Biology subjects

Zheng, Q.

Publications and source records attributed to Zheng, Q..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Photothermal Recycling Biosensing for Continuous, Sensitive Molecular Quantification

Continuous biochemical sensing provides valuable insights into an individuals physiological state and the mechanisms underlying pathophysiological changes. However, most existing bioanalytical methods are not compatible with continuous biochemical sensing. A major technical challenge lies in achieving rapid measurement readouts while maintaining high specificity and sensitivity in complex biological fluids. Sensitive molecular detection typically requires slow analyte-binder dissociation and long incubation to reach equilibrium, whereas rapid and frequent measurements demand fast association-dissociation kinetics that are difficult to reconcile for low-abundance analytes. To address this challenge, we introduce a sensing mechanism termed photothermal recycling (PTR), which mimics the thermal cycling process in polymerase chain reaction. Using plasmonic photothermal effects, PTR rapidly recycles binders to enable frequent measurements. We demonstrate a digital PTR assay capable of multi-hour biochemical monitoring with subpicomolar(pM) sensitivity in buffer, diluted serum, and saliva. This approach leverages localized thermal energy to dynamically modulate biomolecular recognition, offering a new bioanalytical paradigm for continuous biochemical sensing across diverse application settings.

bioengineering↗

bioRxiv2026

Mesolimbic dopamine signaling mediates increased hedonic feeding and food seeking in lactating mice

Lactation dramatically increases energy intake to support milk production and care for the offspring. However, the behavioral and neural circuit mechanisms driving heightened feeding during lactation remain unclear. Here, we reveal that lactation increases food-seeking behavior and enhances palatable food intake in mice. Fiber photometry recordings demonstrate increased dopamine release in the nucleus accumbens in lactating animals during feeding tasks. This elevated dopamine signaling is ultimately required for promoting both food seeking and palatable food intake during lactation as pharmacological inhibition of dopamine receptors or chemogenetic inhibition of VTA dopamine neurons both reduce food seeking and palatable food intake in lactating mice to non-lactating levels. Further, selective inhibition of dopamine receptors in the nucleus accumbens produces similar results. Together, these findings provide a circuit basis mediating elevated food seeking and palatable food intake during lactation, providing novel insights into the regulation of maternal energy balance and feeding behavior. HighlightsLactation increases food seeking and hedonic feeding in mice Mesolimbic dopamine levels are enhanced during feeding in lactating mice VTA dopamine neurons mediate increased palatable food intake and food seeking during lactation VTA-NAc dopamine transmission mediates increased food seeking and palatable food intake during lactation

neuroscience↗

bioRxiv2026

Quinone reductase 2 reads H3 serotonylation to support neuronal maturation

Histone H3 Gln5 serotonylation (H3Q5ser) is a recently described posttranslational modification1 that plays important roles in guiding transcriptional permissiveness in brain and peripheral systems2-5. H3Q5ser has been implicated in diverse physiological and pathological processes ranging from neural differentiation1 to sensory processing6, circadian rhythmicity7, stress responsivity8, placental gene regulation9, and tumorigenesis10-19. Since H3Q5ser can occur in combination with H3 Lys4 trimethylation (H3K4me3), most mechanistic studies to date have focused on H3Q5sers roles in modulating H3K4me3 reader interactions, where it has been shown to potentiate TAF3/TFIID binding to H3K4me31,20,21 and inhibit the recruitment of K4me3 demethylases21; however, whether H3 serotonylation functions as an autonomous chromatin signaling mark through dedicated reader proteins has remained unknown. Here, using a combination of proteomic-, structural-, molecular-, epigenomic-, and cellular-based approaches, we demonstrate that the Quinone reductase 2 (QR2) enzyme reads H3Q5ser independently of H3K4me3. CRISPR-Cas9-mediated disruption of H3 serotonylation or QR2s binding to the mark in human induced pluripotent stem cell-derived neurons impairs the establishment of neuronal transcriptional programs, alters synaptic connectivity, and disrupts electrophysiological maturation. These findings thus uncover an H3 serotonylation-dependent chromatin signaling axis that is essential for human neurodevelopment.

molecular biology↗

bioRxiv2026

Ubiquitination-mediated mitochondrial protein degradation ensures seedling emergence by regulating ER-mitochondrial interaction and mitophagy

Seedling emergence is a pivotal step of plant survival, requiring rapid hypocotyl elongation for soil penetration. This energy-demanding process necessitates active mitochondrial respiration, which inevitably induces oxidative damage. Therefore, plants evolved a quality control mechanism that selectively removes dysfunctional mitochondria through the mitophagy pathway. Here, we identified SPL2, a mitochondrial E3 ligase which is essential for hypocotyl elongation and seedling emergence through degrading mitochondrial outer membrane proteins, such as TRB1 and FIS1A. Intriguingly, these proteins also interact with an ER protein, VAP27-1, forming a complex at the ER-mitochondria contact sites, which is essential for mitophagy initiation. The spl2 mutant exhibits enhanced ER-mitochondrial tethering and mitophagy activation, whereas its overexpression has the opposite effects. The expression of SPL2 increases after light perception, in agreement with the reduced mitophagy. Collectively, our findings reveal novel mechanistic insights into seedling emergence, which are coordinated through protein ubiquitination, ER-mitochondrial interaction, and mitophagy.

plant biology↗

bioRxiv2026

Digital Twin Brain simulation and manipulation of a functional brain network underlying mental illness

Linking synaptic-level perturbations to distributed brain-network dynamics remains a central challenge for understanding and treating mental illness. Although recent whole-brain models can reproduce individual brain activity patterns, they largely function as descriptive simulators rather than mechanistic, intervention-capable systems. Here we present an intervention-capable digital twin of the human brain, integrating individual neuroanatomy and task-evoked dynamics within a neuronal-scale framework. Individualised digital twin brains recapitulate a participant-specific compact cortico-subcortical network phenotype that captures transdiagnostic psychopathology across population and clinical cohorts. In silico modulation of excitatory and inhibitory synaptic conductance produces bidirectional, heterogeneous network responses across individuals. Population-scale simulations stratify individuals and predict longitudinal symptom trajectories from DTB-derived response profiles. Independent pharmacological functional MRI data further validate the predicted baseline-dependent network responses in vivo. Together, these findings establish digital brain models as experimental platforms for mechanistic perturbation, behavioural prediction and stratification, providing a foundation for precision neuroscience and psychiatry.

neuroscience↗

bioRxiv2026

Chemical Proteomic Profiling of the Histaminylation Proteome in Cancer Cells Unveils Uncharted Epigenetic Marks on Core Histones

Histamine is a key signaling molecule in pathophysiology that can exhibit significant regulatory roles in diverse health and disease status. Besides the well-studied noncovalent interactions between histamine and its receptors, protein histaminylation is a recently discovered mechanism of action, through which histamine regulates cellular signaling pathways in a covalent modification manner. Histaminylation is an emerging protein post-translational modification, where an isopeptide bond is formed between the histamine primary amine and {gamma}-carboxyl group of glutamine through a transamidation reaction catalyzed by transglutaminase 2 (TGM2). However, due to the lack of efficient pan-specific antibodies targeting histaminylated glutamine, the histaminylation proteome in cells remains poorly explored. Here, we report the design and development of a novel N{tau}-propargylated histamine (N{tau}-PH) probe as well as its successful application in chemical proteomic profiling of the histaminylation proteome in cancer cells. Notably, new TGM2-catalyzed epigenetic marks on core histones, e.g., H2AX-Q84 and Q104 histaminylation, have been identified from cancer cells and verified. Lastly, the crosstalk between H2AX histaminylation and {gamma}H2AX formation was discovered in this study, suggesting that TGM2-mediated histaminylation plays a critical role in DNA damage responses.

biochemistry↗

bioRxiv2026

Phenotypic Bioactivity Prediction as Open-set Biological Assay Querying

The traditional drug discovery pipeline is severely bottlenecked by the need to design and execute bespoke biological assays for every new target and compound--a process that is both time-consuming and prohibitively expensive. While machine learning has accelerated virtual screening, current models remain confined to "closed-set" paradigms, unable to generalize to entirely novel biological assays without target-specific experimental data. Here, we present OpenPheno, a groundbreaking multimodal foundation model that fundamentally redefines bioactivity prediction as an open-set, visual-language question-answering (QA) task. By integrating chemical structures (SMILES), universal phenotypic profiles (Cell Painting images), and natural language descriptions of biological assays, OpenPheno unlocks the highly coveted "profile once, predict many" paradigm. Instead of conducting countless target-specific wet-lab experiments, researchers only need to capture a single, low-cost Cell Painting image of a novel compound. OpenPheno then evaluates this universal phenotypic "fingerprint" against the text-based description of any unseen assay, predicting bioactivity in a zero-shot manner. On 54 entirely unseen assays, it achieves strong zero-shot performance (mean AUROC 0.75), exceeding supervised baselines trained with full labeled data, and few-shot adaptation further improves predictions. In the most stringent setting where both compounds and assays are novel, OpenPheno maintains robust generalization (mean AUROC 0.66), opening up a new paradigm for a highly scalable, cost-effective, and universal engine for next-generation drug discovery.

bioinformatics↗

bioRxiv2026

Metabolic control of mitochondrial plasticity and extracellular vesicle biology drives Cryptococcus neoformans virulence

Metabolic adaptation to nutrient stress is a key but poorly understood driver of fungal virulence. Here, we show that a dominant East Asian lineage of Cryptococcus neoformans (VNIa-5), which disproportionately infects immunocompetent hosts, has undergone lineage-specific rewiring of glucose-responsive stress pathways. Integrating population genomics, transcriptomics, and experimental infection models, we demonstrate that VNIa-5s clinical dominance is not explained by environmental prevalence. Instead, selective activation of Snf1 signalling links glucose limitation to mitochondrial tubularisation, extracellular vesicle remodelling, and enhanced melanization. Under low-glucose conditions, VNIa-5 exhibits marked mitochondrial plasticity and extracellular vesicle compositional shifts resembling hypervirulent outbreak lineages of Cryptococcus gattii. Following experimental induction of dormancy, VNIa-5 shows significantly increased virulence in vivo compared with the closely related but clinically rare VNIa-31 subclade, with host survival tightly correlated with mitochondrial morphology. These findings identify metabolic stress integration as a central mechanism shaping cryptococcal virulence and disease in immunocompetent human hosts.

microbiology↗

bioRxiv2026

Faf2/Ubx2 potentiates p97/Cdc48 segregase activity via functional priming and reinforcement of the UT3 domain in Ufd1

The AAA+ segregase p97/Cdc48 extracts poly-ubiquitinated proteins from entrenched cellular environments to maintain proteostasis. However, its functional capacity is not uniform; extracting substrates from dense assemblies like stress granules or membrane necessitates a fully potentiated state. Here, using precisely synthesized ubiquitinated substrates, we show that the Faf2/Ubx2 cofactor hyperactivates p97/Cdc48, lowering its minimal ubiquitin chain requirement and broadening linkage specificity. Cryo-EM analysis of the activated complex demonstrates that Faf2/Ubx2 potentiates p97/Cdc48 segregase activity by structurally remodeling the substrate recognition module (K48-diUbProx) and priming its engagement with the AAA+ motor (p97/Cdc48-Npl4). These coordinated actions establish a pump-unit architecture that drives efficient substrate processing. Our findings illuminate a conserved mechanism that unlocks the maximal capacity of p97/Cdc48 and provide a blueprint for therapeutically targeting its hyper-activated state in disease.

biochemistry↗

bioRxiv2026

Multi-omics Analyses of Facial Skin in Acne Identify Distinct Microbial and Metabolic Features at Lesional and Non-lesional Sites

The microbial and biochemical landscape of clinically normal-appearing skin in individuals with acne remains uncharacterized. Here, we performed longitudinal multi-omics profiling of facial skin from 10 individuals with moderate acne and 10 healthy controls, integrating 16S rRNA gene sequencing, shotgun metagenomics, and untargeted metabolomics across lesional and non-lesional sites. Compositional tensor factorization revealed that non-lesional acne skin occupies a distinct intermediate state between healthy and lesional skin in both the microbiome and the metabolome. Machine learning models distinguished healthy from non-lesional acne skin with 70% accuracy, demonstrating that molecular dysbiosis occurs in areas of the skin without visible lesions. Non-lesional sites exhibited reduced microbial diversity, strain-level shifts in Corynebacterium and Lawsonella correlating with disease severity, and metabolic alterations, including elevated lipids and perturbed amino acid and dipeptide profiles. Microbe-metabolite co-occurrence network analyses revealed that healthy skin is enriched for protective metabolites such as urocanic acid, while acne-associated skin shows distinct co-occurrence patterns. These findings establish that acne represents a field effect disorder, with molecular alterations extending beyond visible lesions to encompass the entire facial skin ecosystem. This molecular signature of pre-lesional skin provides potential biomarkers for early intervention and suggests that effective acne treatment may require holistic approaches targeting the broader skin environment rather than individual lesions alone.

microbiology↗

bioRxiv2026

Infant cortical tracking of speech shows emerging spatial release from masking in the first year of life

Natural listening environments are filled with competing sounds. One mechanism that helps overcome this challenge is spatial release from masking (SRM), whereby spatial separation between a target signal and interfering sounds improves perception of the target. SRM has been observed in a wide range of species including songbirds, crocodilians, ferrets, and human adults, suggesting an evolutionarily conserved strategy for listening in noise. However, an important question remains: Is an infants developing brain able to tap into the same mechanism to cope with the noisy world? To address this question, we recorded electroencephalography (EEG) from 7- and 11-month-old infants (N = 53) and adults (N = 20) as they listened to natural speech in quiet, collocated noise, and spatially segregated noise. Our results revealed that both infants and adults showed robust cortical tracking of speech across quiet and noisy listening conditions. For adults, spatial separation between the target speaker and distracting talkers led to enhanced cortical tracking of the target speech, consistent with SRM. Infants also showed SRM, with stronger tracking in segregated than collocated noise, although the effect was confined to a frontal-central region rather than broadly distributed across the scalp as in adults. These findings provide the first neurophysiological evidence that, although still immature, the developing brain can benefit from spatial cues in the first year of life. Together, these results add new insight into how the infant brain solves a fundamental perceptual problem - identifying a relevant voice in a noisy environment - using a mechanism that is evolutionarily grounded.

neuroscience↗

bioRxiv2026

eTRex Reveals Oncogenic Transcriptional Regulatory Programs Across Human Cancers

Transcriptional regulators (TRs) are essential proteins that regulate gene transcription, and their dysregulation defines the oncogenic transcriptional regulatory programs that drive tumor-specific gene expression. Existing pan-cancer resources summarize these programs by aggregating signals across individual datasets, neglecting the context-specific features that capture the diversity of transcriptional regulation underlying cancer heterogeneity. By developing a variational Bayesian hierarchical model named eTRex (epigenomics-based Transcriptional Regulator explorer) and applying it to 4,819 cancer-related ATAC-seq datasets, we provide a comprehensive pan-cancer atlas of functional TR profiles that preserve the context-specific features of each dataset. This study reveals both common regulators across diverse malignancies and those with highly specific roles. We extensively validated these findings using independent CRISPR/Cas9 screening, mutation, and transcriptomic datasets. Collectively, this pan-cancer atlas of functional TR profiles represents a comprehensive, biologically interpretable resource for uncovering transcriptional regulatory programs, identifying biomarkers, prioritizing therapeutic targets in oncology, and is freely accessible through an interactive web portal.

bioinformatics↗

bioRxiv2025

Density-based longitudinal neuron tracking in high-density electrophysiological recordings

Tracking single neurons across days in high-density extracellular recordings is essential for establishing neural mechanisms of learning, memory, and post-injury recovery. However, in weeks-long recordings, identifying cross-day matches among thousands of units is confounded by changes in spike waveforms, unit turnover, and representational drift in neural responses. We introduce DANT (Density-based Across-day Neuron Tracking), an unsupervised framework that jointly estimates probe motion and neuron identity by alternating between density-based clustering in feature space and probe-motion correction inferred from provisional matches. Estimated drift is used to re-register spike waveforms across sessions, after which clustering is recomputed; this iterative loop continues until the set of matches stabilizes. In parallel, DANT learns a decision boundary from match and non-match assignments derived from the clustering results, enabling it to reject low-similarity candidate pairs. Applied to weeks-long Neuropixels recordings from the cortex and striatum in freely moving rats during stable behavior and task switching, DANT substantially increases match yield and reduces false negatives while maintaining a low false-positive rate relative to existing approaches. Together, these results indicate that DANT provides a general, unsupervised solution for longitudinal tracking in chronic, high-density recordings. The bigger pictureModern high-density probes such as Neuropixels record hundreds of units per session. When chronically implanted, many of these units can be stably recorded over extended periods, opening the door to tracking how large neural populations change over days to weeks, a question central to learning, memory, internal states, and recovery from brain injury. Yet, small shifts in probe position, changes in spike waveforms, and drifts in firing properties mean that linking units across sessions is challenging. DANT (Density-based Across-day Neuron Tracking) addresses this problem by providing an unsupervised framework that combines density-based clustering and iterative motion correction to identify cross-day matches with minimal subjective decisions. Applied to chronic Neuropixels recordings from freely moving, task-performing rats, DANT recovers longer and more complete chains of putative same neurons than existing approaches, while keeping the false-positive rate low. By making cross-day tracking more sensitive, scalable, and reproducible, DANT enables a wider range of neuroscience studies to examine the longitudinal behavior of single neurons and neural populations.

neuroscience↗

bioRxiv2025

Conformation-specific Antibody Deciphers K27-linked Ubiquitination in Chaperone-Mediated Proteostasis

Lysine 27 (K27)-linked polyubiquitination plays critical yet incompletely defined roles in proteostasis, innate immunity, and disease progression; however, investigations into this process have long been hindered by its extremely low abundance and the lack of conformation-specific enrichment tools. Herein, we describe the development of a long-sought conformation-specific antibody, K27-IgG, which can selectively recognize--among all ubiquitin chain types--the unique architecture of K27-linked polyubiquitin (K27-polyUb) characterized by a distinct buried K27-isopeptide bond, with high affinity (KD = 4.66 nM). This antibody was derived from synthetic antibodies initially generated via phage display, using chemically synthesized K27-linked diubiquitin (K27-diUb) as the antigen. High-resolution co-crystal structures uncovered the unique K27-diUb interface targeted by these sAbs. Subsequent reformatting of these sAbs into a full-length human immunoglobulin G (IgG) scaffold yielded K27-IgG, notably exhibiting markedly enhanced affinity without compromising selectivity. Using K27-IgG as a tool, we achieved sensitive detection and immunoprecipitation (IP) of endogenous K27-polyUb in cells, and delineated the intracellular interaction landscape of K27-polyUb through complementary proteomic approaches. Two key findings emerged: 1) The molecular chaperone DNAJB1 is a specific reader of K27-linked ubiquitin chains (but not other linkages) and that K27-polyUb chains themselves exhibit chaperone-like activity, suggesting a novel mechanism by which K27-polyUb regulates chaperone-mediated proteostasis; 2) The E2 enzyme UBE2Q1 assembles K27-diUb, identifying it as a potential writer for this ubiquitin chain topology. Collectively, this study establishes K27-IgG as a robust tool for deciphering the K27-linked ubiquitin code, thereby opening new avenues for investigating the biological functions of K27-linked polyubiquitination. HighlightsO_LIFirst K27-linkage conformation-specific antibody with nanomolar affinity overcomes a major barrier in the field. C_LIO_LIK27-IgG unlocks functional mapping of the K27 ubiquitin landscape under proteotoxic stress. C_LIO_LIMolecular chaperone DNAJB1 is a selective "reader" of K27-linked ubiquitin chains. C_LIO_LIK27 chains possess intrinsic chaperone activity, enabling protein refolding and suppressing aggregation. C_LIO_LIE2 enzyme UBE2Q1 is a "writer" that directly assembles K27-linked ubiquitin chains. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=116 SRC="FIGDIR/small/695067v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@113b980org.highwire.dtl.DTLVardef@1f7c1a0org.highwire.dtl.DTLVardef@c91656org.highwire.dtl.DTLVardef@1d9a507_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

A transition zone enriched WIF1⁺ basal cell subtype is associated with benign prostatic hyperplasia

ABSTRACT/SUMMARYThe cellular composition and disease susceptibilities of the distinct zones of the human prostate remain incompletely understood. Through extensive single-cell RNA sequencing (scRNA-seq) of benign regions from prostatectomy specimens, we identified a basal cell population expressing WIF1, VCAN, and NRG1, among other genes, that was significantly enriched in the transition zone (TZ). Benign prostatic hyperplasia (BPH) is a common condition that causes widespread morbidity and is nearly exclusively localized to the TZ. Analysis of previously published scRNA-seq datasets further confirmed that WIF1+ basal cells were significantly enriched in BPH compared to normal prostate. Pathway and cell-cell communication analyses revealed that this basal subtype is associated with programs related to cell proliferation, epithelial-mesenchymal transition (EMT), angiogenesis, and hormone response. Together, the molecular signature, zonal distribution, and pathway enrichment suggest that TZ-enriched WIF1+ basal cells may contribute to BPH pathogenesis by promoting epithelial and stromal remodeling.

cell biology↗

bioRxiv2025

Rovaca: A highly optimized variant caller for rapid and robust germline DNA analysis

The Genome Analysis Toolkit (GATK) HaplotypeCaller is the gold standard for germline variant detection, but its computational intensity presents a significant bottleneck in large-scale genomic analyses. While accelerated solutions exist, they often require specialized hardware or are proprietary, limiting accessibility. We present Rovaca, a novel, pure software variant caller implemented in C++ that dramatically accelerates germline analysis on standard CPU hardware. By preserving the core mathematical models of GATK HaplotypeCaller, Rovaca achieves nearly identical output, ensuring high concordance and facilitating adoption. Performance gains are achieved through a sophisticated producer-consumer multi-threading architecture and targeted micro-architectural optimizations of the PairHMM algorithm using AVX-512 instructions. Benchmarks on standard GIAB datasets show Rovaca is 57-76x faster for Whole-Genome Sequencing and 30x faster for Whole-Exome Sequencing compared to GATK. The F1-scores for both SNPs and INDELs consistently differ by less than 0.01%, demonstrating exceptional accuracy. Rovaca is a deterministic, robust, and cost-efficient tool that removes the computational barrier for high-throughput germline variant analysis. Rovaca is open-source and available at https://github.com/ZephyRoy/Rovaca.

bioinformatics↗

bioRxiv2025

Mass spectrometry-based proteomic and glycoproteomic drafts of fifteen human body fluids

The study of proteins and N-glycosylation in human body fluids (HBFs) is crucial for understanding both physiological and pathological states, offering valuable insights for disease diagnostics and monitoring. In this study, we present a comprehensive proteomics and glycoproteomics dataset featuring 15 types of precious HBFs (plasma (P), urine (U), cerebrospinal fluid (CSF), pleural fluid (PF), ascitic fluid (AF), synovial fluid (SF), pericardial fluid (PCF), peritoneal dialysis effluent (PDE), bile (B), gastric juice (GJ), seminal plasma (SP), saliva (SA), pancreatic juice (PJ), sweat (SW), and tear (T)). We also provide detailed protocols for protein processing specific to each type of HBF. The resulting peptides and enriched intact N-glycopeptides were analyzed via liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data independent acquisition (DIA) and combined electron transfer/higher-energy collisional dissociation and stepped collision energy/higher-energy collisional dissociation (EThcD-sceHCD) mode, respectively. The resulting spectra and searched files have been uploaded to the online repository iProX (www.iprox.cn) and made easily accessible (PXD068799) to facilitate further research into HBF proteomics and glycoproteomics.

systems biology↗

bioRxiv2025

Single-sequence deep learning delivers crystal-quality models of covalent K-Ras G12 hotspot complexes

Structure-based design of covalent drugs has achieved tremendous success by understanding and leveraging the three-dimensional interactions between small-molecule drug candidates and their protein targets. However, this approach traditionally relies on high-resolution co-complex structures obtained by X-ray crystallography, NMR, or cryo-EM, methods that are time-consuming and resource-intensive. Here we show that Chai-1, a publicly available structure prediction tool that accepts user-defined ligands, is able to accurately predict covalent K-Ras(G12C) complexes without using a multiple sequence alignment (MSA). Chai-1 yields pocket-aligned RMSDs <2 [A] for chemically diverse K-Ras(G12C) inhibitors, ranging from ARS-853 to BBO-8520. In addition to the conventional acrylamide-based covalent K-Ras(G12C) inhibitors, Chai-1 with a covalent-bond restraint successfully reproduced the binding poses of covalent K-Ras(G12D) and K-Ras(G12S) inhibitors, while showing limitations in capturing chemical details such as accounting for leaving-groups, bond properties, and stereochemistry. Chai-1 also provides [~]40-fold higher throughput than state-of-the-art AlphaFold3 while maintaining comparable pose accuracy. Together, these findings establish Chai-1 as an accessible and computationally efficient tool for covalent protein-ligand co-complex structure prediction, with its covalent-restraint mode offering a unique solution to accelerate covalent drug discovery, especially for challenging targets beyond cysteine. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/676163v2_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@bcbad5org.highwire.dtl.DTLVardef@8e2baborg.highwire.dtl.DTLVardef@1d507a2org.highwire.dtl.DTLVardef@e851ef_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗