine eotaxin-1. Inhibiting eotaxin-1 alone can reverse several aspects of brain aging. Our findings demonstrate that age-associated microbial inflammation contributes to brain aging and that its attenuation can restore youthful features at the molecular, cellular, and functional levels. Targeting the gut microbiome or its circulating mediators may therefore represent a non-invasive approach to promote brain health and cognitive resilience in aging.

neuroscience↗

bioRxiv2026

Machine Learning Guided Optimization of an Oral Microemulsion System: A Bayesian Optimization Approach

Oral microemulsions are one drug delivery system often implemented to improve intestinal permeability and oral bioavailability of poorly-water soluble drugs. They also present several practical advantages including high patient compliance and simplified manufacturing methods which contribute to their promise as marketable drug products. Despite these advantages, however, the microemulsion formulation development process is extremely time consuming and resource intensive, typically involving extensive screening of components and excessive preliminary trials in order to achieve stable formulations. As a result, MEs are often suboptimal in their therapeutic performance, and there is an unmet need for improved methods to streamline microemulsion formulation design. In this work, a batch Bayesian Optimization strategy was used to design a subset of unique in-specification microemulsions with highly optimized physicochemical properties in five iterations containing batches of five experiments. A two-phase modeling approach was developed to achieve this goal and allowed for navigating a complex experimental design space, including multiple oils, surfactants, cosurfactants, and processing parameters with a training dataset consisting of 22 experiments. As a result of this study, five high-performing blank microemulsions were identified, and four of them exhibited physical stability upon storage for up to 30 days. Further, when loaded with two different model drug candidates, three of the microemulsions achieved high drug loading, acceptable stability and improved in-vitro permeability, highlighting their promise for potential translation to later stages of development.

bioengineering↗

bioRxiv2025

PARP10 condensation inhibits viral infection via targeting NAD+ homeostasis

ADP-ribosylation is a critical post-translational modification mediated by diphtheria toxin-like ADP-ribosyltransferases (ARTDs). The human ARTD family comprises 17 members that catalyze either poly- or mono-ADP-ribosylation. However, the functions and regulatory mechanisms of many ARTD proteins remain poorly understood. Here, we uncover an antiviral role for PARP10 through its ability to form biomolecular condensates. Viral infection triggers PARP10 condensation, a process driven by multivalent homotypic interactions among the structured domains. We show that mono-ADP-ribosylation of PARP10 suppresses its condensation, serving as a negative feedback mechanism that regulates condensate dynamics and protein stability. PARP10 condensates exhibit enhanced enzymatic activity, leading to decreased NAD+ levels and disruption of NAD+ homeostasis, ultimately inhibiting viral replication. Our findings establish PARP10 condensation as a novel mechanism for ARTD enzyme compartmentalization, with significant implications for innate immunity and host defense.

cell biology↗

bioRxiv2025

The natural flavonoid dihydromyricetin targets senescent cells via PRDX2 and alleviates age-related diseases

Aging is a preeminent risk factor for chronic diseases, with cellular senescence as one of the major hallmarks and an effective target to delay, prevent or alleviate age-related disorders. Here we report in vitro screening outputs from a natural medicinal agent (NMA) library, wherein dihydromyricetin (DMY), a natural flavonoid, showed senotherapeutic potential. DMY protected senescent fibroblasts from further DNA damage and attenuated the senescence-associated secretory phenotype (SASP), acting as a senomorphic agent. Proteomics suggested that DMY promotes nuclear translocation of peroxiredoxin 2 (PRDX2), a reactive oxygen species (ROS) scavenger, facilitating DNA repair in senescent cells. In prematurely aged mice, DMY administration mitigated tissue aging changes and age-related physiological decline. In anticancer regimens, DMY improved outcomes of chemotherapy. However, DMY demonstrated senolytic activity against senescent microglial cells, wherein basal PRDX2 expression remains low, by impairing mitochondrial function to promote ROS-mediated apoptosis. In mice developing an Alzheimers disease (AD)-like state, DMY eliminated senescent microglial cells from amyloid {beta}-protein (A{beta}) plaques, alleviating A{beta}-associated pathological phenotypes. Together, our study proposes DMY to be a natural senotherapeutic agent representing a therapeutic solution for mitigating age-related morbidities including but not limited to cancers and AD.

cell biology↗

bioRxiv2025

PI3Kdelta promotes T cell effector differentiation and plasticity during chronic infection

Persistent antigen exposure in chronic infections and cancer leads to a progressive state of T cell dysfunction known as exhaustion, which represents a major barrier to effective immune control, but allows antigen-specific T cells to persist. Understanding signaling pathways that mitigate exhaustion and reinvigorate CD8+ T cell effector function is a key goal for immunotherapeutic strategies. Here, we show that an activating mutant of phosphoinositide-3-kinase {delta} (PI3K{delta}) led to a reduction of FoxO1-dependent TCF-1+ stem-like progenitor CD8+ T cells that are required for sustaining antigen-specific T cells in response to chronic viral infection. Nonetheless, mice expressing activated PI3K{delta} maintained CD8+ T cell responses that were skewed instead towards effector-like cells in a FoxO1-independent manner, associated with an amplified IL-21-STAT3 response axis and improved viral control. Activated PI3K{delta} limited TOX expression, prevented epigenetic changes associated with T cell exhaustion, and promoted effector differentiation and function from both progenitor stem-like cells and cells with an exhausted phenotype. Together, this work uncovers a key role for PI3K{delta} activation in shaping the balance and plasticity between effector function and exhaustion while promoting T cell persistence during chronic infection, providing insight for immunotherapeutic strategies.

immunology↗

bioRxiv2025

Neuronal APOE4 reduction with an APOE-I3-targeting ASO protects against neurodegeneration and neuroinflammation in an Alzheimer's disease mouse model

Apolipoprotein E4 (APOE4) is the strongest genetic risk factor for late-onset Alzheimers disease (AD). Within the central nervous system (CNS), APOE is produced by a variety of cell types, with differential roles in AD pathogenesis. Studies have shown that APOE4 produced by neurons plays a central role in promoting the development of major AD pathologies, including p-tau accumulation, neuroinflammation, and neurodegeneration, highlighting its role as an upstream initiating factor that affects other cell types and downstream AD-related pathologies. Here, we demonstrate that antisense oligonucleotides (ASOs) targeting APOE-I3, a neuron-specific splicing variant of APOE mRNA, effectively reduce APOE expression in neurons in vitro and in vivo. Treating PS19 tauopathy mice expressing APOE4 with this APOE-I3-targeting ASO reduces neuronal APOE4, rescues neurodegeneration, and diminishes neuroinflammation. Strikingly, the extent of neuronal APOE4 reduction predicts the efficacy of rescuing neurodegeneration. Single nucleus RNA-sequencing demonstrated that APOE-I3-targeting ASO treatment decreases disease associated neuronal and glial subtypes and increases a disease-protective microglial subtype. These findings suggest that preferential knockdown of neuronal APOE4 with an APOE-I3-targeting ASO protects against key hallmarks of AD pathology, elucidating a potential therapeutic approach for treating APOE4-driven AD.

neuroscience↗

bioRxiv2025

GPR34 regulation of disease-associated microglial states and responses to physiological stimuli

Expression of the G protein coupled receptor GPR34 is highly enriched in microglia and has been reported to be downregulated in several brain disease contexts, including Alzheimers disease (AD) and multiple sclerosis (MS). GPR34 function is poorly understood, as is its role in regulation of microglial states. Using RNA-sequencing, we find that microglia from Gpr34 knockout (KO) mouse brains exhibited a transcriptomic shift toward disease-associated microglia (DAM) and inflammatory profiles, partially resembling the microglial phenotype seen in 5xFAD AD model mice. Moreover, when Gpr34 KO mice were crossed with 5xFAD mice, the DAM transcriptional profile of microglia and glial pathology were further enhanced beyond the already robust DAM signature driven by 5xFAD alone. This occurred without affecting amyloid plaque burden. Human stem cell-derived microglia (iMGLs) lacking GPR34 showed reduced calcium (Ca{superscript 2}) and phosphorylated ERK (pERK) signaling in response to stimulation with known GPR34 agonists (lyso-phosphatidylserine (lysoPS) and myelin), as well as transcriptomic changes in immune regulation and cell proliferation related pathways. Interestingly, GPR34 KO iMGLs were selectively impaired in phagocytosis of myelin but not amyloid-{beta} (A{beta}) or E. coli, and showed a diminished transcriptional response elicited by myelin. Together, these findings suggest that GPR34 is important for maintaining microglia in a homeostatic state, promotes phagocytosis of and transcriptional response to myelin, and limits microglial activation in neurodegenerative disease conditions.

neuroscience↗

bioRxiv2025

An integrated platform for high-throughput phenospace learning of 3D multilineage organoid systems

Complex multilineage organoid systems lack quantitative phenotyping methods preserving spatial architecture at high throughput. Current approaches compromise biological complexity, spatial resolution, or robust homogeneous multilineage assembly. We establish an integrated experimental-computational platform for high-throughput spatial phenotyping of multilineage organoids through developing a modular tumoroid culture system incorporating pancreatic ductal adenocarcinoma (PDAC) cells and cancer-associated fibroblasts (CAFs) in 384-well format with multiplexed whole-mount imaging. We developed Phenocoder, a machine learning framework combining conditional variational autoencoders with spatial graph analysis to extract multiscale organoid features. Rigorous validation demonstrates robust performance in PDAC tumoroids. The platform identifies pathway modulators that disrupt the fibrotic microenvironment and discovers stroma-dependent vulnerabilities, undetectable in monocultures. Extending to immuno-competent tumoroids, we assess fibrosis modulators in combination with T cell bispecific antibodies, identifying treatments that enhance immune cell proliferation and infiltration inducing cancer cell death, validated in patient-derived explants. This platform establishes a generalizable framework for multilineage organoid phenotyping.

cancer biology↗

bioRxiv2025

A mouse model of classical trigeminal neuralgia via intradural compression of the trigeminal nerve

IntroductionTrigeminal neuralgia (TN) is a debilitating orofacial pain condition that adversely affects quality of life. Although heterogeneous, the most common form of TN is classical TN, characterized by paroxysmal bouts of pain in response to otherwise innocuous stimuli. It is believed that classical TN results from neurovascular compression of the trigeminal nerve. However, the underlying pathophysiology of TN is not well understood, thus limiting the development of targeted therapies. Current animal models lack translational relevance, particularly in their inability to replicate intradural nerve root compression, a core anatomic component of TN. MethodsWe developed a TN mouse model that achieves intradural nerve root compression via a retro-orbital approach confirmed by anatomic dissection and magnetic resonance imaging. To assess behavioral outcomes, we measured orofacial pain through facial wiping and interaction with a reward stimulus. Pharmacological responsiveness was tested using carbamazepine administration. Mechanistic studies included calcium imaging of trigeminal ganglia (TG), electrophysiologic recordings to measure resting membrane potential and rheobase, and immunohistochemical analysis of the TG. ResultsThe model elicited orofacial neuropathic pain, substantiated by increased facial wiping and reduced interaction with a reward stimulus, behaviors that suggest both spontaneous and evoked pain. Carbamazepine attenuated these behaviors, suggesting pharmacologic relevance to current TN treatment. Calcium imaging showed heightened spontaneous activity in the TG, and electrophysiologic recordings revealed an increased resting membrane potential and a reduced rheobase. Finally, immunohistochemical studies showed infiltration of CD45+ cells, demyelination and an increase in CGRP expression in the TG, supporting the presence of neuroinflammation after nerve root compression. ConclusionThese findings show that our approach replicates the anatomy and clinical presentation of classical TN in humans. This model may represent a new and robust platform for future mechanistic studies of TN and subsequent preclinical evaluation of therapies in mice.

neuroscience↗

bioRxiv2025

The Human-In-the-Loop Drug Design Framework with Equivariant Rectified Flow

Advancements in AI-based drug design often face obstacles due to incomplete datasets, hindering progress to clinical trials. Human experts bring invaluable expertise and nuanced contextual understanding to drug design. There are two main difficulties in integrating human knowledge into the drug development process. First, human annotations are costly, and traditional machine learning algorithms require a large number of samples to be effective. Second, human experts are unable to accurately describe their expertise using natural language, nor can they precisely specify what kind of molecule is needed before seeing the generated molecules. To address these problems, we propose a new platform, called HIL-DD, for experts to infuse their experience by selecting molecules generated by AI that meet their criteria, or discarding those that do not. The core generative technology utilizes an Equivariant Rectified Flow Model (ERFM), which offers faster generation speeds than conventional diffusion models, enabling efficient human-AI collaboration. More importantly, we provide a user-friendly interface to ensure smooth and effective collaboration between human experts and AI systems. Rigorous experiments demonstrate that our system can produce 3D molecules that align with expert expectations in minimal interactive sessions. These generated molecules maintain drug-like qualities comparable to those created by current state-of-the-art models.

bioinformatics↗

bioRxiv2025

Gut Microbiota-derived Adenosine Determines the Efficacy of Electroconvulsive Therapy for Depression

Electroconvulsive therapy (ECT) is a final procedure for major depressive disorders (MDD). However, the effectiveness of ECT in treating MDD patients varies. Here we identified gut microbiota as a potential restraining factor of ECT efficacy. By using a 5-day electroconvulsive shock (ECS) in depression mouse model of chronic restraint stress (CRS), it was observed that the antidepressant effect of ECS was suppressed after antibiotics (ABX)-induced microbiota dysbiosis, which also resulted in elevated c-Fos expression of CRH neurons in paraventricular nucleus of hypothalamus (PVN) and increased serum corticosterone levels after ECS. Metabolomic analysis revealed the critical involvement of microbiota associated purine metabolism, and the supplement of gut microbiota-derived adenosine was able to recover the antidepressant effect of ECS in ABX-treated CRS mouse model. Based on the neural tracing from colon to brain and the immunofluorescence staining, it was surmised a gut-brain axis originated from Adora1-expressing cells in colon mediate this biological process. Furthermore, adenosine supplement alleviated the further deterioration of post-ECS memory loss and impairment of synaptic plasticity induced by ABX-treatment as well. Our findings suggest a potential role of microbial adenosine metabolism in ECT efficacy determination and side effect protection, highlights potential application of adenosine supplement in antidepressant therapies of those depression patients with microbiota dysbiosis.

systems biology↗