Biology subjects

Liu, Y.

Publications and source records attributed to Liu, Y..

At least 109 records · Page 6Linked to original sources

bioRxiv2026

Redirecting carbon and electron flow in methanogenic laboratory scale anaerobic digestors with hypophosphite

In anaerobic digestion, formate is a central electron carrier linking primary and secondary fermentation to methanogenesis. Efforts to alter methane production have largely focused on directly targeting methanogens, while disruption of other trophic levels is underexplored. We recently demonstrated that hypophosphite is a naturally occurring inhibitor of formate exchange in syntrophic methanogenic systems. Here, we investigated whether intercepting formate exchange using hypophosphite can modulate methane production in a complex fermentative methanogenic system and what the longer-term consequences are for the structure and function of the microbiome. Using continuous up-flow anaerobic sludge blanket (UASB) columns fed with whey, we found that 100 M hypophosphite resulted in a transient (17 days) reduction in methane production by 20% to 50%, while carbon and electron flow was redirected towards hydrogen and volatile fatty acids. Accumulation of propionate, butyrate, branched-chain fatty acids, and not acetate indicated disruption of syntrophic formate metabolism. Following recovery of methane production in hypophosphite treated columns, we increased hypophosphite concentrations to millimolar levels and saw no repeated suppression of methane production. 16S rDNA amplicon sequencing revealed that hypophosphite treatment did not cause significant changes to microbiome composition. Methanogenic activity assays revealed a loss of formatotrophic methanogenic capacity in hypophosphite treated columns. Together, these results show that specific inhibition of formate exchange between syntrophs and methanogens decouples fermentative and methanogenic processes without altering microbiome composition with carbon and electron flow to methane ultimately redirected through hydrogen or acetate. This work demonstrates that hypophosphite can intercept syntrophic formate exchange in an engineered system and that long- term treatment with hypophosphite redirects electron flow towards electron carriers other than formate.

microbiology↗

bioRxiv2026

Novel Dissymmetric Ionizable Lipid-Assembled Lipid Nanoparticles for Delivery of Ferroptosis-Related siRNA in Diabetic Treatment

Small interfering RNA (siRNA) enables precise post-transcriptional gene silencing for refractory diseases, yet its clinical translation remains limited by the lack of safe and efficient delivery vectors. Inspired by the dissymmetric alkyl chain architecture of natural membrane phospholipids, we designed and synthesized 34 novel ionizable lipids with dissymmetric hydrophobic tails and formulated them into lipid nanoparticles (LNPs). Through systematic physicochemical and biological assessments, we established clear structure-activity relationships and identified two lead LNPs (O14-LNP, H18a-LNP) with superior endosomal escape capacity, enhanced in vivo gene silencing potency, and favorable biosafety relative to the clinical benchmark MC3-LNP. In both streptozotocin-induced and spontaneous db/db type 2 diabetes (T2D) mouse models, lead LNPs delivering ferroptosis-related siRNAs effectively ameliorated glucose and lipid metabolic disorders, restored islet function, and alleviated hepatic steatosis. This study not only lays a theoretical foundation for the rational design of novel ionizable lipids, but also validates the therapeutic potential of siRNA therapy targeting ferroptosis, providing a versatile delivery platform and targeted therapeutic strategy for the treatment of T2D.

pharmacology and toxicology↗

bioRxiv2026

Decoding the Transcriptome Dark Matter: Construction of Single-Cell Whole-Transcriptome Regulatory Atlas by dropTotal

To profile unknown ncRNAs-"dark matter" in single cells, we developed dropTotal, a high-throughput droplet-based total RNA-seq method that uses dU-modified GAT primer with temperature-ramp hybridization and droplet merge barcoding to co-detect coding and non-coding transcripts with record sensitivity (>13,500 genes/cell, including >2,000 lncRNAs and >500 sncRNAs), compatible with fresh, frozen, fixed, and FFPE tissues. Applied to ~75,000 human glioma nuclei, it captured 60,313 genes (18,681 lncRNA, 19,859 mRNAs and 6,753 sncRNAs), enabling ncRNA-driven regulatory landscape construction. In oligodendroglioma, module analysis identified recurrence-associated ncRNA-centered modules linked to therapy resistance and invasion; in glioblastoma, six cellular states showed hundreds of state-specific unannotated ncRNAs with divergent functions, from MIR222HG-mediated immune modulation to SCIRT-driven hypoxia adaptation. Alternative splicing analysis identified 428 state-specific junction markers and mapped cell-state-specific alternative splicing regulation. dropTotal offers broad application for decoding the underlying ncRNA biology and single-cell whole transcriptome regulatory mechanisms in cellular identity and disease progression.

genomics↗

bioRxiv2026

Brain Controllability and Control Energy in Gray-White Matter Fusion Network

Objective: Brain network controllability provides a framework for understanding how structural organization shapes brain dynamics, yet current models mainly rely on white-matter connectivity and may overlook the contribution of gray-matter architecture. Approach: We constructed a fusion network combining diffusion tensor imaging-derived white-matter connectivity with gray-matter morphological similarity and investigated its controllability, biological associations, heritability, phenotype prediction, and control energy. Main results: Controllability derived from the fusion network preserved key topological properties of the white-matter network and was associated with neurotransmitter systems and cerebral metabolism. Compared with the white-matter connectivity-based network, fusion-based controllability showed a systematic shift toward higher heritability, improved prediction of several individual characteristics and cognitive functions, and lower modeled control energy for activating resting-state networks. Significance: These findings suggest that incorporating gray-matter morphological information into a DTI-supported network provides a complementary structural representation for studying brain network controllability and state transitions. The lower control energy represents a model-derived transition cost and should not be interpreted as a direct measure of physiological energy expenditure.

neuroscience↗

bioRxiv2026

The devil in citizen science data: observation processes invalidate the causal inference that photovoltaic policy reduces bird diversity

Citizen science data are increasingly used to infer biodiversity change, but causal claims based on such data are credible only if sampling effort and its temporal shifts are explicitly modeled. Zhang et al. (1) used citizen science data to conclude that greater photovoltaic policy stringency, measured using the photovoltaic policy stringency index (PSI), reduced county-level bird diversity in China. We reproduced their fixed effects and instrumental variable estimates. However, the observed Shannon diversity derived from pooled citizen science records reflects both bird communities and sampling effort, which the authors' controls do not adequately capture. Accounting for observer count changed the reported statistically significant 2.10% decline in Shannon index to a nonsignificant 0.58% increase (P = 0.288) per one-standard-deviation increase in PSI, and rendered the instrumental variable estimate statistically indistinguishable from zero (P = 0.912). Yet observer count is only one of many sources of sampling bias. PSI was also associated with multiple dimensions of sampling effort, consistent with sampling effort acting as a potential mediator in the PSI-diversity chain. The sampling domain also shifted markedly from 2014 to 2023: recorded county-months increased almost 24-fold, median observer count rose from one to three, and zero-duration records declined from 57.2% to 0.17%. Without adequate adjustment, these shifts confound estimates of temporal change in observed bird diversity. Beyond its inadequate treatment of sampling effort, the original study also misinterpreted its statistical results. Although the reported R{superscript 2} values are high, they are dominated by county and year-month fixed effects, with PSI contributing a partial R{superscript 2} of only 0.048% on observed Shannon index. The PSI-photovoltaic-area correlation is also weak (r = 0.0414) and vanishes after accounting for fixed effects (P = 0.977). Furthermore, the released bird observation data contain many erroneous outliers, raising significant concerns about insufficiently rigorous data preprocessing and quality control. These results show that the released data cannot properly distinguish ecological change from sampling effort change. Robust inference from citizen science data requires checklist-level effort metadata, explicit correction for spatiotemporal sampling shifts, and close collaboration among researchers with complementary methodological and ecological expertise.

ecology↗

bioRxiv2026

A self-organized signaling hierarchy patterns the cortex during cell repair

Cells generate dynamic patterns of Rho GTPase activation to direct the subsequent patterning of Rho GTPase effectors needed to remodel the cell cortex during processes ranging from cell division to cell repair. To understand how such patterns arise, we used live cell imaging, time-resolved Rho GTPase manipulations, and a novel computational tool to study the spatiotemporal dynamics of Rho, Cdc42 and several downstream Cdc42 targets in wounded Xenopus laevis oocytes. We find that the characteristic wound-induced segregation of Rho and Cdc42 activity into concentric zones is followed by polarization of the Cdc42 zone such that Toca-1 progressively concentrates at the back of the Cdc42 zone while Arp2/3, cofilin, cortactin, and the Rho GAP p190RhoGAP progressively concentrate at the front of the Cdc42 zone, where it overlaps the Rho zone. Remarkably, the juxtaposition of Rho activity to Cdc42 is required for the polarization of p190RhoGAP, while p190RhoGAP is responsible for establishing the boundary between the Cdc42 and Rho zones. The results indicate that the characteristic segregation of the Rho and Cdc42 zones, as well as the polarization of the Cdc42 zone, arise from cortical self-organization. Further, these findings reveal a simple mechanism for hierarchical establishment of cortical patterns: recruitment of new proteins to regions of signaling compartment overlap.

cell biology↗

bioRxiv2026

Expression of immune checkpoint VISTA represents a differentiated state of cancer cells and plays a role in regulating actin cytoskeleton

Immune checkpoint blockade has revolutionized cancer therapy, but the therapeutic efficacy is limited. Clinical trials on blockade of newly identified immune checkpoints didn't show promising result, suggesting that it might be insufficient to understand the function of immune checkpoints in cancer merely in the context of immunity. Here, we found mutually exclusive expression patterns of the immune checkpoint VISTA (or VSIR) and the neural stemness factor SETDB1, an oncoprotein that promotes immunoevasion, in xenograft tumors, suggesting that cells with high VISTA expression represents a differentiated, and hence, less or non-malignant state in tumor. Non-neural differentiation factors HHEX, MYOD1 and PPARG promote, whereas oncoproteins KRAS (and the mutant KRAS(G12D)) and SOX2, both being embryonic neural factors, repress VISTA expression. This tendency can be inferred from the finding that neural stemness is the core property of cancer cell. Manipulated expression of VISTA in cancer cells generated no significant effect on cell tumorigenicity and differentiation state, but led to change in cell morphology and actin cytoskeleton. Mechanistically, VISTA regulates a key cytoskeleton regulator, WASF2, leading to the change in cell morphology, which might interfere with signal transduction of immune response. The results suggest that 1) high expression of a protein in tumor might represent a less or non-malignant state, targeting of which would leave malignant cells intact, and consequently, leading to weak or even no therapeutic efficacy, a key factor worth considering for target selection; 2) immune checkpoints might play other roles in cells that interfere with regulation of anti-tumor immunity.

cancer biology↗

bioRxiv2026

A tRNA-derived second messenger mediates antiviral defense

CRISPR-Cas systems are RNA-guided nucleases that enable prokaryotic immunity; however, some loci encode additional associated genes that cooperate with CRISPR effectors to perform diverse biological functions. Here, we uncover a CRISPR-associated kinase (CASK) system that links the recognition of target RNA to protein phosphorylation. We show that the kinase Csx33 phosphorylates Csx34 following activation of Cas13, enabling Csx34 to bind DNA in a sequence-specific manner. Together, Csx33 and Csx34 function as a transcriptional activation module that upregulates cas13 and associated genes, revealing a positive autoregulatory circuit that potentiates the immune response upon detection of foreign RNA. At the molecular level, Csx33 is activated by CCA trinucleotide RNA generated by Cas13-mediated cleavage of tRNA 3' tails, uncovering a novel linear second messenger in bacterial immunity and a previously unrecognized signaling role of collateral RNA fragments. Together, these findings establish CASK systems as a new platform for RNA sensing and for engineering programmable phosphorylation-based signaling systems.

molecular biology↗

bioRxiv2026

Dynamic inositol pyrophosphate synthesis is a targetable therapeutic opportunity in ovarian cancer.

We previously reported that the phosphate exporter XPR1 is required to prevent toxic phosphate accumulation in ovarian cancer cells. To guide therapeutic development, we sought to systematically compare potential strategies to inhibit XPR1: directly targeting the phosphate efflux channel, targeting its partner protein KIDINS220, or inhibiting the synthesis of inositol pyrophosphates (PP-InsPs), metabolites which activate XPR1. We evaluated functional domains in XPR1 and KIDINS220 using mutational scanning and found that loss of function mutations in XPR1 clustered in distinct regions throughout the protein, with the most deleterious mutations in the PP-InsP-binding domain. In contrast, loss of function mutations in KIDINS220 were infrequent and altered the localization of XPR1, consistent with a scaffolding role for KIDINS220. These data highlight the functional relevance of PP-InsPs, which we confirmed by inhibiting their synthesis using IP6K inhibitors. We demonstrate that IP6K inhibition phenocopies XPR1 inhibition across hundreds of cancer cell lines, with the mechanism of sensitivity solely due to inhibition of cellular phosphate efflux. Finally, we show that IP6K inhibitors decrease tumor burden in xenograft models of ovarian cancer, but that the rapid resynthesis of PP-InsPs requires high exposures to achieve efficacy. This study comprehensively evaluates the XPR1-dependent phosphate efflux network and reinforces the concept of directly targeting XPR1 as a precision medicine strategy to benefit patients with ovarian cancer.

cancer biology↗

bioRxiv2026

An inflammation-associated five-gene expression signature stratifies survival and immune states in lung adenocarcinoma: an integrative public-cohort analysis

Background: Inflammation and the tumor immune microenvironment contribute to lung adenocarcinoma (LUAD) progression, but the relationship among inflammation-linked transcriptional heterogeneity, patient survival, and immune-state variation remains incompletely defined. Objective: We aimed to identify inflammation-associated LUAD subtypes, derive a parsimonious survival-stratification signature, and characterize its immune and pathway context across public transcriptomic cohorts. Methods: Expression profiles and clinical data were obtained from TCGA-LUAD, GTEx normal lung, and GEO datasets GSE11969, GSE30219, GSE31210, and GSE40791. A curated set of 596 inflammation-related genes was used for consensus clustering. Differential-expression analysis, functional enrichment, univariate Cox regression, and LASSO-Cox modeling were integrated to construct a gene-expression risk score. The prognostic dataset comprised 730 cases and was randomly divided into training (n=502) and internal-validation (n=228) sets; 85 GSE30219 cases formed an external-validation cohort. Immune-cell enrichment, gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), and pan-cancer analyses were used for biological contextualization. Results: The LUAD-versus-control comparison identified 1,305 differentially expressed genes, including 498 upregulated and 807 downregulated genes. Consensus clustering resolved two inflammation-associated subtypes and 67 subtype-associated genes, of which 64 were higher and 3 were lower in Cluster 1 relative to Cluster 2. Thirty-three genes overlapped between the tumor-control and subtype contrasts. LASSO-Cox regression selected CHRDL1, FDCSP, CXCL13, CYP4B1, and S100P. The 1-, 3-, and 5-year areas under the time-dependent receiver operating characteristic curve were 0.6625, 0.6581, and 0.6658 in the training set; 0.7422, 0.6537, and 0.6761 in internal validation; and 0.6560, 0.6387, and 0.6753 in external validation. Risk groups differed across multiple T-cell, B-cell, natural-killer-cell, myeloid, dendritic-cell, macrophage, and granulocyte signatures. Positive GSEA signals included cell cycle (normalized enrichment score [NES]=2.67; adjusted P=1.42 x 10-), DNA replication (NES=2.52; adjusted P=2.52 x 10-), and mismatch repair (NES=2.20; adjusted P=1.77 x 10-). Conclusions: The five-gene expression score separated LUAD survival groups and captured coordinated proliferative and immune transcriptional states. Its moderate discrimination supports further biological and clinical validation rather than immediate clinical application.

bioinformatics↗

bioRxiv2026

AFP-R: An Open Resource Dedicated to Antifreeze Proteins

Antifreeze proteins (AFPs), lower the freezing point via thermal hysteresis activity and/or ice recrystallization inhibition, playing a crucial role in protecting organisms from freezing damage under sub-zero milieu. This property endows them with promising applications in biomedicine and agriculture, ranging from tissue-organ cryopreservation to the development of frost-resistant crops. However, the lack of comprehensive resources dedicated for AFPs hinders further progress in elucidating their functional mechanisms and advancing their applications. Here, we report AFP-R, an online resource comprising AFP-DB and AFP-Predictor. AFP-DB is a comprehensive database with manually curated proteins bearing experimentally validated antifreeze activity derived from published literature, whereas AFP-Predictor is a sequence-based machine-learning model to identify AFPs. AFP-DB stores diverse AFP-related information, including sequences, structures, post-translational modifications, taxonomy and annotations of antifreeze-activity experimental assays. It now holds 186 entries, 607 sub-entries, and 1444 experimental records. AFP-Predictor, an AFP-identification algorithm built on protein language model ESM2 (Evolutionary Scale Modeling2), is trained on data in AFP-DB and outperforms several existing models. This work offers a valuable resource for systematically dissecting the mechanisms underlying AFP antifreeze activity and will facilitate their broader applications.

bioinformatics↗

bioRxiv2026

Image-Derived 3D Blood-Brain Mechanics: Cerebral Haemodynamics, Brain Motion and In Vivo Benchmarking

Cerebrovascular pulsatility drives measurable brain tissue deformation and has been associated with ageing and a range of neurological disorders. Yet how pulsatile haemodynamic forces are transmitted through deformable cerebral arteries into the surrounding brain remains poorly understood, particularly in anatomically realistic vascular geometries. Existing computational approaches have largely treated cerebral fluid and tissue mechanics separately or relied on idealised geometries, limiting our ability to determine how vascular anatomy simultaneously governs intraluminal haemodynamics and extravascular mechanical loading. Here, we develop an image-derived three-dimensional computational framework that jointly resolves pulsatile blood flow, arterial wall deformation and surrounding brain tissue motion in representative cerebral arteries. Four arterial segments, including the middle cerebral artery, middle cerebral artery bifurcation, basilar artery and internal carotid artery, are reconstructed from high-field (5 Tesla) magnetic resonance imaging data of a healthy subject. A finite-deformation fluid-structure interaction model is established by coupling non-Newtonian blood flow, hyperelastic arterial wall and hyper-viscoelastic brain tissue. The predicted tissue response is benchmarked against in vivo magnetic resonance elastography measurements of cardiac-induced volumetric strain over a cardiac cycle. Results reveal spatially localised arterial and tissue deformation whose magnitude and distribution are strongly governed by vascular geometry and wall thickness. Among the segments examined, the internal carotid artery exhibits the largest deformation response, while reduced wall thickness increases strain transmission into the surrounding tissue. Geometrically complex regions also exhibit greater spatial heterogeneity in near-wall haemodynamic metrics. These findings demonstrate that cerebral vascular anatomy simultaneously shapes intraluminal haemodynamics and extravascular mechanical loading. By integrating image-derived vascular anatomy, coupled blood-vessel-brain mechanics and in vivo benchmarking within a unified framework, this study provides a mechanically consistent reference for healthy cerebral pulsatility and establishes a foundation for quantifying how blood-vessel-brain interactions are altered under pathological conditions.

bioengineering↗

bioRxiv2026

C. elegans Nuclear Hormone Receptor NHR-49 promotes attractive chemotaxis independently of its role in fatty acid metabolism

All organisms must sense and adapt to environmental cues to survive and thrive. In the nematode worm Caenorhabditis elegans, the nuclear hormone receptor nhr-49 is required for lipid homeostasis, stress resilience, pathogen defense, and longevity. In addition, recent studies suggest that NHR-49 controls avoidance behaviors and aversive memory to pathogenic bacteria and mitochondrial disruption, acting via its established role in fatty acid desaturation and fatty acid oxidation, respectively. However, the role of NHR-49 in neuronal signaling and behavior remains poorly understood. Here, we uncover a new role for NHR-49 in AWA neuron-mediated attractive chemotaxis. We show that nhr-49 is required for chemotaxis towards diacetyl and pyrazine, two AWA neuron-sensed compounds, but not for AWC- or ASH-mediated chemotaxis. Supplementation with unsaturated fatty acids and mutational analysis of additional genes involved in fatty acid desaturation or {beta}-oxidation reveal that these processes do not affect attractive chemotaxis; this suggests that NHR-49 mediates attractive chemotaxis independently of its role in fatty acid desaturation and oxidation. Tissue-specific expression of NHR-49 in neurons or body wall muscle is sufficient to rescue chemotaxis defects, while nhr-49 depletion in neurons alone causes chemotaxis defects. Finally, nhr-49 mutants also show defects in another behavior, the response and habituation to mechanosensory stimuli. Together, our data reveal new functions for NHR-49 in sensory responses and non-associative learning, which are distinct from its roles in aversive behaviors and memory and, notably, independent of its well-established role in lipid metabolism.

neuroscience↗

bioRxiv2026

Structural-functional calibration corrects single-neuron identity errors in volumetric calcium imaging

Volumetric calcium imaging is increasingly used to capture larger neuronal populations at higher throughput, but high-speed axial sampling can compromise single-neuron identity. Here we identify cross-plane identity duplication as a structured error in volumetric imaging: anisotropic axial blurring and plane-wise functional segmentation can repeatedly detect the same neuron across adjacent planes, creating duplicate functional nodes that inflate neuronal counts and distort network phenotypes. We developed Comprehensive Label-Guided (CLG) volumetric imaging, a structural-functional calibration framework that uses nuclear labels as stable three-dimensional identity anchors for calcium signals. CLG combines nuclear labeling, deep-learning-based 3D segmentation, anatomical registration and identity-guided trace reassignment. In larval zebrafish whole-brain recordings, CLG resolved ~30,000 redundant detections and reduced estimated neuronal counts by 37-46%. In mouse visual cortex, CLG consolidated ~40% of putative duplicates and recovered over 2,000 active neurons missed by calcium-only analysis. Across baseline and perturbed conditions, calibration stabilized graph-derived measurements of hub organization, long-range correlations and network resilience. CLG therefore defines an anatomy-constrained identity-calibration layer for reliable single-neuron-resolved volumetric imaging.

neuroscience↗

bioRxiv2026

Prior low-severity fires reduce the risk of persistent forest loss from subsequent fires

Intensifying fire regimes threaten forests globally, but the risk of persistent post-fire forest loss and its potential mitigation remains poorly quantified. We analyzed millions of wildfires worldwide from 2001 to 2024 and tracked recovery in satellite-observed forest structure and ecosystem function. Post-fire persistent forest loss, indicated by modeled non-recovery to pre-fire conditions over decadal timescales, affected 57.1% of burned forest area globally since 2001, with hotspots in Pacific temperate and southern boreal forests. We then identified 'crucial fires' as events exceeding a stringent modeled-risk probability threshold for persistent structural or functional non-recovery, with fire severity strongly predicting this loss. This severity dependence revealed a management pathway, as locations with prior low-severity fire experienced lower severity in subsequent wildfires and had lower modeled probability of becoming crucial. Under a model-based counterfactual scenario, applying the estimated severity attenuation was associated with a 7.6% reduction; the top 1% of road-accessible areas accounted for 35% of this reduction. These results provide a global framework for identifying where wildfire threatens forest resistance and where targeted low-severity fire management like prescribed fire might be used to combat global forest loss.

ecology↗

bioRxiv2026

Dietary sugar type determines the response to protein restriction in females, but not males

Low protein (LP) diets improve metabolic health in rodents and humans. In rodents, LP diets are typically implemented by replacing protein with carbohydrates like sucrose or cornstarch, keeping diets isocaloric. However, humans can choose from many different types of carbohydrate, and how dietary carbohydrate quality - the precise composition of the dietary sugars - impacts the response to dietary protein remains largely unexplored. Here, mice were fed control (21% protein) or LP (7% protein) diets with four different carbohydrate sources: sucrose, a 1:1 glucose/fructose mixture, glucose, or fructose. While LP diets improved metabolic health across all groups in male mice, carbohydrate quality also significantly altered specific health outcomes, with fructose-fed mice having the lowest body weight and adiposity of all control diets. In female mice, responses to LP diets were influenced by carbohydrate quality, with certain sugars inducing a stronger metabolic response to LP diets than previously seen. Finally, in female APP/PS1 mice, a model of Alzheimer's disease, we find that although LP diets reduce A-beta; plaque burden irrespective of carbohydrate type, dietary sugar type does influence spatial memory. Together, these results demonstrate that while dietary protein is a critical determinant of metabolic and neurological health, carbohydrate quality influences these outcomes in a sex-specific manner.

physiology↗

bioRxiv2026

Outer Pore Collapse as a Potential Mechanism of Partial Loss of Pain in Nav1.7 M899I

Complete loss of function of the voltage-gated sodium channel subtype Nav1.7, encoded by SCN9A, results in congenital insensitivity to pain. Here, we investigate a previously identified variant, M899I, in which methionine at position 899 is substituted by isoleucine. This variant was originally described in a Chinese patient with loss of pain. We confirmed membrane expression of the mutant channel in HEK cells using extracellular HA-tagging; however, no sodium currents were detectable from the variant in patch-clamp recordings. The M899I substitution is located within a tightly packed hydrophobic region of the pore module. Introducing the corresponding variant into Nav1.2 and Nav1.5 similarly abolished channel function, underscoring the high conservation and functional importance of this residue. To further investigate the underlying mechanism, we combined in-silico coarse-grained molecular dynamics simulations with in-vitro electrophysiological analysis. Our simulations predicted that the M899I substitution induces collapse of the outer pore, substantially reducing both pore radius and volume. Substitution with other hydrophobic residues was likewise predicted to alter pore geometry and, consequently, ion permeation to varying degrees. Whole-cell voltage-clamp recordings validated these predictions, with observed current densities closely correlating with the extent of pore collapse predicted in silico. Together, our findings establish pore collapse as a mechanism underlying disease-relevant loss-of-function variants in Nav1.7 and suggest that this principle may extend to other sodium channel subtypes. Moreover, our results demonstrate that in-silico molecular dynamics approaches can reliably predict structural and functional consequences of channel mutations, as confirmed by in-vitro electrophysiological data.

biophysics↗

bioRxiv2026

An AI System for Autonomous Algorithm Evolution in Drug Development

Artificial intelligence (AI) is increasingly permeating the drug development pipeline. Numerous algorithms for accelerating this multi-stage and multi-task process have been constructed, which depends heavily on expert design and labor-intensive task-specific optimization. Given that AI-driven acceleration of drug development is recognized as a cumulative, often synergistic, effect across multiple stages, the autonomous evolution of existing algorithms across the entire pipeline is demanded to achieve a holistic advancement. Here, we present DrugEvolve, a multi-role large language model system for systematic and autonomous algorithm evolution in drug development. DrugEvolve realizes a closed-loop evolution process by incorporating Researcher, Engineer, and Analyst domains, and enables an iterative design, implementation, evaluation, and refinement of algorithm by leveraging scientific knowledge and accumulated evolutionary experience. Across eleven representative tasks spanning target identification, drug discovery, preclinical study, and clinical trial, DrugEvolve autonomously evolved the corresponding task-specific algorithms and achieved substantial performance enhancement on 120 benchmark test sets. Moreover, it showed robust generalizabilities across heterogeneous data modalities (ranging from biological sequence and graph to molecular topology and textual language), and realized gains in both predictive and generative tasks. Collectively, this AI system can serve not only as an algorithmic infrastructure for drug development, but also as a transferable paradigm for broader scientific domains.

pharmacology and toxicology↗