Targeted Degradation of SOS1 Exhibits Potent Anticancer Activity and Overcomes Resistance in KRAS-Mutant Tumors and BCR-ABL-Positive Leukemia.

SOS1 is an essential guanine nucleotide exchange factor for RAS that also plays a critical role in the activation of the small GTPase RAC mediated by BCR-ABL in leukemogenesis. Despite this, small molecule inhibitors targeting SOS1 have shown limited efficacy in clinical trials for KRAS mutant cancers, and their potential as a therapeutic approach for chronic myeloid leukemia (CML) remains largely unexplored. In this study, we developed a potent SOS1 PROTAC SIAIS562055, which was designed by connecting a CRBN ligand to an analogue of the SOS1 inhibitor BI-3406. SIAIS562055 exhibited sustained degradation of SOS1 and inhibition of downstream ERK pathways, resulting in superior anti-proliferative activity compared to small molecule inhibitors. SIAIS562055 also potentiated the activity of both KRAS inhibitors in KRAS-mutant cancers and ABL inhibitors in BCR-ABL+ CML. In KRAS-mutant xenografts, SIAIS562055 displayed promising antitumor potency as a monotherapy and enhanced ERK inhibition and tumor regression when combined with KRAS inhibitors, overcoming acquired resistance. In CML cells, SIAIS562055 promoted the active uptake of BCR-ABL inhibitors by upregulating the carnitine/organic cation transporter SLC22A4. SIAIS562055 and BCR-ABL inhibitors synergistically enhanced inhibition of ABL phosphorylation and downstream signaling, demonstrating robust antitumor activities in both mouse xenografts and primary CML patient samples. In summary, this study suggests that PROTAC-mediated SOS1 degradation represents an effective therapeutic strategy for treating not only KRAS-mutant cancers but also BCR-ABL-harboring leukemia.

Unraveling the CDK9/PP2A/ERK Network in Transcriptional Pause Release and Complement Activation in KRAS-mutant Cancers.

Selective inhibition of the transcription elongation factor (P-TEFb) complex represents a promising approach in cancer therapy, yet CDK9 inhibitors (CDK9i) are currently limited primarily to certain hematological malignancies. Herein, while initial responses to CDK9-targeted therapies are observed in vitro across various KRAS-mutant cancer types, their efficacy is far from satisfactory in nude mouse xenograft models. Mechanistically, CDK9 inhibition leads to compensatory activation of ERK-MYC signaling, accompanied by the recovery of proto-oncogenes, upregulation of immediate early genes (IEGs), stimulation of the complement C1r-C3-C3a cascade, and induction of tumor immunosuppression. The "paradoxical" regulation of PP2Ac activity involving the CDK9/Src interplay contributes to ERK phosphorylation and pause-release of RNA polymerase II (Pol II). Co-targeting of CDK9 and KRAS/MAPK signaling pathways eliminates ERK-MYC activation and prevents feedback activation mediated by receptor tyrosine kinases, leading to more effective control of KRAS-mutant cancers and overcoming KRASi resistance. Moreover, modulating the tumor microenvironment (TME) by complement system intervention enhances the response to CDK9i and potently suppresses tumor growth. Overall, the preclinical investigations establish a robust framework for conducting clinical trials employing KRASi/SOS1i/MEKi or immunomodifiers in combination with CDK9i to simultaneously target cancer cells and their crosstalk with the TME, thereby yielding improved responses in KRAS-mutant patients.

Highly accurate carbohydrate-binding site prediction with DeepGlycanSite.

As the most abundant organic substances in nature, carbohydrates are essential for life. Understanding how carbohydrates regulate proteins in the physiological and pathological processes presents opportunities to address crucial biological problems and develop new therapeutics. However, the diversity and complexity of carbohydrates pose a challenge in experimentally identifying the sites where carbohydrates bind to and act on proteins. Here, we introduce a deep learning model, DeepGlycanSite, capable of accurately predicting carbohydrate-binding sites on a given protein structure. Incorporating geometric and evolutionary features of proteins into a deep equivariant graph neural network with the transformer architecture, DeepGlycanSite remarkably outperforms previous state-of-the-art methods and effectively predicts binding sites for diverse carbohydrates. Integrating with a mutagenesis study, DeepGlycanSite reveals the guanosine-5'-diphosphate-sugar-recognition site of an important G-protein coupled receptor. These findings demonstrate DeepGlycanSite is invaluable for carbohydrate-binding site prediction and could provide insights into molecular mechanisms underlying carbohydrate-regulation of therapeutically important proteins.

Combination of miR159 Mimics and Irinotecan Utilizing Lipid Nanoparticles for Enhanced Treatment of Colorectal Cancer.

Colorectal cancer (CRC) ranks as the third most prevalent global malignancy, marked by significant metastasis and post-surgical recurrence, posing formidable challenges to treatment efficacy. The integration of oligonucleotides with chemotherapeutic drugs emerges as a promising strategy for synergistic CRC therapy. The nanoformulation, lipid nanoparticle (LNP), presents the capability to achieve co-delivery of oligonucleotides and chemotherapeutic drugs for cancer therapy. In this study, we constructed lipid nanoparticles, termed as LNP-I-V by microfluidics to co-deliver oligonucleotides miR159 mimics (VDX05001SI) and irinotecan (IRT), demonstrating effective treatment of CRC both in vitro and in vivo. The LNP-I-V exhibited a particle size of 118.67 ± 1.27 nm, ensuring excellent stability and targeting delivery to tumor tissues, where it was internalized and escaped from the endosome with a pH-sensitive profile. Ultimately, LNP-I-V significantly inhibited CRC growth, extended the survival of tumor-bearing mice, and displayed favorable safety profiles. Thus, LNP-I-V held promise as an innovative platform to combine gene therapy and chemotherapy for improving CRC treatment.

FMRP phosphorylation modulates neuronal translation through YTHDF1.

RNA-binding proteins (RBPs) control messenger RNA fate in neurons. Here, we report a mechanism that the stimuli-induced neuronal translation is mediated by phosphorylation of a YTHDF1-binding protein FMRP. Mechanistically, YTHDF1 can condense with ribosomal proteins to promote the translation of its mRNA targets. FMRP regulates this process by sequestering YTHDF1 away from the ribosome; upon neuronal stimulation, FMRP becomes phosphorylated and releases YTHDF1 for translation upregulation. We show that a new small molecule inhibitor of YTHDF1 can reverse fragile X syndrome (FXS) developmental defects associated with FMRP deficiency in an organoid model. Our study thus reveals that FMRP and its phosphorylation are important regulators of activity-dependent translation during neuronal development and stimulation and identifies YTHDF1 as a potential therapeutic target for FXS in which developmental defects caused by FMRP depletion could be reversed through YTHDF1 inhibition.

Identification of a carbohydrate recognition motif of purinergic receptors.

As a major class of biomolecules, carbohydrates play indispensable roles in various biological processes. However, it remains largely unknown how carbohydrates directly modulate important drug targets, such as G-protein coupled receptors (GPCRs). Here, we employed P2Y purinoceptor 14 (P2Y14), a drug target for inflammation and immune responses, to uncover the sugar nucleotide activation of GPCRs. Integrating molecular dynamics simulation with functional study, we identified the uridine diphosphate (UDP)-sugar-binding site on P2Y14, and revealed that a UDP-glucose might activate the receptor by bridging the transmembrane (TM) helices 2 and 7. Between TM2 and TM7 of P2Y14, a conserved salt bridging chain (K2.60-D2.64-K7.35-E7.36 [KDKE]) was identified to distinguish different UDP-sugars, including UDP-glucose, UDP-galactose, UDP-glucuronic acid, and UDP-N-acetylglucosamine. We identified the KDKE chain as a conserved functional motif of sugar binding for both P2Y14 and P2Y purinoceptor 12 (P2Y12), and then designed three sugar nucleotides as agonists of P2Y12. These results not only expand our understanding for activation of purinergic receptors but also provide insights for the carbohydrate drug development for GPCRs.

Sugars and other types of carbohydrates are biomolecules which play a range of key roles in the body. In particular, they are important messengers that help to coordinate immune responses. For example, a carbohydrate known as UDP-Glucose (a kind of UDP-sugar) can activate P2Y14, a receptor studded through the surface of many cells; this event then triggers a cascade of molecular events associated with asthma, kidney injury and lung inflammation. Yet it remains unclear how exactly UDP-Glucose recognizes P2Y14 ­ and, more broadly, how carbohydrates interact with purinergic receptors, the class of proteins that P2Y14 belongs to. To examine this question, Zhao et al. combined functional experiments in the laboratory with molecular dynamics simulations, a computational approach. This work revealed that UDP-Glucose may activate P2Y14 by bridging its segments anchored within the cell membrane. A component of P2Y14, known as the KDKE chain, was found to have an important role in distinguishing between highly similar types of UDP-sugars. This allowed Zhao et al. to design three sugar molecules which could activate another purinergic receptor that also contained a KDKE chain. Purinergic receptors are promising therapeutic targets. A finer understanding of how they recognise the molecules that activate them is therefore important to be able to identify and design new drug compounds.

Loops Mediate Agonist-Induced Activation of the Stimulator of Interferon Genes Protein.

The stimulator of interferon genes (STING) is an important therapeutic target for cancer diseases. The activated STING recruits downstream tank-binding kinase 1 (TBK1) to trigger several important immune responses. However, the molecular mechanism of how agonist molecules mediate the STING-TBK1 interactions remains elusive. Here, we performed molecular dynamics simulations to capture the conformational changes of STING and TBK1 upon agonist binding. Our simulations revealed that multiple helices (α5-α7) and especially three loops (loop 6, loop 8, and C-terminal tail) of STING participated in the allosteric mediation of the STING-TBK1 interactions. Consistent results were also observed in the simulations of the constitutive activating mutant of STING (R284S). We further identified α5 as a key region in this agonist-induced activation mechanism of STING. Free-energy perturbation calculations of multiple STING agonists demonstrated that an alkynyl group targeting α5 is a determinant for agonist activities. These results not only offer deeper insights into the agonist-induced allosteric mediation of STING-TKB1 interactions but also provide a guidance for future drug development of this important therapeutic target.

Structure-based development and preclinical evaluation of the SARS-CoV-2 3C-like protease inhibitor simnotrelvir.

The persistent pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants accentuates the great demand for developing effective therapeutic agents. Here, we report the development of an orally bioavailable SARS-CoV-2 3C-like protease (3CLpro) inhibitor, namely simnotrelvir, and its preclinical evaluation, which lay the foundation for clinical trials studies as well as the conditional approval of simnotrelvir in combination with ritonavir for the treatment of COVID-19. The structure-based optimization of boceprevir, an approved HCV protease inhibitor, leads to identification of simnotrelvir that covalently inhibits SARS-CoV-2 3CLpro with an enthalpy-driven thermodynamic binding signature. Multiple enzymatic assays reveal that simnotrelvir is a potent pan-CoV 3CLpro inhibitor but has high selectivity. It effectively blocks replications of SARS-CoV-2 variants in cell-based assays and exhibits good pharmacokinetic and safety profiles in male and female rats and monkeys, leading to robust oral efficacy in a male mouse model of SARS-CoV-2 Delta infection in which it not only significantly reduces lung viral loads but also eliminates the virus from brains. The discovery of simnotrelvir thereby highlights the utility of structure-based development of marked protease inhibitors for providing a small molecule therapeutic effectively combatting human coronaviruses.

A viral RNA-dependent RNA polymerase inhibitor VV116 broadly inhibits human coronaviruses and has synergistic potency with 3CLpro inhibitor nirmatrelvir.

During the ongoing pandemic, providing treatment consisting of effective, low-cost oral antiviral drugs at an early stage of SARS-CoV-2 infection has been a priority for controlling COVID-19. Although Paxlovid and molnupiravir have received emergency approval from the FDA, some side effect concerns have emerged, and the possible oral agents are still limited, resulting in optimized drug development becoming an urgent requirement. An oral remdesivir derivative, VV116, has been reported to have promising antiviral effects against SARS-CoV-2 and positive therapeutic outcomes in clinical trials. However, whether VV116 has broad-spectrum anti-coronavirus activity and potential synergy with other drugs is not clear. Here, we uncovered the broad-spectrum antiviral potency of VV116 against SARS-CoV-2 variants of concern (VOCs), HCoV-OC43, and HCoV-229E in various cell lines. In vitro drug combination screening targeted RdRp and proteinase, highlighting the synergistic effect of VV116 and nirmatrelvir on HCoV-OC43 and SARS-CoV-2. When co-administrated with ritonavir, the combination of VV116 and nirmatrelvir showed significantly enhanced antiviral potency with noninteracting pharmacokinetic properties in mice. Our findings will facilitate clinical treatment with VV116 or VV116+nirmatrelvir combination to fight coronavirus infection.

STING agonist-boosted mRNA immunization via intelligent design of nanovaccines for enhancing cancer immunotherapy.

Messenger RNA (mRNA) vaccine is revolutionizing the methodology of immunization in cancer. However, mRNA immunization is drastically limited by multistage biological barriers including poor lymphatic transport, rapid clearance, catalytic hydrolysis, insufficient cellular entry and endosome entrapment. Herein, we design a mRNA nanovaccine based on intelligent design to overcome these obstacles. Highly efficient nanovaccines are carried out with machine learning techniques from datasets of various nanocarriers, ensuring successful delivery of mRNA antigen and cyclic guanosine monophosphate-adenosine monophosphate (cGAMP) to targets. It activates stimulator of interferon genes (STING), promotes mRNA-encoded antigen presentation and boosts antitumour immunity in vivo, thus inhibiting tumour growth and ensuring long-term survival of tumour-bearing mice. This work provides a feasible and safe strategy to facilitate STING agonist-synergized mRNA immunization, with great translational potential for enhancing cancer immunotherapy.

Sequence-based drug design as a concept in computational drug design.

Drug development based on target proteins has been a successful approach in recent decades. However, the conventional structure-based drug design (SBDD) pipeline is a complex, human-engineered process with multiple independently optimized steps. Here, we propose a sequence-to-drug concept for computational drug design based on protein sequence information by end-to-end differentiable learning. We validate this concept in three stages. First, we design TransformerCPI2.0 as a core tool for the concept, which demonstrates generalization ability across proteins and compounds. Second, we interpret the binding knowledge that TransformerCPI2.0 learned. Finally, we use TransformerCPI2.0 to discover new hits for challenging drug targets, and identify new target for an existing drug based on an inverse application of the concept. Overall, this proof-of-concept study shows that the sequence-to-drug concept adds a perspective on drug design. It can serve as an alternative method to SBDD, particularly for proteins that do not yet have high-quality 3D structures available.

Spermine is a natural suppressor of AR signaling in castration-resistant prostate cancer.

In castration-resistant prostate cancer (CRPC), clinical response to androgen receptor (AR) antagonists is limited mainly due to AR-variants expression and restored AR signaling. The metabolite spermine is most abundant in prostate and it decreases as prostate cancer progresses, but its functions remain poorly understood. Here, we show spermine inhibits full-length androgen receptor (AR-FL) and androgen receptor splice variant 7 (AR-V7) signaling and suppresses CRPC cell proliferation by directly binding and inhibiting protein arginine methyltransferase PRMT1. Spermine reduces H4R3me2a modification at the AR locus and suppresses AR binding as well as H3K27ac modification levels at AR target genes. Spermine supplementation restrains CRPC growth in vivo. PRMT1 inhibition also suppresses AR-FL and AR-V7 signaling and reduces CRPC growth. Collectively, we demonstrate spermine as an anticancer metabolite by inhibiting PRMT1 to transcriptionally inhibit AR-FL and AR-V7 signaling in CRPC, and we indicate spermine and PRMT1 inhibition as powerful strategies overcoming limitations of current AR-based therapies in CRPC.

Discovery, structural optimization, and anti-tumor bioactivity evaluations of betulinic acid derivatives as a new type of RORγ antagonists.

Betulinic acid (BA) is a natural pentacyclic triterpenoid that has a wide range of biological and pharmacological effects. Here, computational methods such as pharmacophore screening and reverse docking were used to predict the potential target for BA. Retinoic acid receptor-related orphan receptor gamma (RORγ) was confirmed as its target by several molecular assays as well as crystal complex structure determination. RORγ has been the focus of metabolic regulation, but its potential role in cancer treatment has only recently come to the fore. In this study, rationale optimization of BA was performed and several new derivatives were generated. Among them, the compound 22 showed stronger binding affinity with RORγ (KD = 180 nM), good anti-proliferative activity against cancer cell lines, and potent anti-tumor efficacy with a TGI value of 71.6% (at a dose of 15 mg/kg) in the HPAF-II pancreatic cancer xenograft model. Further RNA-seq analysis and cellular validation experiments supported that RORγ antagonism was closely related to the antitumor activity of BA and 22, resulting in suppression of the RAS/MAPK and AKT/mTORC1 pathway and inducing caspase-dependent apoptosis in pancreatic cancer cells. RORγ was highly expressed in cancer cells and tissues and positively correlated with the poor prognosis of cancer patients. These results suggest that BA derivatives are potential RORγ antagonists worthy of further exploration.

YTHDF2 inhibition potentiates radiotherapy antitumor efficacy.

RNA N6-methyladenosine (m6A) modification is implicated in cancer progression. However, the impact of m6A on the antitumor effects of radiotherapy and the related mechanisms are unknown. Here we show that ionizing radiation (IR) induces immunosuppressive myeloid-derived suppressor cell (MDSC) expansion and YTHDF2 expression in both murine models and humans. Following IR, loss of Ythdf2 in myeloid cells augments antitumor immunity and overcomes tumor radioresistance by altering MDSC differentiation and inhibiting MDSC infiltration and suppressive function. The remodeling of the landscape of MDSC populations by local IR is reversed by Ythdf2 deficiency. IR-induced YTHDF2 expression relies on NF-κB signaling; YTHDF2 in turn leads to NF-κB activation by directly binding and degrading transcripts encoding negative regulators of NF-κB signaling, resulting in an IR-YTHDF2-NF-κB circuit. Pharmacological inhibition of YTHDF2 overcomes MDSC-induced immunosuppression and improves combined IR and/or anti-PD-L1 treatment. Thus, YTHDF2 is a promising target to improve radiotherapy (RT) and RT/immunotherapy combinations.

Bioactive compounds from Huashi Baidu decoction possess both antiviral and anti-inflammatory effects against COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic is an ongoing global health concern, and effective antiviral reagents are urgently needed. Traditional Chinese medicine theory-driven natural drug research and development (TCMT-NDRD) is a feasible method to address this issue as the traditional Chinese medicine formulae have been shown effective in the treatment of COVID-19. Huashi Baidu decoction (Q-14) is a clinically approved formula for COVID-19 therapy with antiviral and anti-inflammatory effects. Here, an integrative pharmacological strategy was applied to identify the antiviral and anti-inflammatory bioactive compounds from Q-14. Overall, a total of 343 chemical compounds were initially characterized, and 60 prototype compounds in Q-14 were subsequently traced in plasma using ultrahigh-performance liquid chromatography with quadrupole time-of-flight mass spectrometry. Among the 60 compounds, six compounds (magnolol, glycyrrhisoflavone, licoisoflavone A, emodin, echinatin, and quercetin) were identified showing a dose-dependent inhibition effect on the SARS-CoV-2 infection, including two inhibitors (echinatin and quercetin) of the main protease (Mpro), as well as two inhibitors (glycyrrhisoflavone and licoisoflavone A) of the RNA-dependent RNA polymerase (RdRp). Meanwhile, three anti-inflammatory components, including licochalcone B, echinatin, and glycyrrhisoflavone, were identified in a SARS-CoV-2-infected inflammatory cell model. In addition, glycyrrhisoflavone and licoisoflavone A also displayed strong inhibitory activities against cAMP-specific 3',5'-cyclic phosphodiesterase 4 (PDE4). Crystal structures of PDE4 in complex with glycyrrhisoflavone or licoisoflavone A were determined at resolutions of 1.54 Å and 1.65 Å, respectively, and both compounds bind in the active site of PDE4 with similar interactions. These findings will greatly stimulate the study of TCMT-NDRD against COVID-19.

Synthesis, cytotoxicity, and pharmacokinetic evaluations of niclosamide analogs for anti-SARS-CoV-2.

Niclosamide, an oral anthelmintic drug, could inhibit SARS-CoV-2 virus replication through autophagy induction, but high cytotoxicity and poor oral bioavailability limited its application. Twenty-three niclosamide analogs were designed and synthesized, of which compound 21 was found to exhibit the best anti-SARS-CoV-2 efficacy (EC50 = 1.00 µM for 24 h), lower cytotoxicity (CC50 = 4.73 µM for 48 h), better pharmacokinetic, and it was also well tolerated in the sub-acute toxicity study in mice. To further improve the pharmacokinetics of 21, three prodrugs have been synthesized. The pharmacokinetics of 24 indicates its potential for further research (AUClast was 3-fold of compound 21). Western blot assay indicated that compound 21 could down-regulate SKP2 expression and increase BECN1 levels in Vero-E6 cells, indicating the antiviral mechanism of 21 was related to modulating the autophagy processes in host cells.

MolFilterGAN: a progressively augmented generative adversarial network for triaging AI-designed molecules.

Artificial intelligence (AI)-based molecular design methods, especially deep generative models for generating novel molecule structures, have gratified our imagination to explore unknown chemical space without relying on brute-force exploration. However, whether designed by AI or human experts, the molecules need to be accessibly synthesized and biologically evaluated, and the trial-and-error process remains a resources-intensive endeavor. Therefore, AI-based drug design methods face a major challenge of how to prioritize the molecular structures with potential for subsequent drug development. This study indicates that common filtering approaches based on traditional screening metrics fail to differentiate AI-designed molecules. To address this issue, we propose a novel molecular filtering method, MolFilterGAN, based on a progressively augmented generative adversarial network. Comparative analysis shows that MolFilterGAN outperforms conventional screening approaches based on drug-likeness or synthetic ability metrics. Retrospective analysis of AI-designed discoidin domain receptor 1 (DDR1) inhibitors shows that MolFilterGAN significantly increases the efficiency of molecular triaging. Further evaluation of MolFilterGAN on eight external ligand sets suggests that MolFilterGAN is useful in triaging or enriching bioactive compounds across a wide range of target types. These results highlighted the importance of MolFilterGAN in evaluating molecules integrally and further accelerating molecular discovery especially combined with advanced AI generative models.

Increased Soluble Epoxide Hydrolase Activity Positively Correlates with Mortality in Heart Failure Patients with Preserved Ejection Fraction: Evidence from Metabolomics.

Epoxyeicosatrienoic acids (EETs) have pleiotropic endogenous cardiovascular protective effects and can be hydrolyzed to the corresponding dihydroxyeicosatrienoic acids by soluble epoxide hydrolase (sEH). Heart failure with preserved ejection fraction (HFpEF) has shown an increased prevalence and worse prognosis over the decades. However, the role of sEH activity in HFpEF remains unclear. We enrolled 500 patients with HFpEF and 500 healthy controls between February 2010 and March 2016. Eight types of sEH-related eicosanoids were measured according to target metabolomics, and their correlation with clinical endpoints was also analyzed. The primary endpoint was cardiac mortality, and the secondary endpoint was a composite of cardiac events, including heart failure (HF) readmission, cardiogenic hospitalization, and all-cause mortality. Furthermore, the effect of sEH inhibitors on cardiac diastolic function in HFpEF was investigated in vivo and in vitro. Patients with HFpEF showed significantly enhanced EET degradation by the sEH enzyme compared with healthy controls. More importantly, sEH activity was positively correlated with cardiac mortality in patients with HFpEF, especially in older patients with arrhythmia. A consistent result was obtained in the multiple adjusted models. Decreased sEH activity by the sEH inhibitor showed a significant effective effect on the improvement of cardiac diastolic function by ameliorating lipid disorders in cardiomyocytes of HFpEF mouse model. This study demonstrated that increased sEH activity was associated with cardiac mortality in patients with HFpEF and suggested that sEH inhibition could be a promising therapeutic strategy to improve diastolic cardiac function. Clinical trial identifier: NCT03461107 (https://clinicaltrials.gov). Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-022-00069-8.

Structural basis of peptide recognition and activation of endothelin receptors.

Endothelin system comprises three endogenous 21-amino-acid peptide ligands endothelin-1, -2, and -3 (ET-1/2/3), and two G protein-coupled receptor (GPCR) subtypes-endothelin receptor A (ETAR) and B (ETBR). Since ET-1, the first endothelin, was identified in 1988 as one of the most potent endothelial cell-derived vasoconstrictor peptides with long-lasting actions, the endothelin system has attracted extensive attention due to its critical role in vasoregulation and close relevance in cardiovascular-related diseases. Here we present three cryo-electron microscopy structures of ETAR and ETBR bound to ET-1 and ETBR bound to the selective peptide IRL1620. These structures reveal a highly conserved recognition mode of ET-1 and characterize the ligand selectivity by ETRs. They also present several conformation features of the active ETRs, thus revealing a specific activation mechanism. Together, these findings deepen our understanding of endothelin system regulation and offer an opportunity to design selective drugs targeting specific ETR subtypes.