Biology subjects

Zhang, B.

Publications and source records attributed to Zhang, B..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Conditional Deletion of All Neurexins Defines Diversity of Essential Synaptic Organizer Functions for Neurexins

Presynaptic neurexins are key regulators of synapse properties that arguably represent the best-studied synaptic adhesion molecules. Despite thousands of papers, however, no direct comparison of overall neurexin functions in different types of synapses is available. A decade ago, we provided such an analysis but we recently retracted this paper because four images contained microduplications that, although without discernible impact on the paper's conclusions, could not be corrected. As a result, the scientific community lost access to primary data that established the fundamental principle that neurexins perform profoundly different functions in different types of synapses. In the present study, we have therefore reanalyzed the original raw data and expanded their conclusions with new experiments to document, in a single study, the basic contributions of neurexins to different synapses. We used triple conditional knockout mice targeting all neurexins except for Neurexin-1r and applied neuron-specific manipulations combined with slice electrophysiology, two-photon Ca2+-imaging, and immunohistochemistry. With this approach, we focused on excitatory climbing-fiber synapses in the cerebellum and on inhibitory synapses formed by parvalbumin- or somatostatin-positive neurons in the cerebellum, hippocampus, and medial prefrontal cortex. Our results show that pan-neurexin deletions produce dramatically different phenotypes in synapses, ranging from modest to massive impairments in synapse assembly (climbing-fiber and parvalbumin-positive synapses) to severe but selective decreases in action potential-induced presynaptic Ca2+-transients (somatostatin-positive synapses). Thus, neurexins perform powerful but distinct context-dependent roles in different synapses that shape the brain's circuits.

neuroscience↗

bioRxiv2026

A multi-agent workflow converts CAR-T patient evidence into experimentally testable hypotheses

Clinical studies of chimeric antigen receptor (CAR)-T therapy generate diverse molecular and clinical evidence that remains fragmented across publications, public repositories and patient-derived datasets, limiting systematic therapeutic discovery. Here we present BioPathfinder, an evidence-guided multi-agent workflow for closed-loop biomedical discovery. BioPathfinder constructs a provenance-aware knowledge resource linking publications with patient single-cell RNA sequencing (scRNA-seq) datasets and clinical metadata, and uses role-specialized large language model agents to generate, review and prioritize diverse, falsifiable and dataset-aware mechanistic hypotheses for computational and experimental validation. Applied to a curated corpus of CAR-T-treated patient studies and matched scRNA-seq datasets, BioPathfinder identified candidate mechanisms underlying CAR-T persistence, dysfunction and therapeutic resistance. The workflow prioritized the hypothesis that genes associated with an NK-like transition programme could be targeted to reduce CAR-T exhaustion and improve persistence. Analysis of patient scRNA-seq datasets showed enrichment of this programme in exhausted post-infusion CAR-T cells. Virtual perturbation prioritized transition-associated receptor genes, including KLRC1, KLRD1 and KLRG1, and expert review selected KLRC1, encoding NKG2A, for experimental validation. In vitro and in vivo chronic-stimulation models showed that NKG2A marked activated, exhaustion-associated CD8 CAR-T cells, whereas NKG2A blockade enhanced antitumour activity and persistence-associated functional readouts in vivo. BioPathfinder establishes a generalizable framework that transforms fragmented clinical single-cell evidence into experimentally validated therapeutic hypotheses, providing a scalable strategy for AI-guided biomedical discovery. HIGHLIGHTSO_LIBioPathfinder integrates fragmented CAR-T clinical studies, patient scRNA-seq datasets and metadata into a provenance-aware evidence resource for AI-guided hypothesis discovery. C_LIO_LIA multi-agent workflow generates, critiques and prioritizes diverse, falsifiable, dataset-aware mechanisms underlying CAR-T persistence, dysfunction and therapeutic resistance. C_LIO_LIBioPathfinder prioritizes KLRC1/NKG2A as a therapeutic target, and experimental validation demonstrates that NKG2A blockade enhances CAR-T persistence and antitumour function. C_LI

bioengineering↗

bioRxiv2026

Real-time mass defect-driven prediction of glycopeptide precursors enables enrichment-free serum glycoproteomics

Glycopeptide enrichment remains a cornerstone in glycoproteomics, but bias and reproducibility issues continue to hinder biological insight and clinical translation. Employing curated glycoproteomics datasets and machine learning, we trained a glycopeptide classifier to recognize N-glycopeptide precursors through mass defect signatures. Integration of the classifier into a data-dependent acquisition framework facilitated real-time prediction of N-glycopeptides from human serum and revealed sex differences in murine plasma fucosylation opening avenues for enrichment-free glycoproteomics.

bioinformatics↗

bioRxiv2026

Multimodal computational framework identifies B cell convergence in autoimmunity and ageing

Identification of the origin of pathogenic immune cells is crucial for therapeutic interventions and diagnosis but pseudotime methods struggle to trace immune cells accurately. Current trajectory inference methods for B cell development and response in health and disease either ignore or underutilize antigen receptor sequence information, limiting their ability to resolve developmental pathways, particularly for pathogenic populations. Widely used methods such as Monocle 3 reconstruct developmental paths from transcriptomic similarity alone, discarding the features from immune receptors. Dandelion has combined the immune receptor features with transcriptomics but it struggles to simulate the trajectory path of B cells. Here we present ClonoTrace, a computational framework that integrates BCR sequence features with transcriptomic trajectory inference through gated fusion of multimodal embeddings. In fetal B cell development and germinal centre development, ClonoTrace achieves higher trajectory inference accuracy than Monocle 3 and Dandelion. Applied to systemic lupus erythematosus, ClonoTrace identifies memory B cell extrafollicular maturation pathway in addition to naive B cell, accompanied by induction of ZEB2 with a concomitant decline of BACH2 along the trajectory, as the alternative origin of pathogenic double negative 2 B cells (DN2) in systemic lupus erythematosus (SLE) patients. In healthy ageing, ClonoTrace identified three pathways from naive, IgM+ memory B cells and switched-memory B cells mature through a DN2-associated transcriptional state that precedes age-associated B cells. ClonoTraces fate probability algorithm indicated that IgM+memory B cell to ABC transition emerged as the leading candidate age-associated transition, that is a process distinct from SLE DN2 maturation. ClonoTrace provides a generalizable framework for receptor-informed trajectory inference, revealing the developmental pathways of pathogenic B cell populations that are untraceable to single modality approaches in autoimmunity and aging.

bioinformatics↗

bioRxiv2026

A Generalized Spatial Progress Code for Navigation in the Medial Prefrontal Cortex

Goal-directed navigation requires an internal estimate of progress toward a desired outcome, yet how the brain constructs and represents such a signal remains unclear. Here, we designed a multi-route navigation paradigm with geometrically distinct paths and imaged medial prefrontal cortex (mPFC) activity as mice performed goal-directed route choice behavior. We found that a substantial fraction of mPFC neurons fired at consistent positions along a normalized start-to-goal axis, independent of path geometry, running direction, and task context. At the ensemble level, mPFC activity reliably decoded spatial progress but carried minimal information about path identity. This progress code emerged with task familiarity and required input from the hippocampal CA1. Inactivation of either mPFC or CA1[->]mPFC projection did not disrupt learned path preference but impaired navigational fluency in trained mice. These findings reveal a hippocampal-prefrontal mechanism for representing abstract, context-generalized spatial progress within a goal-directed navigational episode, supporting fluent navigation across variable routes.

neuroscience↗

bioRxiv2026

Deciphering shared and divergent tissue architectures from cross-species spatial transcriptomics

The integration of spatial transcriptomics (ST) data across species is essential for cross-species and translational studies, but remains challenging due to molecular divergence and anatomical differences between organisms. We present STACAME, a graph attention autoencoder-based framework to decipher shared and divergent tissue architectures from cross-species ST data by explicitly modeling both orthologous and species-specific genes. STACAME aligns ST slices in a spatially aware manner, identifies homologous and species-specific domains, and enables a suite of downstream comparative analyses. We demonstrate its utility by integrating ST datasets from diverse tissues, including hippocampus, isocortex, embryo, breast, liver, and cerebellum, across multiple species such as human, macaque, marmoset, mouse, and zebrafish. STACAME supports cross-species spatial domain alignment, the detection of shared and divergent spatially variable genes, development alignment and comparison, and the 3D integration of tissue architecture. This flexible approach facilitates the translation of findings from model organisms to humans, providing a unified computational platform for cross-species spatial transcriptomics.

bioinformatics↗

bioRxiv2026

Lineage-associated tumor cell states predict outcome and guide immunotherapeutic target selection in pediatric osteosarcoma

Osteosarcoma is a highly heterogeneous primary bone malignancy that predominantly affects adolescents and young adults, and robust prognostic biomarkers and effective targeted therapies remain lacking. While single-cell transcriptomics has begun to resolve tumor composition, a tumor cell-intrinsic framework linking transcriptional states to clinical outcome and therapeutic targeting is not established. Here, we present a single-cell transcriptomic analysis of pediatric osteosarcoma, integrating 22 samples across 18 patients spanning six diagnostic, six post-treatment, and ten metastatic lesions profiled using complementary sequencing platforms. Using non-negative matrix factorization, we identify recurrent lineage-associated transcriptional programs that define osteoblastic-like, chondroblastic-like, and fibroblastic-like tumor cell states. These programs show overlapping activity across tumor cells, indicating that tumor cell states are not strictly discrete. Strikingly, combined osteoblastic-like and chondroblastic-like program activity is associated with poorer overall survival, a finding validated across two independent bulk RNA-sequencing cohorts. These tumor cell states are further linked to distinct immune microenvironmental compositions. Mapping candidate immunotherapeutic targets at single-cell resolution reveals variable expression across tumor cell states, supporting state-informed strategies for CAR T cell targeting. Together, our findings establish a tumor cell state framework that links osteosarcoma heterogeneity to clinical outcome and provides a basis for patient stratification and the development of state-informed therapeutic strategies in pediatric osteosarcoma.

Cancer Biology↗

bioRxiv2026

Validation of MHPC512: A Publicly Available Special-Purpose Supercomputer for Molecular Dynamics Simulations of Biomolecular Systems

MHPC512 is a massively parallel, special-purpose supercomputer designed primarily for atomic-level molecular dynamics (MD) simulations of biomolecular systems. It comprises 512 processor units interconnected by a high-speed three-dimensional torus network and employs a custom chip architecture that uses 35-bit fixed-point arithmetic to accelerate computation while controlling precision loss within an acceptable margin. The preprocessor is compatible with GROMACS and AMBER input formats and supports widely used biomolecular force fields (including CHARMM, AMBER, and OPLS/AA), the Neutral Territory method for short-range nonbonded interactions, the k-space Gaussian Split Ewald method for long-range electrostatics, and multiple thermostats, barostats, and integrators. We present a three-tier validation protocol--comparing static energy and virial components, examining ensemble distributions (NVE, NVT, NPT), and evaluating long-time statistical properties--demonstrating that MHPC512 reproduces results consistent with GROMACS and AmberTools. Application examples, including bulk water, dipeptide conformational sampling, folding of fast-folding peptides, membrane-protein systems, lipid self-assembly, and GPCR conformational transitions, further confirm its reliability. MHPC512 has been deployed at multiple supercomputing centers and is publicly accessible, representing a significant advance in high-throughput, large-scale biomolecular MD simulations.

Molecular Biology↗

bioRxiv2026

Controlling metal-carbonate phase, form, and function through de novo protein design

Biomineralization enables living systems to construct hybrid materials by controlling the location, orientation, and polymorph of inorganic crystals with proteins and other biomolecules. Despite decades of study, the molecular principles underlying these processes remain difficult to harness in engineered materials, in part because native biomineralization proteins are often intrinsically disordered, heterogeneous, or insoluble. Here we show that de novo designed protein interfaces can be assembled into reconfigurable two-dimensional arrays which template calcite nanocrystals. By fine-tuning RFdiffusion2 on repeat protein scaffolds, we further enable the design of protein architectures which selectively form aragonite, a metastable polymorph of calcium carbonate, in nucleation conditions that otherwise result in a mixture of phases. Extending beyond inorganics found in biological systems, we show that lattice-matched protein designs template cobalt carbonate formation: a flat helical repeat protein interface promotes unconfined growth, whereas soluble D3 cage assemblies yield more homogenous cobalt carbonate nanocrystals confined to the interior of the cage. These protein-cage cobalt carbonate hybrid materials function as electrocatalysts for alkaline water splitting. Our results demonstrate the potential of deep learning-based methods to unlock the structural and functional activity of protein-mineral composites.

biochemistry↗

bioRxiv2026

MOFF2: A Transferable Coarse-Grained Protein Force Field for Predictive Condensate Simulations

Coarse-grained protein force fields enable simulations of biomolecular systems at length and time scales that are difficult to access with atomistic models, but achieving transferability across folded, intrinsically disordered, and multidomain proteins remains challenging. A central difficulty is that one-bead-per-residue models must represent chemically specific residue interactions while also absorbing solvent-mediated and many-body effects into a simplified energy function. Here, we present MOFF2, a transferable coarse-grained protein force field that combines residue-pair-specific interactions with a density-dependent many-body potential. MOFF2 is optimized using a two-stage strategy: bottom-up parameter learning from heterogeneous reference ensembles followed by refinement against experimental conformational observables. The resulting model provides balanced performance across ordered proteins, intrinsically disordered proteins, and multidomain proteins, and predicts condensate saturation-concentration trends for A1-LCD variant systems. Analysis of the learned parameters reveals chemically interpretable interaction patterns and density-dependent effects that explain the models improved transferability. These results demonstrate that combining a generalized coarse-grained energy function with data-driven optimization can produce a practical and interpretable force field for protein conformational and condensate simulations.

biophysics↗

bioRxiv2026

Leptin Drives Osteoarthritis Pain Through Sensory Neuron Reprogramming Independent of Cartilage Signaling

ObjectivePain in osteoarthritis (OA) is often discordant with structural joint damage, particularly in obesity-associated OA, where adipose-derived signals may drive nociception independently of cartilage pathology. Leptin has been demonstrated to be necessary, but not sufficient, to drive obesity-associated OA. Here, we tested the hypothesis that leptin mediates OA-associated pain through sensory neuron reprogramming rather than chondrocyte-intrinsic signaling, suggesting a fat-sensory nerve axis. DesignMale and female constitutive leptin-deficient (Ob/Ob), heterozygous (Ob/+), and wild-type (WT) mice, as well as chondrocyte-specific leptin receptor knockout mice (Aggrecan-CreERT2;LepRfl/fl), were challenged with destabilization of the medial meniscus (DMM) surgery to induce OA. Pain-related behaviors, joint pathology, serum cytokines, and lumbar dorsal root ganglia (DRG) transcriptomes were assessed. Human DRG cultures treated with leptin underwent transcriptomic profiling. Secondary analyses of human infrapatellar fat pad and synovium single-cell datasets evaluated leptin and leptin receptor expression patterns. ResultsChondrocyte-specific deletion of the leptin receptor did not mitigate OA pathology or pain. Global leptin-deficient (Ob/Ob) mice exhibited worse structural joint outcomes than WT and Ob/+ animals following DMM yet were robustly protected from OA-associated hyperalgesia - directly dissociating pain from structural pathology and demonstrating that leptin is involved in nociceptive sensitization. Serum cytokine profiles were sex-dependent and did not align with pain outcomes, separating systemic inflammation from nociceptive differences. Transcriptomic analysis of DRGs revealed that leptin drives enrichment of lipid metabolism, eicosanoid, and inflammatory programs, whereas leptin deficiency shifts sensory neurons toward a cytoskeletal remodeling state that does not sustain pain signaling. In human DRG cultures, leptin treatment produced a transcriptomic shift to enrich for neuronal excitability while vehicle treated cells were enriched for inflammatory signaling. Human infrapatellar fat pad and synovium transcriptomic data demonstrated adipocyte-enriched leptin expression and broad distribution of the leptin receptor across stromal, vascular, immune, and adipocyte populations. ConclusionsLeptin contributes to OA pain through neuro-immune crosstalk between adipose tissue and sensory neurons rather than through direct cartilage signaling. These findings identify leptin-associated neuronal programs linked to nociceptor sensitization and support targeting leptin-modulated neuro-immune pathways as a strategy to alleviate OA pain independently of structural disease progression.

physiology↗

bioRxiv2026

Lack of ancestral SARS-CoV-2 imprinting promotes BA.3.2.2 infection in children

The ongoing evolution of SARS-CoV-2 is heavily constrained by population-level immune imprinting. Recent genomic surveillance reveals an unexpected demographic shift: the highly mutated BA.3.2.2 sublineage is significantly enriched in paediatric populations globally, unlike concurrent variants XFG and NB.1.8.1. Here, the evidence demonstrates that this paediatric susceptibility arises from the absence of ancestral Wuhan-strain immune imprinting. Serological analyses reveal a profound failure to neutralise BA.3.2.2 in young children with no ancestral strain exposure. Concurrently, single-B-cell sequencing analyses demonstrate that BA.3.2.2 completely evades Omicron-specific Class 1/4 neutralising antibodies, encoded by IGHV2-5 and IGHV5-51, which dominate the repertoires of weakly imprinted individuals such as young children. Conversely, BA.3.2.2 remains uniquely susceptible to broadly cross-reactive Class 1 antibodies, encoded by IGHV3-53/66, typically enriched in adults with strong ancestral imprinting, such as mRNA vaccine recipients. Critically, sustained transmission of BA.3.2.2 in paediatric populations may catalyse the emergence of secondary variants that combine the paediatric-evading features of BA.3.2.2 with adult-evading Class 1 mutations. This could allow the lineage to breach the imprinted immunity of the adult population, potentially driving widespread global transmission. Together, these findings show that legacy immune imprinting paradoxically provides superior protection against a highly divergent saltation variant, directly explaining the age-biased transmission of BA.3.2.2, and informing future paediatric vaccination strategies.

immunology↗

bioRxiv2026

Aberrant cortical subcortical somatosensory network organization is associated with impaired tactile-motion perception in akinetic-rigid Parkinson's disease

BackgroundParkinsons disease (PD) is associated with somatosensory dysfunction, yet higher-order tactile-motion processing and its neural basis remain poorly understood. Here, we combined psychophysical assessment of tactile-motion perception with resting-state functional MRI (rs-fMRI) to investigate how altered sensorimotor network organization relates to tactile perceptual deficits in akinetic-rigid dominant PD (PDAR). MethodsForty-six participants (25 PDAR and 21 healthy controls, HCs) underwent clinical evaluation and resting-state functional MRI scanning. A subset of participants (15 PDAR and 15 HCs) additionally completed a tactile-motion perception task assessing directional bias and speed sensitivity. ROI-to-ROI functional connectivity analyses were performed within a customized 26-node sensorimotor and cortico-basal ganglia-thalamo-cortical (CBGTC) network. ResultsCompared with HCs, PDAR patients exhibited significantly altered tactile-motion perception, including greater directional bias (p = 0.047) and reduced sensitivity to dynamic tactile speed (p < 0.001), reflecting diminished sensitivity to mid-to-high speeds. Resting-state functional connectivity analyses revealed widespread reductions in connectivity within cortical somatosensory regions (Areas 1, 2, 3a, 3b, 5), particularly between primary somatosensory and motor cortices. In contrast, increased connectivity was observed between basal ganglia-thalamic structures and cortical sensorimotor regions, including thalamus-M1 and GPi-sensorimotor connections (all p-FDR < 0.05). ConclusionsThese findings demonstrate a dual pattern of sensorimotor network reorganization in PDAR, characterized by disrupted cortical somatosensory integration alongside enhanced subcortical-cortical coupling. The present study provides evidence that higher-order tactile-motion dysfunction in PD is associated with large-scale abnormalities in distributed sensorimotor networks and highlights the somatosensory system as a potential target for future therapeutic intervention.

neuroscience↗

bioRxiv2026

Prophage and metabolic determinants of Staphylococcus aureus survival to vancomycin identified via TraDIS screening

Reduced vancomycin susceptibility phenotypes in Staphylococcus aureus contribute to treatment failure, yet the genetic determinants of survival under inhibitory vancomycin exposure remain incompletely defined. We performed transposon directed insertion-site sequencing (TraDIS) on a methicillin resistant S. aureus (MRSA) ST398 mutant library following exposure to vancomycin at its minimum inhibitory concentration, identifying 52 genes whose disruption was associated with loss of population survival at inhibitory drug concentrations. Prophage associated loci were the largest functional group, spanning predicted structural and regulatory genes as well as multiple conserved hypothetical proteins. Targeted testing of defined transposon mutants in a USA300 background confirmed that disruption of selected loci impaired growth under vancomycin exposure. Our results highlight the contribution of diverse physiological processes, including metabolism, stress responses, and a prominent role for prophage-associated functions, rather than discrete resistance pathways. Together, these findings indicate that vancomycin tolerance is shaped by the general physiological state of the bacterial cell, including metabolic capacity and stress adaptation. ImportanceTreatment failure in Staphylococcus aureus infections often occurs in the absence of known antibiotic resistance determinants, suggesting that additional survival mechanisms influence therapeutic outcomes. In this study, we identify genetic determinants required for survival during inhibitory vancomycin exposure, revealing a broad role for metabolic functions, stress adaptation, and prophage-associated loci. The prominence of these diverse processes highlights that survival reflects global physiological adaptation rather than discrete resistance pathways. This insight underscores the need to consider cellular physiology and stress responses when developing strategies to prevent antibiotic tolerance and improve treatment efficacy.

microbiology↗

bioRxiv2026

Multiomic State-Transitions Reveal Post-Treatment Transcriptome Desynchronization in Acute Myeloid Leukemia

Temporal dynamics of the peripheral blood transcriptome are crucial for understanding leukemia evolution and response to therapy because they can reveal how gene expression programs drive abnormal cell states, disease heterogeneity, and treatment resistance. Using a mathematical model of state-transitions, we studied the temporal dynamics of peripheral blood messenger RNA (mRNA) and microRNA (miRNA) transcriptomes in a mouse model of acute myeloid leukemia (AML). In our state-transition model, mRNA and miRNA transcriptomes are represented as a particle undergoing Brownian motion in a two-dimensional multiomic potential landscape. Following chemotherapy, we observed a temporal desynchronization between mRNA and miRNA transcriptomic responses corresponding to an asymmetric shift in the landscape. Specifically, mRNA trajectories responded almost immediately post-treatment, whereas miRNA responses were delayed by approximately two weeks. Clustering analysis identified that the temporal delay is driven by a prominent cluster of miRNAs from the imprinted Dlk1-Dio3 region. Although previously implicated in acute promyelocytic leukemia, lymphomas, and metabolic dysregulation, this provides the first evidence linking the Dlk1-Dio3 locus to AML chemotherapy response and treatment-induced transcriptomic desynchronization. This framework offers an innovative dynamics-based strategy to identify biological drivers of therapeutic response and novel therapeutic targets across hematological malignancies. Key PointsO_LITreatment can induce desynchronization between messenger RNA and microRNA transcriptome dynamics in a murine model of AML C_LIO_LIMicroRNAs from the imprinted Dlk1-Dio3 locus are identified as key contributors to desynchronization and may serve as therapeutic targets C_LI

cancer biology↗

bioRxiv2026

Cell vulnerability within the sublaterodorsal tegmental nucleus underlies REM sleep behaviour disorder in prodromal α-synucleinopathy

REM sleep behaviour disorder (RBD) is a prodromal manifestation of -synucleinopathies such as Parkinsons disease. Evidence suggests that degeneration of REM sleep regulating neurons in the sublaterodorsal tegmental nucleus (SLD) could give rise to RBD, yet the specific cellular populations involved and their contribution to synucleinopathy progression remain unclear. Here, we investigated the role of defined SLD cell types in RBD pathogenesis. Using viral vector and fibril-based models of -synucleinopathy, we show that -synuclein pathology in SLD neurons triggers RBD in mice. Notably, glutamatergic SLD neurons are selectively vulnerable to synucleinopathy and the loss of these cells correlates with RBD severity. Propagation of synucleinopathy from the SLD to midbrain and forebrain structures leads to the emergence of neurological deficits associated with Parkinsons disease. These findings establish that SLD neurons are critical substrates for RBD and provide insight into the cellular mechanisms at play in the early stages of synucleinopathies.

neuroscience↗

bioRxiv2026

A functional investigation of antibody Fc-FcRn variant binding guided by in silico free energy perturbation methods

Accurate calculation of energy changes upon mutation is a key requirement for the effective use of computational methods in protein design. In this study, we applied free energy perturbation (FEP) calculations to predict the effects of mutations on the binding free energy between the immunoglobulin subtype G (IgG) antibody fragment-crystallizable (Fc) region and the neonatal Fc receptor (FcRn), an interaction that is primarily responsible for antibody half-life. We assembled an extensive experimental dataset of Fc-FcRn binding affinities for wild-type (wt) and mutant complexes, including values from literature and from newly measured results. Starting from a crystal structure of the M252Y/S254T/T256E ("YTE") Fc variant bound to FcRn, we prepared all-atom models of human IgG1-subtype wt and YTE variant Fc-FcRn complexes, adding explicit hydrogens and assigning protonation states for key ionizable residues. Initial results using standard FEP protocols to compute relative binding free energies were promising but exhibited multiple outliers. By accounting for coupling effects for FEP mutations near key histidine residues, we improved the results for several outliers, suggesting such coupling as an important approach for pH-sensitive systems. Further, upon determining new crystal structures of four Fc variants at multiple pH values, we observed subtle conformational changes in unbound Fc; by accounting for these conformational changes in FEP calculations, we additionally improved agreement with experiment. The detailed structural and energetic analyses of the Fc-FcRn system we present here thus provide an accurate energy-calculation framework to enable rational in silico design of novel Fc variants. SignificanceThe ability to determine changes in binding affinity upon mutation is critical to structure-based protein design. In this study, we demonstrate a successful computational approach using free energy perturbation (FEP) calculations on the antibody Fc-FcRn complex, a medically relevant system with implications for both therapeutic and prophylactic antibody use. Our successful calculation of accurate binding energies across a wide range of cases speaks to the power of the FEP methodology in navigating the free energy landscapes of dynamic molecular complexes. Furthermore, we show that accurate Fc-FcRn affinity calculations required careful consideration of conformational flexibility between bound and unbound states, contributing to our functional understanding of a system that will be important for future rational antibody-design efforts. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/721095v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@f754d8org.highwire.dtl.DTLVardef@1e366beorg.highwire.dtl.DTLVardef@6e67caorg.highwire.dtl.DTLVardef@602a14_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2026

Chromosome-level genome assembly of macroalgae Gracilariopsis lemaneiformis

As an important cultivated red alga, Gracilariopsis lemaneiformis has great economic and ecological value. However, its existing genome assembly is highly fragmented and inadequately annotated. In this study, we constructed the first high-quality chromosome-level genome of Gp. lemaneiformis using PacBio long reads, Illumina short reads and Hi-C sequencing data. The assembled genome was approximately 86.66 Mb and the assembled sequences were anchored to 28 pseudo-chromosomes with lengths ranging from 1.70 to 7.81 Mb. 99.91% of the PacBio reads could be mapped to our assembly. In total, 8,664 genes were annotated, and the repeat elements identified in Gp. lemaneiformis constituted 65.04% of the whole genome, including 2.24% tandem repeat sequences and 62.81% interspersed repeats. We also established a high-evidence phylogenetic tree from 19 representative algae species, with the main aim to calculate their divergence times. This high-quality genome of Gp. lemaneiformis provides a crucial foundation for understanding genetic characteristics, investigating the genomic evolution, and facilitating molecular breeding.

genomics↗