Biology subjects

Li, H.

Publications and source records attributed to Li, H..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

A tissue-resolved endothelial surface proteome atlas informs organ-selective vascular targeting

BACKGROUND Endothelial cells (ECs) exhibit organ-specific functional diversity that shapes vascular homeostasis, disease susceptibility, and therapeutic accessibility. Although single-cell transcriptomic studies have defined endothelial heterogeneity at the RNA level, the in vivo cell-surface protein landscape that directly mediates vascular signaling and drug targeting remains incompletely characterized. Here, we mapped organ-specific endothelial surface proteomes atlas in vivo to define tissue-enriched vascular protein candidates relevant to organ-selective therapeutic design. METHODS We generated Cdh5-CreERT; Cre-iPEEL mice, referred to here as CHRP mice, in which membrane-tethered horseradish peroxidase is induced selectively in ECs after tamoxifen treatment, and compared CHRP labeling with non-selective NHS-Biotin vascular labeling. Following in vivo biotin-phenol perfusion, endothelial surface proteins were enriched by streptavidin affinity purification and analyzed by mass spectrometry across six organs. Proteomic profiles were used to resolve tissue- and subtype-associated endothelial surface signatures, compare protein and transcript detection patterns, and nominate tissue-selective endothelial membrane candidates, which were annotated using ChEMBL compound-target information. RESULTS Compared with non-selective NHS-Biotin labeling, CHRP improved endothelial specificity and produced clearer separation of tissue-resolved endothelial surface proteomes across brain, white adipose tissue, small intestine, kidney, lung, and skeletal muscle. CHRP proteomics revealed pronounced organ-specific heterogeneity and resolved canonical arterial, venous, and capillary programs, as well as specialized endothelial signatures including blood-brain barrier and glomerular endothelial features. Comparison with single-cell endothelial references revealed systematic differences between transcriptomic and proteomic detection of endothelial membrane proteins. Further analysis identified tissue-selective endothelial membrane candidates, and ChEMBL annotation linked a subset of these candidates to existing compound-target records, supporting the candidate atlas as a resource for future tissue-selective vascular targeting studies. CONCLUSIONS CHRP-based in vivo proximity labeling enables systematic, protein-level mapping of organ-specific endothelial surface proteomes. Together with transcriptomic comparison and compound-target annotation, this study provides a tissue-resolved endothelial surfaceome resource for vascular biology and future organ-selective therapeutic target evaluation.

cell biology↗

bioRxiv2026

TRAPPC8 Is an Endogenous Brake on UFMylation That Suppresses Tauopathy

UFMylation, a ubiquitin-like protein modification, drives tau spread through the brain, but what keeps this process in check has remained unclear. We show that TRAPPC8 acts as a natural brake on UFMylation, binding directly to the E1 enzyme UBA5 to dampen pathway activity. In Alzheimer's disease brain tissue, TRAPPC8 is reduced while UFMylation is elevated, suggesting this brake fails as disease progresses. Sustaining UFMylation in human iPSC-derived neurons increased tau aggregation and spread while disrupting lysosomal function and lipid balance. Restoring TRAPPC8-UBA5 binding reversed these defects through the lysosomal protein CLN8, which restored lysosomal function and reduced tau pathology. Notably, expressing just the UBA5-binding region of TRAPPC8 was enough to suppress tau pathology in vivo, marking it as a promising therapeutic target.

neuroscience↗

bioRxiv2026

Accelerated lung evolution associated with end-Permian and end-Triassic mass extinctions

The end-Permian and end-Triassic mass extinctions, driven by massive catastrophic volcanism and prolonged hypoxia, fundamentally reshaped life on Earth. However, the genomic impacts of these two biodiversity crises on living organisms remain largely unknown. Here, we performed a genome-wide screening to identify accelerated evolved regions in the ancestral lineage of mammals that survived both extinction events. Nearly all (20/21) of these accelerated regions were located in protein-coding sequences, and 81% (17/21) were found to be associated with lung function. We further extended our analysis to three additional vertebrate lineages that experienced either one or both of the mass extinctions. Similar genomic signatures, involving accelerated evolution of lung-related genes, were also observed in these non-mammalian lineages. Collectively, these findings suggest that adaptation of lung-related genes to prolonged hypoxia may have occurred during the two mass extinction events, potentially driving a second evolutionary stage of the lung following the vertebrate transition to land.

evolutionary biology↗

bioRxiv2026

Brain State Dynamics and Developmental Differences in Reading Comprehension

Reading comprehension is a complex cognitive task that involves dynamic interactions between the brain and external information. Previous studies on reading development primarily focused on localized or static brain activities. However, it remains an enigma how brain state dynamics evolve with development underlying reading comprehension. This study aims to address this issue by combining functional magnetic resonance imaging (fMRI) with Hidden Markov Model (HMM) to explore brain state dynamics. A total of 35 typically developing children and 31 adults were scanned while reading a story. Our results demonstrated a tripartite brain state organization, characterized respectively by high activities in the visual (State #1), language (State #2), and default mode network (DMN, State #3) regions. Children exhibited significantly longer dwell time in the DMN state (State #3) compared to adults, along with a higher probability of transitioning from the language state (State #2) to the DMN state (State #3). In addition, adults exhibited greater flexibility in state transitions during reading comprehension. Finally, the alignment between the dynamic states of children and the average states of adults was a significant positive predictor of their reading comprehension performance. This study provides a novel, intuitive perspective on how brain state dynamics evolve during the development of reading comprehension.

neuroscience↗

bioRxiv2026

Tumor-tropic E. coli engineered as living T and NK cell engagers

Despite advances in immunotherapy, most solid tumors remain resistant to treatment. Immune cell engagers redirect cytotoxic lymphocytes against cancer, but limited tumor access, immunosuppressive microenvironments and systemic immune activation limit efficacy. Here we develop live immune modulating engagers (LIME), a modular platform where non-pathogenic, tumor-tropic Escherichia coli display tandem single-chain variable fragments targeting a tumor-associated antigen and an activating receptor on T or natural killer cells. LIME bridged effector and tumor cells, induced transcriptional programs of T cell activation, metabolism and proliferation, and enhanced cytotoxicity across cancer cell lines and patient-derived organoids. In mouse models, LIME safely accumulated in tumors, outperformed tarlatamab in small cell lung cancer, and induced durable immunity in lymphoma. RAS inhibition and PD-L1 blockade enhanced LIME activity in pancreatic cancer and induced humoral responses. Multi-lineage immune modulation remained tumor-confined, without organ toxicity. These findings establish LIME as a versatile living therapeutic platform for programmable, tumor-restricted immune orchestration.

bioengineering↗

bioRxiv2026

Cell-Based Sensor for Extracellular DNA

Detection of molecules with cell-based sensors allows for conversion of binding events into gene expression outputs. Here, we present a cell-based sensor that can detect extracellular double-stranded DNA. This sensor is based on an engineered receptor which we call Luminescent Ultrasensitive Nucleic Acid Reporter, or LUNAR. LUNAR is based on a recently developed Programmable Antigen-gated G-protein-coupled Engineered Receptor (PAGER). PAGERs are a genetic fusion of an auto-inhibitory peptide, a protein-binding domain, and a modified kappa opioid receptor. PAGERs are gated by two binding events. First, a protein ligand displaces an intramolecular inhibitor, Arodyn, then a second ligand activates the receptor. By replacing the protein-binding domain with a DNA binding zinc finger protein (ZFP) we could detect extracellular DNA in a dose-dependent fashion. Here, we show that first-generation LUNAR constructs can detect both oligonucleotides and plasmid double-stranded DNA with nanomolar sensitivity in mammalian cells. Future work will focus on improving sensitivity, fold-change, and multiplexing capabilities for sequence-specific DNA detection.

synthetic biology↗

bioRxiv2026

Maximum trophic level predicts food webs susceptibility to coextinctions

As ecosystems face a growing number of threats, coextinctions (resultant extinctions following a primary extinction) are expected to proliferate. However, less is known about the conditions under which coextinctions could outpace primary extinctions. Because coextinctions often occur through lost species interactions, we posit that aspects of food web structure and complexity can help predict differences in vulnerability to coextinction across ecosystems. To test this, we leverage Bayesian network models to assess the extent to which variation in ecosystem vulnerability to coextinction varies with food web structure. We find that food webs with high maximum trophic level are most vulnerable to coextinction, and that maximum trophic level is a better predictor than other aspects of food web structure, such as species richness or trophic connectance. Extending this approach, we also find that maximum trophic level uncovers the relative vulnerability of ecosystem services to species coextinction across 12 empirical food webs.

ecology↗

bioRxiv2026

Whole-genome resequencing-based comparative variant analysis identifies candidate genes associated with cross-beak phenotype in Huiyang Bearded chickens

Cross-beaks are deemed a threat to poultry health, productivity, and animal welfare. Nevertheless, due to sporadic cases, heterogeneity of gene loci and incomplete dominance, the molecular mechanism of cross-beak formation, especially the degree of cross, is not yet clear. Thus, we screen key genes and reveal the possible phenotypic formation mechanism of cross-beak by comparison with different degrees of deformity in Huiyang Bearded chickens by compare whole-genome resequencing-based variant analysis. Comparative analysis between cross-beak and normal-beaked chickens identified differential variants in several candidate genes, including CDH11, CTNNAL1, NRXN3, NRXN1, CDH5, SDC3, and DHFR. Genes harboring these variants were enriched in pathways related to cell adhesion molecules and metabolic processes, with functional annotations involving cell-cell adhesion and neural crest cell migration. Comparative analysis between chickens with severe and slight cross-beak deformities identified additional candidate genes, including MRPL21, NSUN2, DDX55, GNB3, and NFKB2. These genes were associated with enriched terms and pathways related to focal adhesion, amyotrophic lateral sclerosis, steroid 7 -hydroxylase activity, and skin-barrier establishment. These findings provide a preliminary catalogue of genetic variants and candidate genes for future functional studies of cross-beak development and severity in chickens.

genomics↗

bioRxiv2026

Collaborative multi-agent intelligence uncovers subtype-selective allosteric sites at GPCR-lipid interaction interface

Closely related G protein-coupled receptor (GPCR) subtypes often share highly conserved orthosteric pockets, making subtype-selective ligand development challenging. Here, we developed a five-agent workflow to systematically identify divergent protein-membrane-interface sites across class A GPCRs and exploit them for selective allosteric ligand discovery. By combining dMaSIF-derived surface fingerprints with Ballesteros-Weinstein (BW) position alignment, we compared structurally equivalent membrane-facing regions and identified the three most divergent hotspots for each of 163 receptor pairs. These regions showed substantial spatial overlap with experimentally characterized allosteric sites. Paired target-off-target screening of one million lead-like compounds, followed by detail-mode redocking and multi-seed consistency filtering, yielded 352 receptor-pair-specific candidates corresponding to 344 unique compounds across 104 receptor pairs. These candidates, together with their divergent sites and predicted selectivity profiles, were integrated into a searchable database. Our findings establish a scalable strategy for translating GPCR membrane-interface divergence into precise allosteric sites and testable subtype-selective ligand candidates.

biochemistry↗

bioRxiv2026

Sex-dependent chronic neurological dysfunction following isoflurane anesthesia and surgery is associated with circulating extracellular vesicle-mediated neuroinflammatory signaling

PurposeIt is well established that volatile anesthetics and surgery induce acute and subacute changes in the cellular and molecular landscape of the brain and peripheral circulation and can impair neurological function. However, the chronic neurological sequelae of isoflurane (Iso) anesthesia combined with surgical operation (OP), as well as the underlying mechanisms of postoperative neurological dysfunction, remain poorly understood. MethodsYoung adult male (M) and female (F) C57BL/6 mice underwent 4 h of 2% Iso plus laparotomy or sham treatment. At 12 weeks, olfactory and cognitive function were assessed by odor memory, buried food, Y-maze, and active avoidance tests. Olfactory bulbs (OB) and hippocampi (HI) were collected for RNAseq, while plasma extracellular vesicles (EVs) were isolated, characterized by NanoFCM, and profiled by Olink proteomics. Lastly, EVs were injected into the HI of naive male mice, and cytokine/chemokine responses were measured 24 h later. ResultsBoth sexes showed olfactory impairment after chronic Iso/OP, with greater deficits in females. Iso/OP mice, especially females, exhibited impaired odor recognition in the OM test and longer latencies to locate buried food. Female mice also showed greater hippocampal-dependent spatial working memory deficits in the Y-maze, with more arm returns and fewer alternations than Sham/F mice, whereas Iso/OP/M mice performed similarly to controls. Likewise, female, but not male, Iso/OP mice displayed impaired associative learning in the active avoidance test, evidenced by fewer avoided trials and more escape responses. These long-term behavioral abnormalities were accompanied by sex-divergent transcriptomic remodeling in the OB and HI, including altered synaptic, neurodevelopmental, extracellular matrix, stress-response, and chemotaxis-related pathways. Iso/OP reduced plasma EV particle numbers in both sexes and shifted EV size distributions, with prominent reductions in the 40-100 nm EV fraction. Proteomics revealed distinct sex-and condition-specific EV profiles, with several EV-associated proteins showing opposing sex-dependent expression patterns. Hippocampal injection of Iso/OP-derived EVs induced donor sex-dependent cytokine remodeling, confirming inflammatory bioactivity. ConclusionsFour-hour isoflurane (Iso) exposure combined with laparotomy in young adult mice induces chronic, sex-dependent neurological deficits with distinct transcriptomic remodeling across brain subregions. Persistent alterations in circulating EV abundance and inflammatory cargo may drive chronic neuroinflammation and long-term brain dysfunction.

neuroscience↗

bioRxiv2026

HDOCK-Multimer: integrating docking and combinatorial assembly for structure prediction of large protein complexes

Deep learning methods, such as AlphaFold and RosettaFold, achieve high accuracy in protein structure prediction. However, predicting the structure of large protein complexes remains challenging due to their large size and intricate multi-chain interactions. Docking-based methods can handle large proteins, but are limited by the huge combinatorial binding space of multichains. Assembly-based approaches offer an alternative, but their accuracy critically relies on the precision of predicted subcomponents. Addressing the challenges, we propose HDOCK-Multimer (HDM), a structure prediction framework of large protein complexes by integrating ab initio docking and combinatorial assembly. HDM can efficiently reduce reliance on subcom-ponent accuracy through docking process, while leveraging the pairwise interactions of subcom-ponents through assembly strategy. HDM is extensively validated on three benchmarks of 35 large heteromeric complexes, 172 large protein complexes, and 7 CASP15 targets, and compared with state-of-the-art methods including MoLPC, CombFold, AlphaFold-Multimer (AFM), and AlphaFold3 (AF3). It is shown that HDOCK-Multimer substantially outperforms the other methods. In addition, HDM also shows ability to predict the stoichiometry and model the complex without stoichiometry input. It is anticipated that HDM will serve as a powerful tool for studying large protein complexes or molecular machines. The HDM package is freely available at https://github.com/huang-laboratory/HDOCK-Multimer/.

bioinformatics↗

bioRxiv2026

Isoflurane and surgery aggravate APOE4-dependent lipid dysregulation and neural dysfunction, leading to neurological impairment in male mice

PurposePerioperative exposure to the volatile anesthetic isoflurane (ISO) has been associated with cognitive and olfactory deficits and may increase the risk of Alzheimers disease (AD). Apolipoprotein E4 (APOE4), the strongest genetic risk factor for AD, contributes to disease pathogenesis through disrupted lipid homeostasis. However, whether and how isoflurane interacts with APOE genotype to influence neurological vulnerability remains unclear. MethodsYoung adult, presymptomatic humanized APOE4 and APOE3 knock-in mice underwent laparotomy under 2 h of isoflurane anesthesia. Microglia and astrocytes were isolated from the olfactory bulb (OB) and hippocampus (HI) by magnetic-activated cell sorting. Lipid composition, transcriptional responses, and functional outcomes were assessed using lipidomic, bulk RNA-seq, and longitudinal behavioral testing. In vivo and ex vivo electrophysiological recordings evaluated neuronal excitability and synaptic transmission in both regions. ResultsBy day 7 post-anesthesia, cell type-specific lipidomic profiling of both OB and HI revealed more pronounced lipid perturbations in microglia and astrocytes from APOE4/ISO mice than from APOE3 mice, characterized by elevated free fatty acids, increased lipid peroxidation, triglyceride depletion, and reduced hippocampal hexosylceramides and cardiolipins. Electrophysiological recordings showed greater olfactory circuit dysfunction in APOE4/ISO mice, accompanied by persistent odor memory deficits, transient olfactory sensitivity loss, early motor coordination impairments, and delayed cognitive deficits. RNA sequencing of the OB identified downregulated lipid metabolism and atherosclerosis-related pathways. ConclusionThese findings establish a mechanistic link between APOE4-dependent glial lipid dysregulation, olfactory circuit dysfunction, and delayed cognitive impairment following isoflurane anesthesia and surgery, highlighting lipid homeostasis as a potential therapeutic target.

neuroscience↗

bioRxiv2026

The S1B-Targeting PEDV Neutralizing Antibody C62 Prematurely Activates S-trimer and Mimics Receptor Function

Porcine epidemic diarrhea virus (PEDV) causes devastating enteric disease in piglets, yet the mechanistic basis of antibody-mediated neutralization remains poorly understood. Here, we determined the structure of PEDV HNXX-strain spike domain B (S1B) simultaneously bound by C62, a neutralizing porcine monoclonal antibody against PEDV G2 strains, and N34, a non-neutralizing porcine PEDV antibody. The structure reveals that C62 targets a conserved, cryptic epitope that is accessible only when S1B adopts an "up" conformation. Functionally, we showed that C62 has substantially stronger activity than N34 in triggering S-trimer disassembly and inducing the formation of proteinase K-resistant, post-fusion-like S2 structures. Despite the weaker triggering activity of N34, both C62 and N34 can function as artificial receptors. Notably, although the C62 epitope is conserved across both G1 and G2 strains, C62 exhibits G2-strain-biased neutralizing activity. We further showed that differences in cell-surface membrane fusion activity among PEDV spikes correlate with distinct viral entry pathways and are jointly determined by the S1A and S1B sequences. Together, our findings identify a strain-specific vulnerable site on the PEDV S-trimer and provide insight into how cell-surface membrane fusion activity may influence viral entry pathway selection and antibody neutralization efficacy.

microbiology↗

bioRxiv2026

Scientific computing in the age of agentic AI: an exploratory field report

Scientific computing has become a central component of modern scientific discovery. Yet many computational tools are developed by small, specialized teams under incentives that encourage the release of rapidly prototyped tooling without commensurate attention to engineering concerns, including performance and maintainability. These gaps are particularly visible in the life sciences, where the advent of high-throughput sequencing and molecular profiling has made the production and processing of datasets routine at scales that strain reliability and cost. Recently, LLM-based agents have become increasingly capable, with publicly available systems possessing both significant domain knowledge in many scientific fields and the ability to autonomously operate over complex and specialized codebases in pursuit of well-defined goals. Together, these developments create a practical opportunity for scientific computing. Many of the persistent weaknesses of the scientific computing ecosystem stem from technical debt and a shortage of sustained engineering labor and expertise. Here, we examine coding agents as a potential way to address these weaknesses: we present an exploratory field report of eight early case studies in the application of LLM agents to scientific computing across a range of project scopes, from lightweight maintenance tasks to full performance-oriented rewrites of scientific libraries, with a focus on the life sciences. Each of these case studies is accompanied by reflections from the individual or group responsible for the work, including lessons from the process. Overall, we find that the use of coding agents in scientific computing holds great promise for accelerating scientific research and increasing the reliability of critical systems, but that outstanding concerns remain, including responsibility and ownership for such projects, and we suggest collaboration and stewardship with existing maintainers when feasible.

bioinformatics↗

bioRxiv2026

Pervasive Backdoor Vulnerabilities in Genomic Foundation Models

Genomic foundation models are increasingly used to interpret and design DNA sequences, yet their susceptibility to training-data manipulation remains poorly understood. Here we systematically evaluate backdoor poisoning across three model families, seven parameter scales ranging from 50 million to 7 billion, and 18 genomic classification tasks. We introduce two complementary 48-nucleotide triggers: a composition-matched synthetic sequence and a biologically grounded trigger derived from transposon terminal inverted repeats. Poisoning 5% of the training data induced high attack success rates across all tested models, with model-level median values ranging from 91.4% to 100%. Increasing parameter scale did not consistently improve resistance, whereas poisoning rate and trigger length had stronger effects on attack efficacy. Performance on unmodified sequences was generally preserved, with 79.4% of model - task - trigger configurations changing by no more than two percentage points, although larger task-specific losses occurred. We further developed a two-stage defense that combines single-nucleotide mutation-sensitivity screening with reference-database validation. Across 28 evaluated configurations, the method achieved 100% precision and a median recall of 92.95%, while localizing the trigger in nearly all detected poisoned sequences. These findings establish training-data poisoning as a pervasive and difficult-to-detect vulnerability in genomic foundation models and motivate stronger data-provenance controls, adversarial evaluation and post-training security auditing.

bioinformatics↗

bioRxiv2026

Humanized Anti-PD-1 Antibodies Generated Using The Conditional Kernel-Elastic Autoencoder

The human immune system excels at generating highly effective antibodies through natural selection and somatic hypermutation, but adapting these antibodies for therapeutic use, referred to as "antibody medicine-likeness", requires careful consideration of biochemical and physiological properties. Traditional redesign methods are often slow and limited in scope. In this study, we introduce a machine learning-based approach to evolve new anti-PD-1 antibodies within a chemically informed latent space using a conditional kernel-elastic autoencoder (CKEA) between nivolumab and pembrolizumab, both of which bind the FG-loop "hotspot" of PD-1 in the most distantly related orientations, differing by 174{degrees}. This generative framework is designed to preserve favorable therapeutic features while exploring variants with different potency, ultimately for improved potency. To evaluate structural and functional viability, we performed molecular dynamics (MD) simulations of the generated antibody - PD-1 complexes and described their MD properties. These simulations reveal detailed free-energy landscapes and identify stable binding conformations, providing a strong basis for experimental validation. To validate our designs, we expressed and experimentally tested the antibodies for binding affinity to PD-1. Upon expression and purification, three out of six designed antibodies exhibited some binding to PD-1, whose properties could likely be improved using other computational saturation mutagenesis or laboratory evolution. Our results demonstrate the potential of artificial intelligence (AI)-guided interpolation methods to generate novel, high-affinity antibodies with therapeutic promise, offering a powerful strategy for next-generation antibody development. SYNOPSIS TOCCombination of MD simulations with machine learning algorithms could revolutionize the antibody-breeding sciences to lead to new antibody discovery that is compatible with or better than naturally occurring antibodies. Topics of Content (TOC)Fingerprints of R86 finger of PD-1 are recognized by our designed P2N_2 anti-PD-1 antibody according to our MD simulations O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=173 SRC="FIGDIR/small/742579v1_ufig1.gif" ALT="Figure 1000"> View larger version (49K): org.highwire.dtl.DTLVardef@130fd5aorg.highwire.dtl.DTLVardef@1495cd8org.highwire.dtl.DTLVardef@16e822forg.highwire.dtl.DTLVardef@25004c_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2026

A genetic switch involving EGR1 and EZH2 links aging and development across human tissues

Aging is often regarded as the last chapter of development. There is growing evidence that aging and development are mechanistically linked. Here we describe a genetic switch involving EZH2 and EGR1 as opposing regulatory nodes that appears to connect aging and development across human tissues. We show that this switch defines two distinct states in fibroblasts: a proliferative (EZH2-high/EGR1-low) state and a non-proliferative and extracellular matrix-expressing (EGR1-high/EZH2-low) state. During replicative aging, cells shift from the proliferative state to the non-proliferative state and targeting either regulatory node--by overexpressing EZH2 or suppressing EGR1--rejuvenates aged fibroblasts. We provide evidence that this switch is involved in the transition from neural progenitor cells to matured neurons during brain development and becomes destabilized during aging, partially reversing the gene expression program established during development. We observed that this same switch becomes blurred and biased towards EGR1-high/EZH2-low state during the aging of muscle stem cells and hematopoietic stem cells. Since genetic switches are widely used in development to establish and reinforce cellular identity, we propose that attenuation of developmental switches may underlie aging across diverse organs and tissues, and partially accounts for the erosion of the epigenetic landscape and the loss of cellular identity.

systems biology↗

bioRxiv2026

ESCAPE: assigning site-specific activity to covalent ligands in cells by prime editing

Chemical proteomics has identified covalent ligands targeting cysteine residues across many hundreds of human proteins. The functional effects of these liganding events, however, remain challenging to assign at scale. Here we describe ESCAPE (Endogenous Site-specific Competition Assays using Prime Editors), a platform for the site-resolved functional analysis of covalent ligands in cells. In this method, cysteine-to-serine substitutions are generated by prime editing to abrogate covalent ligand-protein interactions, and the impact of these edits on ligand-induced cellular phenotypes is quantified through allele frequency-based resistance scores. Applied to ligandable cysteines mapped by activity-based protein profiling in 50+ proteins, ESCAPE identified multiple covalent ligand-protein interactions that impair cancer cell growth, including azetidine butynamides that target a non-orthosteric cysteine in the RNA helicase DDX49 to disrupt 18S rRNA processing, 40S ribosome assembly, and protein synthesis. ESCAPE thus provides a scalable framework for the functional characterization of covalent ligands targeting structurally and mechanistically diverse proteins.

biochemistry↗