Biology subjects

Xu, Y.

Publications and source records attributed to Xu, Y..

At least 631 records · Page 35Linked to original sources

bioRxiv2022

The N-terminal extension of Arabidopsis ARGONAUTE 1 is essential for microRNA activities

microRNAs (miRNAs) regulate target gene expression through their ARGONAUTE (AGO) effector protein, mainly AGO1 in Arabidopsis thaliana. In addition to the highly conserved N, PAZ, MID and PIWI domains with known roles in RNA silencing, AGO1 contains a long, unstructured N-terminal extension (NTE) of little-known function. Here, we show that the NTE is indispensable for the functions of Arabidopsis AGO1, as a lack of the NTE leads to seedling lethality. Within the NTE, the region containing amino acids (a.a.) 91 to 189 is essential for rescuing an ago1 null mutant. Through global analyses of small RNAs, AGO1-associated small RNAs, and miRNA target gene expression, we show that the region containing a.a. 91-189 is required for the loading of miRNAs into AGO1. Moreover, we show that reduced nuclear partitioning of AGO1 did not affect its profiles of miRNA and ta-siRNA association. Furthermore, we show that the 1-to-90a.a. and 91-to-189a.a. regions of the NTE redundantly promote the activities of AGO1 in the biogenesis of trans-acting siRNAs. Together, we report novel roles of the NTE of Arabidopsis AGO1.

plant biology↗

bioRxiv2022

Integrative Single Cell Multiomic Profiling Analysis Reveals HOX-PBX Gene Regulatory Network Contributing to the Survival of mTOR Hyperactive Cells

Lymphangioleiomyomatosis (LAM) is a rare, debilitating lung disease that predominantly affects women of reproductive age. LAM is characterized by the infiltration of the lungs by abnormally proliferating smooth muscle-like cells of unknown origin via an estrogen-dependent metastatic mechanism. LAM cells carry deleterious mutations of tuberous sclerosis complex (TSC1/TSC2) genes, resulting in hyperactivation of the mechanistic target of rapamycin complex 1 (mTORC1) and ultimately dysregulated cell growth. Sirolimus, an FDA approved mTORC1 inhibitor and current best-choice medication for LAM stabilizes lung function in most LAM patients. However, it requires sustained application and remains inefficacious in some patients. The greatest barriers to finding a cure for LAM include its undetermined origin and unclear underlying pathogenesis. Our study aims to advance knowledge on the origin of LAM, and ultimately serve as a premise for the development of novel therapeutic targets for LAM. Single cell RNA sequencing (scRNA-seq) is a powerful tool in biomedical research that informs gene expression differences at the cellular level and may provide insights into the most fundamental origin of LAM cells. Our scRNA-seq analysis of LAM cells revealed a unique population of cells (LAMCORE), expressing uterine-similar homeobox transcription factors (HOX) and Pre-B-cell leukemia homeobox 1 (PBX1), which are absent in normal lung, suggesting that the uterus is the primary origin of LAM. PBX1 is a transcription factor critical for female reproductive tract development and maintenance, and its overexpression is implicated in some female reproductive cancers. In this study we hypothesize that PBX1 promotes survival and lung colonization of LAM (TSC2-null) cells. Using LAM patient-derived cells, we validated the transcriptional profile, gene expression and protein levels of PBX1. We have the first functional evidence that PBX1 and its downstream targets are upregulated in LAM cells. In a mouse model of LAM, we monitored the effect of suppression of PBX1 by short hairpin RNA-mediated gene silencing on lung colonization and tumor growth. We also found that pharmacological suppression of PBX1 attenuates LAM lung colonization and promotes death of LAM cells in vivo and vitro. Our data collectively suggests that PBX1 is a critical regulator of LAM progression.

cancer biology↗

bioRxiv2022

Dysregulation of Acid Ceramidase-mediated Sphingolipid Metabolism Contributes to Tumor Progression in Tuberous Sclerosis Complex

Tuberous Sclerosis Complex (TSC) is disorder of multi-system benign neoplasia in the brain, heart, kidneys and lungs. Lymphangioleiomyomatosis (LAM) is a progressive pulmonary disease affecting exclusively women. Both are caused by mutations in TSC1 and TSC2, resulting in mTORC1 hyperactivation. Single cell RNA sequencing of LAM lungs identified activation of genes in the sphingolipid pathway. Independent validation studies showed that acid ceramidase (ASAH1) and dihydroceramide desaturase (DEGS1), key enzyme for regulating sphingolipid and ceramide metabolism, were significantly increased in TSC2-null cells, and their expression and activity were rapamycin-insensitive. TSC2 negatively regulated the biosynthesis of tumorigenic sphingolipids. Suppression of ASAH1 by shRNA or the inhibitor ARN14976 (17a) markedly decreased the viability of TSC2-null cells. In vivo, 17a significantly decreased the growth of Tsc2-null cell derived mouse xenografts. When combined with rapamycin, 17a more strongly inhibited the progression of renal cystadenomas in Tsc2+/- mice than either agent alone, evaluated by pathology and MRI. Collectively, our studies identify a rapamycin-insensitive disorder of sphingolipid metabolism in TSC2-null cells and tumors and validate the novel hypothesis that TSC2 regulates sphingolipid production and action via ASAH1. Targeting aberrant sphingolipid metabolism pathways may have therapeutic value in TSC and LAM, and possibly in mTORC1-hyperactive neoplasms.

cell biology↗

bioRxiv2022

PF-D-Trimer, a broadly protective SARS-CoV-2 subunit vaccine: immunogenicity and application

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has had and still has a considerable impact on global public health. One of the characteristics of SARS-CoV-2 is a surface homotrimeric spike protein, the primary responsible for the host immune response upon infection. Here we show the preclinical studies of a broad protective SARS-CoV-2 subunit vaccine developed from our Trimer Domain platform using the Delta spike protein, from antigen design to purification, vaccine evaluation and manufacturability. The prefusion trimerized Delta spike protein, PF-D-Trimer, was highly expressed in Chinese hamster ovary (CHO) cells, purified by a rapid one-step anti-Trimer Domain monoclonal antibody immunoaffinity process and prepared as a vaccine formulation with an adjuvant. The immunogenicity studies demonstrated that this vaccine candidate induces robust immune responses in mouse, rat and Syrian hamster models. It also protects K18-hACE2 transgenic mice in a homologous virus challenge. The neutralizing antibodies induced by this vaccine display a cross-reactive capacity against the ancestral WA1 and Delta variants as well as different Omicron, including BA.5.2. The Trimer Domain platform was proven to be a key technology in the rapid production of the PF-D-Trimer vaccine and may be crucial to accelerate the development of updated versions of SARS-CoV-2 vaccines.

immunology↗

bioRxiv2022

Joint likelihood-free inference of the number of selected SNPs and the selection coefficient in an evolving population

Given the often intractable exact likelihood, likelihood-free inference plays an important role in population genetics. Indeed, several methodological developments in approximate Bayesian Computation (ABC) were inspired by applications in population genetics. Here, we explore a novel combination of recently proposed ABC tools that can handle high-dimensional summary statistics and apply them to infer selection strength and the number of selected loci from experimental evolution data. While several methods infer selection strength at the single-nucleotide polymorphism (SNP) level, our approach provides additional information about the selective architecture, including the number of selected positions in a candidate window of interest. This is nontrivial, since the spatial correlation induced by genomic linkage can produce selection signals at neighboring SNPs. A further advantage of our approach is that we can readily quantify uncertainty using the ABC posterior. On both simulated and real data, we demonstrate promising performance. This suggests that our ABC variant could also be interesting in other applications.

evolutionary biology↗

bioRxiv2022

Regenerative hallmarks of aging: Insights through the lens of Pleurodeles waltl

BackgroundAging and regeneration are heavily linked processes. While it is generally accepted that regenerative capacity declines with age, some vertebrates, such as newts, can bypass the deleterious effects of aging and successfully regenerate a lens throughout their lifetime. ResultsHere, we used Optical Coherence Tomography (OCT) to monitor the lens regeneration process of larvae, juvenile, and adult newts. While all three life stages were able to regenerate a lens through transdifferentiation of the dorsal iris pigment epithelial cells (iPECs), an age-related decline in the kinetics of the regeneration process was observed. Consistent with these findings, iPECs from older animals exhibited a delay in cell cycle re-entry. Furthermore, it was observed that clearance of the extracellular matrix (ECM) was delayed in older organisms. ConclusionsCollectively, our results suggest that although lens regeneration capacity does not decline throughout the lifespan of newts, the intrinsic and extrinsic cellular changes caused by aging alter the kinetics of this process. By understanding how aging affects lens regeneration in newts, we can gain important insights for restoring the age-related regeneration decline observed in most vertebrates.

developmental biology↗

bioRxiv2022

Imprinted SARS-CoV-2 humoral immunity induces converging Omicron RBD evolution

Continuous evolution of Omicron has led to a rapid and simultaneous emergence of numerous variants that display growth advantages over BA. 5. Despite their divergent evolutionary courses, mutations on their receptor-binding domain (RBD) converge on several hotspots. The driving force and destination of such convergent evolution and its impact on humoral immunity remain unclear. Here, we demonstrate that these convergent mutations can cause striking evasion of neutralizing antibody (NAb) drugs and convalescent plasma, including those from BA.5 breakthrough infection, while maintaining sufficient ACE2 binding capability. BQ.1.1.10, BA.4.6.3, XBB, and CH. 1.1 are the most antibody-evasive strain tested, even exceeding SARS-CoV-1 level. To delineate the origin of the convergent evolution, we determined the escape mutation profiles and neutralization activity of monoclonal antibodies (mAbs) isolated from BA.2 and BA.5 breakthrough-infection convalescents. Importantly, due to humoral immune imprinting, BA.2 and especially BA.5 breakthrough infection caused significant reductions in the epitope diversity of NAbs and increased proportion of non-neutralizing mAbs, which in turn concentrated humoral immune pressure and promoted convergent evolution. Moreover, we showed that the convergent RBD mutations could be accurately inferred by integrated deep mutational scanning (DMS) profiles, and the evolution trends of BA.2.75/BA.5 subvariants could be well-simulated through constructed convergent pseudovirus mutants. Together, our results suggest current herd immunity and BA.5 vaccine boosters may not provide good protection against infection. Broad-spectrum SARS-CoV-2 vaccines and NAb drugs development should be highly prioritized, and the constructed mutants could help to examine their effectiveness in advance.

immunology↗

bioRxiv2022

Novel Small Molecular Compound AE-848 Showed Potent Inhibitory Activity Against Human Hepatoblastoma Cells

PurposeAE-848/33345007, is a novel small molecular compound that was independently synthesized by our laboratory. The aim of the current study was to investigate potential therapeutic effects of the small molecule compound AE-848 on human hepatoblastoma cells. MethodsHuman hepatoblastoma cell line HepG2 was cultured under different concentrations of AE-848. MTT assay was used to detect the inhibitory ability of AE-848 on the activity of this cell line, while flow cytometry was applied to quantify apoptosis. Western-blot technique was used to determine expression levels of signaling pathway-associated molecules. The antitumor in vivo activity of AE-848 against hepatoblastoma was evaluated using hepatoblastoma-bearing nude mice randomly divided into AE-848 (experimental) and saline (control) groups respectively. Changes in survival and tumor sizes were compared between these two groups. ResultsAE-848 significantly inhibited proliferation and induced apoptosis of HepG2 cells, and induced activation of PI3K/Akt/mTOR signaling pathways. More importantly, AE-848 administration significantly inhibited tumor growth and prolonged survival of hepatoblastoma-bearing mice. ConclusionAE-848 had a strong anti-hepatoblastoma activity both in vitro and in vivo, indicating the importance of developing AE-848 as a potential drug for hepatoblastoma treatment.

cancer biology↗

bioRxiv2022

Crosstalk between RNA m6A and DNA methylation regulates transposable element chromatin activation and cell fate in human pluripotent stem cells

Transposable elements (TEs) are parasitic DNA sequences accounting for over half of the human genome. Tight control of the repression and activation states of TEs is critical for genome integrity, development, immunity, and diseases, including cancer. However, precisely how this regulation is achieved remains unclear. To address this question, we develop a targeted proteomic proximity labeling approach to capture TE-associated proteins in human embryonic stem cells (hESCs). We find that the RNA N6-methyladenosine(m6A)-reader, YTHDC2, occupies genomic loci of the primate-specific TE, LTR7/HERV-H, specifically through its interaction with m6A-modified HERV-H RNAs. Unexpectedly, YTHDC2 recruits the DNA 5-methylcytosine(5mC)-demethylase, TET1, to remove 5mC from LTR7/HERV-H and prevent epigenetic silencing. Functionally, the YTHDC2/LTR7-axis inhibits neural differentiation of hESCs. Our results reveal both an underappreciated crosstalk between RNA m6A and DNA 5mC, the most abundant regulatory modifications of RNA and DNA in eukaryotes, and the fact that in hESCs this interplay controls TE activity and cell fate.

genetics↗

bioRxiv2022

SETD2 deficiency promotes renal fibrosis through the TGF-β/Smad signaling pathway in the absence of VHL

Renal fibrosis is the final development pathway and the most common pathological manifestation of chronic kidney disease. An important intrinsic cause of renal fibrosis is epigenetic alterations. SET domain-containing 2 (SETD2) is the sole histone H3K36 trimethyltransferase, catalyzing H3K36 dimethylation to trimethylation. There is evidence that SETD2-mediated epigenetic alterations are implicated in many diseases. However, it is unclear what role SETD2 plays in the development of renal fibrosis. Clinical data indicate that SETD2 is lowly expressed in patients with renal fibrosis. Here, we established genetically engineered mice with SETD2 and VHL deficiency. SETD2 deficiency leads to severe renal fibrosis in VHL-deficient mice. Mechanically, SETD2 maintains the transcriptional level of Smad7, a negative feedback factor of the TGF-{beta}/Smad signaling pathway, thereby preventing the activation of the TGF-{beta}/Smad signaling pathway. Deletion of SETD2 leads to reduced smad7 expression, which results in activation of the TGF-{beta}/Smad signaling pathway and ultimately fibrosis in the absence of VHL. Our findings reveal the role of SETD2-mediated H3K36me3 of Smad7 in regulating the TGF-{beta}/Smad signaling pathway in renal fibrogenesis. Thus, our study provides innovative insights into SETD2 as a potential therapeutic target for the treatment of renal fibrosis.

molecular biology↗

bioRxiv2022

Transcriptome-wide characterization of piRNAs during the developmental process of European honey bee larval guts

piRNAs play pivotal roles in suppressing transposons, maintaining genome stability, regulating gene expression, and modulating development and immunity. However, there are few piRNA-associated studies on honey bee, and the regulatory role of piRNAs in the development of bee guts is largely unknown. In this current work, the differential expression pattern of piRNAs during the developmental process of the European honey bee (Apis mellifera) was analyzed, and target prediction of differentially expressed piRNAs (DEpiRNAs) was then conducted, followed by investigation of regulatory networks and the potential function of DEpiRNAs in regulating larval gut development. Here, a total of 843 piRNAs were identified in the larval guts of A. mellifera; among these, 764 piRNAs were shared by 4- (Am4 group), 5- (Am5 group), and 6-day-old (Am6 group) larval guts, while 11, 67, and 1, respectively, were unique. The first base of piRNAs in each group had a cytosine (C) bias. Additionally, 61 up-regulated and 17 down-regulated piR-NAs were identified in the Am4 vs. Am5 comparison group, further targeting 9, 983 genes, which were involved in 50 GO terms and 142 pathways, while two up-regulated and five down-regulated piRNAs were detected in the Am5 vs. Am6 comparison group, further targeting 1, 936 genes, which were engaged in 41 functional terms and 101 pathways. piR-ame-742536 and piR-ame-856650 in the Am4 vs. Am5 comparison group as well as piR-ame-592661 and piR-ame-31653 in the Am5 vs. Am6 comparison group were found to link to the highest number of targets. Further analysis indicated that targets of DEpiRNAs in these two comparison groups were seven development-associated signaling pathways such as Hippo and Notch signaling pathways, seven immune-associated pathways including endocytosis and the Jak/STAT signaling pathway, and three energy metabolism pathways, namely sulfur metabolism, nitrogen metabolism, and oxidative phosphorylation. Moreover, the expression trends of five randomly selected DEpiRNAs were verified based on stem-loop RT-PCR and RT-qPCR. These results were suggestive of the overall alteration of piRNAs during the larval developmental process and demonstrated that DEpiRNAs potentially modulate development-, immune-, and energy metabolism-associated pathways by regulating expression of corresponding genes via target binding, further affecting the development of A. mellifera larval guts. Our data offer novel insights into the development of bee guts and lay a basis for clarifying the developmental mechanism underlying the larval guts of European honey bee.

molecular biology↗

bioRxiv2022

Canonical and Replicable Multi-Scale Intrinsic Connectivity Networks in 100k+ Resting-State fMRI Datasets

Resting-state functional magnetic resonance imaging (rsfMRI) has shown considerable promise for improving our understanding of brain function and characterizing various mental and cognitive states in the healthy and disordered brain. However, the lack of accurate and precise estimations of comparable functional patterns across datasets, individuals, and ever-changing brain states in a way that captures both individual variation and inter-subject correspondence limits the clinical utility of rsfMRI and its application to single-subject analyses. We posit that using reliable network templates and advanced group-informed network estimation approaches to accurately and precisely obtain individualized (dynamic) networks that retain cross-subject correspondence while maintaining subject-specific information is one potential solution to overcome the aforementioned barrier when considering cross-study comparability, independence of subject-level estimates, the limited data available in single studies, and the low signal-to-noise ratio (SNR) of rsfMRI. Toward this goal, we first obtained a reliable and replicable network template. We combined rsfMRI data of over 100k individuals across private and public datasets and selected around 58k that meet quality control (QC) criteria. We then applied multi-model-order independent component analysis (ICA) and subsampling to obtain reliable canonical intrinsic connectivity networks (ICNs) across multiple spatial scales. The selected ICNs (i.e., network templates) were also successfully replicated by independently analyzing the data that did not pass the QC criteria, highlighting the robustness of our adaptive template to data quality. We next studied the feasibility of estimating the corresponding subject-specific ICNs using a multivariate-spatially constrained ICA as an example of group-informed network estimation approaches. The results highlight that several factors, including ICNs themselves, data length, and spatial resolution, play key roles in successfully estimating the ICNs at the subject level. Large-scale ICNs, in general, require less data to achieve a specific level of spatial similarity with their templates (as well as within- and between-subject spatial similarity). Moreover, increasing data length can reduce an ICNs subject-level specificity, suggesting longer scans might not always be desirable. We also show spatial smoothing can alter results, and the positive linear relationship we observed between data length and spatial smoothness (we posit that it is at least partially due to averaging over intrinsic dynamics or individual variation) indicates the importance of considering this factor in studies such as those focused on optimizing data length. Finally, the consistency in the spatial similarity between ICNs estimated using the full-length of data and subset of it across different data lengths may suggest that the lower within-subject spatial similarity in shorter data lengths is not necessarily only defined by lower reliability in ICN estimates; rather, it can also be an indication of brain dynamics (i.e., different subsets of data may reflect different ICN dynamics), and as we increase the data length, the result approaches the average (also known as static) ICN pattern, and therefore loses its distinctiveness.

neuroscience↗

bioRxiv2022

Evolution of m6A related genes in insects and function of METTL3 in embryonic development of silkworm.

N6-methyladenosine (m6A), the most prevalent modification in eukaryotic RNAs, plays a key role in biological processes. However, the evolutionary relationships and function of m6A related genes in insects are still largely unknown. Here, we analyzed the phylogenetics of m6A related genes among 207 insects and find that m6A related genes are evolutionarily conserved in insects. We apply the lepidopteran model insect Bombyx. mori as a study system. Subcellular localization experiments in BmN cells confirmed that YTHDF3 localizes in the cytoplasm, METTL3, METTL14 and YTHDC localize in the nucleus, while FL2D localizes in both nucleus and cytoplasm. We also detected expression pattern of m6A related genes during the embryonic development of B. mori and found that m6A related genes expression pattern is temporally specific. To elucidate the function of METTL3 during embryonic stage, RNA sequencing was performed to measure differential expressions of mRNA from silkworm eggs after METTL3 knockdown, and METTL3-overexpressing BmN cells. The global transcriptional pattern showed that METTL3 knockdown affected multiple cellular processes, including oxidoreductase activity, transcription regulator activity, cation binding and fundamental many metabolism processes, such as carbon metabolism, purine metabolism, biosynthesis of amino acids, and the citrate cycle, were affected. In addition, METTL3 knockdown significantly affected Wnt and Toll/Imd pathways in embryonic stage. The results suggest that METTL3 plays an important role during the embryonic development of B. mori. This study deepens our understanding of the function of m6A related genes in insects.

evolutionary biology↗

bioRxiv2022

Single-nuclear RNA sequencing of endomyocardial biopsies identifies persistence of donor-recipient chimerism with distinct signatures in severe cardiac allograft vasculopathy

Cardiac allograft vasculopathy (CAV) is the leading cause of late allograft failure and mortality after heart transplantation. As current standards of diagnosis and treatment of CAV have significant limitations, understanding cell-specific responses may prove critical for developing improved detection strategies and novel therapeutics. This study is the first to successfully utilize human endomyocardial biopsy (EMB) samples to isolate large numbers of intact nuclei for single-nuclear transcriptomics. These data also lay the groundwork for ongoing experiments to study serial, routinely-collected EMB specimens after heart transplantation to identify novel biomarkers and pathways through which early CAV pathogenesis can be interrupted, thereby prolonging allograft survival.

systems biology↗

bioRxiv2022

A machine learning model for disease risk prediction by integrating genetic and non-genetic factors

Polygenic risk score (PRS) has been widely used to identify the high-risk individuals from the general population, which would be helpful for disease prevention and early treatment. Many methods have been developed to calculate PRS by weighted aggregating the phenotype-associated risk alleles from genome-wide association studies. However, only considering genetic effects may not be sufficient for risk prediction because the disease risk is not only related to genetic factors but also non-genetic factors, e.g., diet, physical exercise et al. But it is still a challenge to integrate these genetic and non-genetic factors into a unified machine learning framework for disease risk prediction. In this paper, we proposed PRSIMD (PRS Integrating Multi-source Data), a machine learning model that applies posterior regularization to integrate genetic and non-genetic factors to improve disease risk prediction. Also, we applied Mendelian Randomization analysis to identify the causal non-genetic risk factors for the selected diseases. We applied PRSIMD to predict type 2 diabetes and coronary artery disease from UK Biobank and observed that PRSIMD was significantly better than the methods to calculate PRS including p-value threshold (P+T), PRSice2, SBLUP, DMSLMM, and LDpred2. In addition, we observed that PRSIMD achieved the better predictive power than the composite risk score.

bioinformatics↗

bioRxiv2022

Widely Used and Fast De Novo Drug Design by a Protein Sequence-Based Reinforcement Learning Model

De novo molecular design has facilitated the exploration of large chemical space to accelerate drug discovery. Structure-based de novo method can overcome the data scarcity of active ligands by incorporating drug-target interaction into deep generative architectures. However, these strategies are bottlenecked by the small fraction of experimentally determined protein or complex structures. In addition, the cost of the molecular generation is computationally expensive due to 3D representations of both molecule and protein. Here, we demonstrate a widely used and fast protein sequence-based reinforcement learning (RL) model for drug discovery. In the generative model, one of the reward components, a binding affinity predictor, is based on 1D protein sequence and molecular SMILES. As a proof of concept, the RL model was utilized to design molecules for four targets. The generated compounds showed bioactivities by the validation of both QSAR and molecular docking with experimental 3D binding pockets. We also found that the performance of generated molecules depends on the selection of data source training for the binding predictor. Furthermore, drug design for a kinase without any experimental structure, CDK20, was studied. By only 1D protein sequence as input, the generated novel compounds showed favorable binding affinity based on the AlphaFold predicted structure.

bioinformatics↗

bioRxiv2022

ERStruct: A Python Package for Inferring the Number of Top Principal Components from Whole Genome Sequencing Data

Large-scale multi-ethnic DNA sequencing data is increasingly available owing to decreasing cost of modern sequencing technologies. Inference of the population structure with such sequencing data is fundamentally important. However, the ultra-dimensionality and complicated linkage disequilibrium patterns across the whole genome make it challenging to infer population structure using traditional principal component analysis (PCA) based methods and software. We present the ERStruct Python Package, which enables the inference of population structure using whole-genome sequencing data. By leveraging parallel computing and GPU acceleration, our package achieves significant improvements in the speed of matrix operations for large-scale data. Additionally, our package features adaptive data splitting capabilities to facilitate computation on GPUs with limited memory. Our Python package ERStruct is an efficient and user-friendly tool for estimating the number of top informative PCs that capture population structure from whole genome sequencing data.

bioinformatics↗

bioRxiv2022

Development of highly potent non-covalent inhibitors of SARS-CoV-2 3CLpro

The SARS-CoV-2 virus is the causal agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19). There is an urgent need for potent, specific antiviral compounds against SARS-CoV-2. The 3C-like protease (3CLpro) is an essential enzyme for the replication of SARS-CoV-2 and other coronaviruses, and thus is a target for coronavirus drug discovery. Nearly all inhibitors of coronavirus 3CLpro reported so far are covalent inhibitors. Here, we report the development of specific, non-covalent inhibitors of 3CLpro. The most potent one, WU-04, effectively blocks SARS-CoV-2 replications in human cells with EC50 values in the 10-nM range. WU-04 also inhibits the 3CLpro of SARS-CoV and MERS-CoV with high potency, indicating that it is a pan-inhibitor of coronavirus 3CLpro. WU-04 showed anti-SARS-CoV-2 activity similar to that of PF-07321332 (Nirmatrelvir) in K18-hACE2 mice when the same dose was administered orally. Thus, WU-04 is a promising drug candidate for coronavirus treatment. One-Sentence SummaryA oral non-covalent inhibitor of 3C-like protease effectively inhibits SARS-CoV-2 replication.

microbiology↗