RESUMO
G-protein coupled receptors (GPCRs), crucial in various diseases, are targeted of over 40% of approved drugs. However, the reliable acquisition of experimental GPCRs structures is hindered by their lipid-embedded conformations. Traditional protein-ligand interaction models falter in GPCR-drug interactions, caused by limited and low-quality structures. Generalized models, trained on soluble protein-ligand pairs, are also inadequate. To address these issues, we developed two models, DeepGPCR_BC for binary classification and DeepGPCR_RG for affinity prediction. These models use non-structural GPCR-ligand interaction data, leveraging graph convolutional networks and mol2vec techniques to represent binding pockets and ligands as graphs. This approach significantly speeds up predictions while preserving critical physical-chemical and spatial information. In independent tests, DeepGPCR_BC surpassed Autodock Vina and Schrödinger Dock with an area under the curve of 0.72, accuracy of 0.68 and true positive rate of 0.73, whereas DeepGPCR_RG demonstrated a Pearson correlation of 0.39 and root mean squared error of 1.34. We applied these models to screen drug candidates for GPR35 (Q9HC97), yielding promising results with three (F545-1970, K297-0698, S948-0241) out of eight candidates. Furthermore, we also successfully obtained six active inhibitors for GLP-1R. Our GPCR-specific models pave the way for efficient and accurate large-scale virtual screening, potentially revolutionizing drug discovery in the GPCR field.
Assuntos
Descoberta de Drogas , Receptores Acoplados a Proteínas G , Receptores Acoplados a Proteínas G/química , Receptores Acoplados a Proteínas G/metabolismo , Ligantes , Descoberta de Drogas/métodos , Humanos , Simulação de Acoplamento Molecular , Ligação Proteica , Sítios de LigaçãoRESUMO
The process of virtual screening relies heavily on the databases, but it is disadvantageous to conduct virtual screening based on commercial databases with patent-protected compounds, high compound toxicity and side effects. Therefore, this paper utilizes generative recurrent neural networks (RNN) containing long short-term memory (LSTM) cells to learn the properties of drug compounds in the DrugBank, aiming to obtain a new and virtual screening compounds database with drug-like properties. Ultimately, a compounds database consisting of 26,316 compounds is obtained by this method. To evaluate the potential of this compounds database, a series of tests are performed, including chemical space, ADME properties, compound fragmentation, and synthesizability analysis. As a result, it is proved that the database is equipped with good drug-like properties and a relatively new backbone, its potential in virtual screening is further tested. Finally, a series of seedling compounds with completely new backbones are obtained through docking and binding free energy calculations.
Assuntos
Aprendizado Profundo , Simulação de Acoplamento Molecular , Simulação de Acoplamento Molecular/métodos , Inibidores Enzimáticos/química , Inibidores Enzimáticos/farmacologia , Avaliação Pré-Clínica de Medicamentos/métodos , Humanos , Bases de Dados de Produtos Farmacêuticos , Redes Neurais de Computação , Bases de Dados de Compostos QuímicosRESUMO
Ensuring the safety and efficacy of chemical compounds is crucial in small-molecule drug development. In the later stages of drug development, toxic compounds pose a significant challenge, losing valuable resources and time. Early and accurate prediction of compound toxicity using deep learning models offers a promising solution to mitigate these risks during drug discovery. In this study, we present the development of several deep-learning models aimed at evaluating different types of compound toxicity, including acute toxicity, carcinogenicity, hERG_cardiotoxicity (the human ether-a-go-go related gene caused cardiotoxicity), hepatotoxicity, and mutagenicity. To address the inherent variations in data size, label type, and distribution across different types of toxicity, we employed diverse training strategies. Our first approach involved utilizing a graph convolutional network (GCN) regression model to predict acute toxicity, which achieved notable performance with Pearson R 0.76, 0.74, and 0.65 for intraperitoneal, intravenous, and oral administration routes, respectively. Furthermore, we trained multiple GCN binary classification models, each tailored to a specific type of toxicity. These models exhibited high area under the curve (AUC) scores, with an impressive AUC of 0.69, 0.77, 0.88, and 0.79 for predicting carcinogenicity, hERG_cardiotoxicity, mutagenicity, and hepatotoxicity, respectively. Additionally, we have used the approved drug dataset to determine the appropriate threshold value for the prediction score in model usage. We integrated these models into a virtual screening pipeline to assess their effectiveness in identifying potential low-toxicity drug candidates. Our findings indicate that this deep learning approach has the potential to significantly reduce the cost and risk associated with drug development by expediting the selection of compounds with low toxicity profiles. Therefore, the models developed in this study hold promise as critical tools for early drug candidate screening and selection.
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Aprendizado Profundo , Humanos , Descoberta de Drogas/métodos , Animais , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos , Cardiotoxicidade/etiologiaRESUMO
BACKGROUND: Class III peroxidases (PODs) perform crucial functions in various developmental processes and responses to biotic and abiotic stresses. However, their roles in wheat seed dormancy (SD) and germination remain elusive. RESULTS: Here, we identified a wheat class III POD gene, named TaPer12-3A, based on transcriptome data and expression analysis. TaPer12-3A showed decreasing and increasing expression trends with SD acquisition and release, respectively. It was highly expressed in wheat seeds and localized in the endoplasmic reticulum and cytoplasm. Germination tests were performed using the transgenic Arabidopsis and rice lines as well as wheat mutant mutagenized with ethyl methane sulfonate (EMS) in Jing 411 (J411) background. These results indicated that TaPer12-3A negatively regulated SD and positively mediated germination. Further studies showed that TaPer12-3A maintained H2O2 homeostasis by scavenging excess H2O2 and participated in the biosynthesis and catabolism pathways of gibberellic acid and abscisic acid to regulate SD and germination. CONCLUSION: These findings not only provide new insights for future functional analysis of TaPer12-3A in regulating wheat SD and germination but also provide a target gene for breeding wheat varieties with high pre-harvest sprouting resistance by gene editing technology.
Assuntos
Germinação , Dormência de Plantas , Triticum , Triticum/genética , Triticum/enzimologia , Triticum/fisiologia , Dormência de Plantas/genética , Germinação/genética , Sementes/genética , Sementes/crescimento & desenvolvimento , Sementes/fisiologia , Regulação da Expressão Gênica de Plantas , Proteínas de Plantas/genética , Proteínas de Plantas/metabolismo , Peróxido de Hidrogênio/metabolismo , Giberelinas/metabolismo , Arabidopsis/genética , Arabidopsis/fisiologia , Peroxidases/genética , Peroxidases/metabolismo , Plantas Geneticamente Modificadas , Ácido Abscísico/metabolismo , Genes de PlantasRESUMO
BACKGROUND: B-box (BBX) proteins are a type of zinc finger proteins containing one or two B-box domains. They play important roles in development and diverse stress responses of plants, yet their roles in wheat remain unclear. RESULTS: In this study, 96 BBX genes were identified in the wheat genome and classified into five subfamilies. Subcellular localization prediction results showed that 68 TaBBXs were localized in the nucleus. Protein interaction prediction analysis indicated that interaction was one way that these proteins exerted their functions. Promoter analysis indicated that TaBBXs may play important roles in light signal, hormone, and stress responses. qRT-PCR analysis revealed that 14 TaBBXs were highly expressed in seeds compared with other tissues. These were probably involved in seed dormancy and germination, and their expression patterns were investigated during dormancy acquisition and release in the seeds of wheat varieties Jing 411 and Hongmangchun 21, showing significant differences in seed dormancy and germination phenotypes. Subcellular localization analysis confirmed that the three candidates TaBBX2-2 A, TaBBX4-2 A, and TaBBX11-2D were nuclear proteins. Transcriptional self-activation experiments further demonstrated that TaBBX4-2A was transcriptionally active, but TaBBX2-2A and TaBBX11-2D were not. Protein interaction analysis revealed that TaBBX2-2A, TaBBX4-2A, and TaBBX11-2D had no interaction with each other, while TaBBX2-2A and TaBBX11-2D interacted with each other, indicating that TaBBX4-2A may regulate seed dormancy and germination by transcriptional regulation, and TaBBX2-2A and TaBBX11-2D may regulate seed dormancy and germination by forming a homologous complex. CONCLUSIONS: In this study, the wheat BBX gene family was identified and characterized at the genomic level by bioinformatics analysis. These observations provide a theoretical basis for future studies on the functions of BBXs in wheat and other species.
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Germinação , Família Multigênica , Dormência de Plantas , Proteínas de Plantas , Triticum , Triticum/genética , Triticum/fisiologia , Dormência de Plantas/genética , Germinação/genética , Proteínas de Plantas/genética , Proteínas de Plantas/metabolismo , Sementes/genética , Sementes/crescimento & desenvolvimento , Regulação da Expressão Gênica de Plantas , Genes de Plantas , Simulação por Computador , FilogeniaRESUMO
Deep learning is an artificial intelligence technique in which models express geometric transformations over multiple levels. This method has shown great promise in various fields, including drug development. The availability of public structure databases prompted the researchers to use generative artificial intelligence models to narrow down their search of the chemical space, a novel approach to chemogenomics and de novo drug development. In this study, we developed a strategy that combined an accelerated LSTM_Chem (long short-term memory for de novo compounds generation), dense fully convolutional neural network (DFCNN), and docking to generate a large number of de novo small molecular chemical compounds for given targets. To demonstrate its efficacy and applicability, six important targets that account for various human disorders were used as test examples. Moreover, using the M protease as a proof-of-concept example, we find that iteratively training with previously selected candidates can significantly increase the chance of obtaining novel compounds with higher and higher predicted binding affinities. In addition, we also check the potential benefit of obtaining reliable final de novo compounds with the help of MD simulation and metadynamics simulation. The generation of de novo compounds and the discovery of binders against various targets proposed here would be a practical and effective approach. Assessing the efficacy of these top de novo compounds with biochemical studies is promising to promote related drug development.
Assuntos
Aprendizado Profundo , Inteligência Artificial , Simulação por Computador , Desenho de Fármacos , Humanos , Redes Neurais de ComputaçãoRESUMO
KEY MESSAGE: Ten stable loci for freezing tolerance (FT) in wheat were detected by genome-wide association analysis. The putative candidate gene TaRPM1-7BL underlying the major locus QFT.ahau-7B.2 was identified and validated. Frost damage restricts wheat growth, development, and geographical distribution. However, the genetic mechanism of freezing tolerance (FT) remains unclear. Here, we evaluated FT phenotypes of 245 wheat varieties and lines, and genotyped them using a Wheat 90 K array. The association analysis showed that ten stable loci were significantly associated with FT (P < 1 × 10-4), and explained 6.45-26.33% of the phenotypic variation. In particular, the major locus QFT.ahau-7B.2 was consistently related to all nine sets of FT phenotypic data. Based on five cleaved amplified polymorphic sequence (CAPS) markers closely linked to QFT.ahau-7B.2, we narrowed down the target region to the 570.67-571.16 Mb interval (0.49 Mb) on chromosome 7B, in which four candidate genes were annotated. Of these, only TaRPM1-7BL exhibited consistent differential expression after low temperature treatment between freezing-tolerant and freezing-sensitive varieties. The results of cloning and whole-exome capture sequencing indicated that there were two main haplotypes for TaRPM1-7BL, including freezing-tolerant Hap1 and freezing-sensitive Hap2. Based on the representative SNP (+1956, A/G), leading to an amino acid change in the NBS domain, a CAPS marker (CAPS-TaRPM1-7BL) was developed and validated in 431 wheat varieties (including the above 245 materials) and 318 F2 lines derived from the cross of 'Annong 9267' (freezing-tolerant) × 'Yumai 9' (freezing-sensitive). Subsequently, the TaRPM1-7BL gene was silenced in 'Yumai 9' by virus-induced gene silencing (VIGS), and these silenced wheat seedlings exhibited enhanced FT phenotypes, suggesting that TaRPM1-7BL negatively regulates FT. These findings are valuable for understanding the complex genetic basis of FT in wheat.
Assuntos
Plântula , Triticum , Congelamento , Plântula/genética , Triticum/genética , Estudo de Associação Genômica Ampla , Fenótipo , Locos de Características QuantitativasRESUMO
OBJECTIVE: To analyze the diagnostic efficacy of the periportal hypoechoic band (PHB) in the histological stage of patients with primary biliary cholangitis (PBC). METHODS: We prospectively included 77 cases of PBC pathologically or clinically confirmed, and high-frequency ultrasound (HFUS) measurements of the PHB were performed in all included patients. Ludwig staging system of histopathology was used as the gold standard. RESULTS: The width of the PHB was positively correlated with histological staging (r = 0.844, p < 0.001). By area under the receiving operating characteristic curve (AUROC), the best cutoff value for PHB for advanced stage (≥ stage 3) was 2.4 mm (AUROC: 0.934; 95%CI: 0.841-0.981) and 0.93 for sensitivity, and 0.91 for specificity, the concordance rates of PHB vs. liver biopsy was 90.3%. The correct rate for early-stage PBC was 87.9% and for the progressive stage was 93.1%. After multi-factor regression analysis, the PHB (OR = 1.331, CI = 1.105-1.603, p = 0.003) and total bilirubin (OR = 1.156, CI = 1.041-1.285, p = 0.007) were independent influencing factors for progressive PBC. CONCLUSIONS: Measurement of the PHB to assess advanced PBC is a simple and effective method. This method may complement current methods for the histological staging assessment of patients with PBC. REGISTRATION: Clinical trial registration: ChiCTR 2000032053, 2020/04/19. CLINICAL RELEVANCE STATEMENT: The measurement of periportal hypoechoic band (PHB) provides a simple and easy assessment of the degree of disease progression in patients with PBC and provides an important clinical reference in predicting the histological staging of PBC from an ultrasound perspective. KEY POINTS: ⢠The PHB is correlated with histological staging in the patient with PBC. ⢠The area under the ROC curves of PHB for detecting advanced stage (≥ stage 3) were 0.934 and 0.93 for sensitivity, and 0.91 for specificity, the concordance rates of PHB vs. liver biopsy was 90.3%. The application of PHB can better assess the advanced PBC. ⢠Measurement of the PHB to assess advanced PBC is a simple and effective method that can significantly reduce the need for liver biopsy.
Assuntos
Colangite , Cirrose Hepática Biliar , Humanos , Cirrose Hepática Biliar/diagnóstico por imagem , Curva ROC , Biópsia , Progressão da Doença , Colangite/diagnóstico por imagem , Colangite/patologiaRESUMO
In the current context of the increasing incidence of breast cancer, we aim to develop an efficient drug carrier for breast cancer by constructing an innovative complex consisting of a metal-organic framework (MOF) and a hydrogel. The aim of this initiative is to provide new ideas and tools for breast cancer treatment strategies through scientific research, so as to address the current challenges in breast cancer treatment. In the present study, by employment of a new Co(II)-based coordination polymer with the chemical formula of [Co(H2O)(CH3OH)L]n (1) (H2L = 5-(1 H-tetrazol-5-yl)nicotinic acid) was solvothermally synthesized by reaction of Co(NO3)2·6H2O a mixed solvent of MeOH and water. The characteristics of ligand-based absorption and emission, as unveiled by ultraviolet and fluorescence spectroscopy tests, offer insights into the distinctive electronic transitions and structural features originating from the ligand in compound 1. Using natural polysaccharide hyaluronic acid (HA) and carboxymethyl chitosan (CMCS) as raw materials, HA/CMCS hydrogels were successfully prepared by chemical method and their internal morphology was studied by scanning electron microscopy. Using paclitaxel as a drug model, we further designed and synthesized a novel metal gel particle-loaded paclitaxel drug and evaluated its inhibitory effect on breast cancer cells. Finally, the hypothesized interactions between the complex and the receptor have been confirmed through molecular docking simulation, and multiple polar interactions have been verified, which further proves the potential anti-cancer capability and excellent bioactivity. Based on this, this composite material prepared from a novel Co(II)-coordinated polymer with paclitaxel hydrogel could provide a useful pathway for the identification and treatment of breast cancer.
RESUMO
Accurate repair of DNA double-stranded breaks by homologous recombination preserves genome integrity and inhibits tumorigenesis. Cyclic GMP-AMP synthase (cGAS) is a cytosolic DNA sensor that activates innate immunity by initiating the STING-IRF3-type I IFN signalling cascade1,2. Recognition of ruptured micronuclei by cGAS links genome instability to the innate immune response3,4, but the potential involvement of cGAS in DNA repair remains unknown. Here we demonstrate that cGAS inhibits homologous recombination in mouse and human models. DNA damage induces nuclear translocation of cGAS in a manner that is dependent on importin-α, and the phosphorylation of cGAS at tyrosine 215-mediated by B-lymphoid tyrosine kinase-facilitates the cytosolic retention of cGAS. In the nucleus, cGAS is recruited to double-stranded breaks and interacts with PARP1 via poly(ADP-ribose). The cGAS-PARP1 interaction impedes the formation of the PARP1-Timeless complex, and thereby suppresses homologous recombination. We show that knockdown of cGAS suppresses DNA damage and inhibits tumour growth both in vitro and in vivo. We conclude that nuclear cGAS suppresses homologous-recombination-mediated repair and promotes tumour growth, and that cGAS therefore represents a potential target for cancer prevention and therapy.
Assuntos
Núcleo Celular/metabolismo , Transformação Celular Neoplásica/patologia , Neoplasias/metabolismo , Neoplasias/patologia , Nucleotidiltransferases/metabolismo , Reparo de DNA por Recombinação , Transporte Ativo do Núcleo Celular , Adulto , Animais , Proteínas de Ciclo Celular/antagonistas & inibidores , Proteínas de Ciclo Celular/metabolismo , Linhagem Celular Tumoral , Núcleo Celular/enzimologia , Quebras de DNA de Cadeia Dupla , Dano ao DNA , Feminino , Células HEK293 , Humanos , Peptídeos e Proteínas de Sinalização Intracelular/antagonistas & inibidores , Peptídeos e Proteínas de Sinalização Intracelular/metabolismo , Masculino , Proteínas de Membrana/metabolismo , Camundongos , Camundongos Endogâmicos C57BL , Proteínas de Neoplasias/metabolismo , Neoplasias/genética , Nucleotidiltransferases/deficiência , Fosforilação , Ftalazinas/farmacologia , Piperazinas/farmacologia , Poli(ADP-Ribose) Polimerase-1/antagonistas & inibidores , Poli(ADP-Ribose) Polimerase-1/metabolismo , Ligação Proteica/efeitos dos fármacos , Reparo de DNA por Recombinação/genética , Quinases da Família src/metabolismoRESUMO
BACKGROUND: The prognostic potential of immune-related genes, particularly immune checkpoint inhibitors (ICIs) and long non-coding RNAs (lncRNAs), is gaining attention for evaluating the prognosis of breast cancer patients. METHODS: We analyzed 23 datasets to identify 15 ICI-related mRNAs and 5 immune-related lncRNAs, creating a robust immune score (IS). This score was used to classify patients into high and low IS groups and assess their survival outcomes. RESULTS: Patients with high IS showed significantly poorer overall survival (OS) and progression-free survival (PFS) compared to those with low IS. Multivariate Cox regression analysis confirmed IS as an independent prognostic factor. Additionally, high IS was associated with higher mutation loads and neoantigen profiles, while low IS correlated with enhanced immune cell infiltration. CONCLUSIONS: The immune score developed from ICI-related mRNAs and lncRNAs effectively predicts the prognosis of breast cancer patients and highlights the differential immune and inflammatory responses between patients with varying levels of immune score. This underscores the relevance of IS in guiding therapeutic decisions and tailoring patient management strategies in clinical settings.
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Neoplasias da Mama , RNA Longo não Codificante , Humanos , Neoplasias da Mama/genética , Neoplasias da Mama/imunologia , Neoplasias da Mama/mortalidade , Feminino , Prognóstico , RNA Longo não Codificante/genética , RNA Mensageiro/genética , Pessoa de Meia-Idade , Inflamação/genética , Inibidores de Checkpoint Imunológico/uso terapêutico , Biomarcadores Tumorais/genética , TranscriptomaRESUMO
BACKGROUND: Epidermal growth factor receptor (EGFR) fusions are rare but potentially actionable oncogenic drivers across multiple solid tumors. However, the distribution and molecular characteristics of EGFR fusions in Chinese patients with solid malignancies have not been explored. METHODS: Panel-based next-generation sequencing (NGS) data of 35,023 patients with various types of solid tumors was collected and analyzed from the Simcere Diagnostics (Nanjing, China) database. A 9563-patient cohort was derived from The Cancer Genome Atlas (TCGA) to explore the relationship between EGFR fusion status and overall survival (OS). RESULTS: In this study, prevalence of functional EGFR fusions was 0.303% (106/35,023) in total across solid tumors, which occur more commonly in gastroesophageal junction cancer (1/61, 1.613%), followed by medulloblastoma (1/66, 1.515%) and glioma (33/2409, 1.370%). Analysis showed a prevalence for fusion partners in different tumor types. The top 3 co-mutant genes with EGFR fusion were TP53 (mutation frequency, MF: 65%), BRCA2 (MF: 43%), and ALK (MF: 41%). Furthermore, patients in the EGFR fusion group had a significantly shorter OS than those in the non-EGFR fusion group (p < 0.0001) in the TCGA cohort, suggesting that EGFR fusion might be a high-risk factor for poor prognosis. CONCLUSIONS: Our study is the first retrospective analysis of EGFR fusions in a large-scale solid tumor population, which may provide a reference for future EGFR-TKI clinical trials with EGFR fusions.
Assuntos
Receptores ErbB , Sequenciamento de Nucleotídeos em Larga Escala , Neoplasias , Proteínas de Fusão Oncogênica , Humanos , Receptores ErbB/genética , Masculino , Feminino , Proteínas de Fusão Oncogênica/genética , Prognóstico , Taxa de Sobrevida , Pessoa de Meia-Idade , Neoplasias/genética , Neoplasias/patologia , Adulto , Sequenciamento de Nucleotídeos em Larga Escala/métodos , China/epidemiologia , Biomarcadores Tumorais/genética , Seguimentos , Proteína BRCA2/genética , Proteína Supressora de Tumor p53/genética , Quinase do Linfoma Anaplásico/genética , Idoso , Adulto Jovem , Mutação , Adolescente , Estudos Retrospectivos , População do Leste AsiáticoRESUMO
BACKGROUND: Pregnancy and gestation information is routinely recorded in electronic medical record (EMR) systems across China in various data sets. The combination of data on the number of pregnancies and gestations can imply occurrences of abortions and other pregnancy-related issues, which is important for clinical decision-making and personal privacy protection. However, the distribution of this information inside EMR is variable due to inconsistent IT structures across different EMR systems. A large-scale quantitative evaluation of the potential exposure of this sensitive information has not been previously performed, ensuring the protection of personal information is a priority, as emphasized in Chinese laws and regulations. OBJECTIVE: This study aims to perform the first nationwide quantitative analysis of the identification sites and exposure frequency of sensitive pregnancy and gestation information. The goal is to propose strategies for effective information extraction and privacy protection related to women's health. METHODS: This study was conducted in a national health care data network. Rule-based protocols for extracting pregnancy and gestation information were developed by a committee of experts. A total of 6 different sub-data sets of EMRs were used as schemas for data analysis and strategy proposal. The identification sites and frequencies of identification in different sub-data sets were calculated. Manual quality inspections of the extraction process were performed by 2 independent groups of reviewers on 1000 randomly selected records. Based on these statistics, strategies for effective information extraction and privacy protection were proposed. RESULTS: The data network covered hospitalized patients from 19 hospitals in 10 provinces of China, encompassing 15,245,055 patients over an 11-year period (January 1, 2010-December 12, 2020). Among women aged 14-50 years, 70% were randomly selected from each hospital, resulting in a total of 1,110,053 patients. Of these, 688,268 female patients with sensitive reproductive information were identified. The frequencies of identification were variable, with the marriage history in admission medical records being the most frequent at 63.24%. Notably, more than 50% of female patients were identified with pregnancy and gestation history in nursing records, which is not generally considered a sub-data set rich in reproductive information. During the manual curation and review process, 1000 cases were randomly selected, and the precision and recall rates of the information extraction method both exceeded 99.5%. The privacy-protection strategies were designed with clear technical directions. CONCLUSIONS: Significant amounts of critical information related to women's health are recorded in Chinese routine EMR systems and are distributed in various parts of the records with different frequencies. This requires a comprehensive protocol for extracting and protecting the information, which has been demonstrated to be technically feasible. Implementing a data-based strategy will enhance the protection of women's privacy and improve the accessibility of health care services.
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Confidencialidade , Registros Eletrônicos de Saúde , Humanos , Gravidez , Feminino , China , Estudos Retrospectivos , AdultoRESUMO
DNA-PKcs is a crucial protein target involved in DNA repair and response pathways, with its abnormal activity closely associated with the occurrence and progression of various cancers. In this study, we employed a deep learning-based screening and molecular dynamics (MD) simulation-based pipeline, identifying eight candidates for DNA-PKcs targets. Subsequent experiments revealed the effective inhibition of DNA-PKcs-mediated cell proliferation by three small molecules (5025-0002, M769-1095, and V008-1080). These molecules exhibited anticancer activity with IC50 (inhibitory concentration at 50%) values of 152.6 µM, 30.71 µM, and 74.84 µM, respectively. Notably, V008-1080 enhanced homology-directed repair (HDR) mediated by CRISPR/Cas9 while inhibiting non-homologous end joining (NHEJ) efficiency. Further investigations into the structure-activity relationships unveiled the binding sites and critical interactions between these small molecules and DNA-PKcs. This is the first application of DeepBindGCN_RG in a real drug screening task, and the successful discovery of a novel DNA-PKcs inhibitor demonstrates its efficiency as a core component in the screening pipeline. Moreover, this study provides important insights for exploring novel anticancer therapeutics and advancing the development of gene editing techniques by targeting DNA-PKcs.
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Proteína Quinase Ativada por DNA , Simulação de Dinâmica Molecular , Humanos , Proteína Quinase Ativada por DNA/antagonistas & inibidores , Proteína Quinase Ativada por DNA/metabolismo , Inibidores de Proteínas Quinases/farmacologia , Inibidores de Proteínas Quinases/química , Proliferação de Células/efeitos dos fármacos , Relação Estrutura-Atividade , Ensaios de Triagem em Larga Escala/métodos , Antineoplásicos/farmacologia , Antineoplásicos/química , Linhagem Celular Tumoral , Reparo do DNA por Junção de Extremidades/efeitos dos fármacos , Simulação de Acoplamento Molecular , Sítios de LigaçãoRESUMO
BACKGROUND: The aim of this study was to investigate the effects of covalent and non-covalent interactions between myofibrillar protein (MP) and cyanidin-3-O-glucoside (C3G) on protein structure, binding sites, and digestion properties. Four methods of inducing covalent cross-linking were used in the preparation of MP-C3G conjugates, including tyrosinase-catalyzed oxidation, alkaline pH shift treatment, free radical grafting, and ultrasonic treatment. A comparison was made between MP-C3G conjugates and complexes, and the analysis included sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), C3G binding ratio, liquid chromatography-tandem mass spectrometry (LC-MS/MS), protein side-chain amino acids, circular dichroism spectroscopy, three-dimensional fluorescence, particle size, and in vitro simulated digestion. RESULTS: Covalent bonding between C3G and amino acid side chains in MP was confirmed by LC-MS/MS. In covalent bonding, tryptophan residues, free amino groups and sulfhydryl groups were all implicated. Among the 22 peptides covalently modified by C3G, 30 modification sites were identified, located in lysine, histidine, tryptophan, arginine and cysteine. In vitro simulated digestion experiments showed that the addition of C3G significantly reduced the digestibility of MP, with the covalent conjugate showing lower digestibility than the non-covalent conjugate. Moreover, the digestibility of protein decreased more during intestinal digestion, possibly because covalent cross-linking of C3G and MP further inhibited trypsin targeting sites (lysine and arginine). CONCLUSION: Covalent cross-linking of C3G with myofibrillar proteins significantly affected protein structure and reduced protein digestibility by occupying more trypsin binding sites. © 2023 Society of Chemical Industry.
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Lisina , Triptofano , Cromatografia Líquida , Tripsina/metabolismo , Espectrometria de Massas em Tandem , Sítios de Ligação , Antocianinas/química , Glucosídeos/metabolismo , Digestão , ArgininaRESUMO
BACKGROUND: Floral nectar is the most common reward flowers offered to pollinators. The quality and quantity of nectar produced by a plant species provide a key to understanding its interactions with pollinators and predicting rates of reproductive success. However, nectar secretion is a dynamic process with a production period accompanied or followed by reabsorption and reabsorption remains an understudied topic. In this study, we compared nectar volume and sugar concentration in the flowers of two long-spurred orchid species, Habenaria limprichtii and H. davidii (Orchidaceae). We also compared sugar concentration gradients within their spurs and rates of reabsorption of water and sugars. RESULTS: Both species produced diluted nectar with sugar concentrations from 17 to 24%. Analyses of nectar production dynamics showed that as flowers of both species wilted almost all sugar was reabsorbed while the original water was retained in their spurs. We established a nectar sugar concentration gradient for both species, with differences in sugar concentrations at their spur's terminus and at their spur's entrance (sinus). Sugar concentration gradient levels were 1.1% in H. limprichtii and 2.8% in H. davidii, both decreasing as flowers aged. CONCLUSION: We provided evidence for the reabsorption of sugars but not water occurred in wilted flowers of both Habenaria species. Their sugar concentration gradients vanished as flowers aged suggesting a slow process of sugar diffusion from the nectary at the spur's terminus where the nectar gland is located. The processes of nectar secretion/reabsorption in conjunction with the dilution and hydration of sugar rewards for moth pollinators warrant further study.
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Orchidaceae , Néctar de Plantas , Açúcares , Carboidratos/análise , Flores/química , PolinizaçãoRESUMO
BACKGROUND: Arteriosclerosis and atherosclerosis are closely related with cardiovascular disease (CVD) risk. Remnant cholesterol (RC) could predict CVD. However, its effect on joint arteriosclerosis and atherosclerosis progression remains unclear. This study aims to evaluate the association of RC with joint arteriosclerosis and atherosclerosis progression trajectories in the general population. METHODS: This study collected data across five biennial surveys of the Beijing Health Management Cohort from 2010 to 2019. Multi-trajectory model was used to determine the joint arteriosclerosis and atherosclerosis progression patterns by brachial-ankle pulse wave velocity (baPWV) and ankle brachial index (ABI). We also performed discordance analyses for RC vs. low density lipoprotein cholesterol (LDL-C) using ordinal logistics model. RESULTS: A total of 3186 participants were included, with three clusters following distinct arteriosclerosis and atherosclerosis progression patterns identified using a multi-trajectory model. In the multivariable-adjusted ordinal logistics analyses, RC was significantly associated with baPWV and ABI progression (OR: 1.20; 95% CI: 1.13-1.28, per 10 mg/dL). For the discordance analyses, the discordant low RC group was associated with decreased risk compared to the concordant group (OR: 0.73; 95% CI: 0.60-0.89). People with a high RC level were at an increased risk of joint arteriosclerosis and atherosclerosis progression, even with optimal LDL-C. CONCLUSIONS: RC is independently associated with joint arteriosclerosis and atherosclerosis progression beyond LDL-C. RC could be an earlier risk factor than LDL-C of arteriosclerosis and atherosclerosis in the general population.
Assuntos
Índice Tornozelo-Braço , Aterosclerose , Humanos , LDL-Colesterol , Análise de Onda de Pulso , Aterosclerose/epidemiologia , Colesterol , Fatores de RiscoRESUMO
BACKGROUND: Impaired sensitivity to thyroid hormones is a newly proposed clinical entity associated with hyperuricemia in the subclinical hypothyroid population. However, it is unknown whether the association exists in the euthyroid population. This study aimed to explore the association of impaired sensitivity to thyroid hormones (assessed by the thyroid feedback quantile-based index [TFQI], parametric thyroid feedback quantile-based index [PTFQI], thyrotrophic thyroxine resistance index [TT4RI] and thyroid-stimulating hormone index [TSHI]) with hyperuricemia and quantify the mediating effect of body mass index BMI in the euthyroid population. METHODS: This cross-sectional study enrolled Chinese adults aged ≥ 20 years who participated in the Beijing Health Management Cohort (2008-2019). Adjusted logistic regression models were used to explore the association between indices of sensitivity to thyroid hormones and hyperuricemia. Odds ratios [OR] and absolute risk differences [ARD] were calculated. Mediation analyses were performed to estimate direct and indirect effects through BMI. RESULTS: Of 30,857 participants, 19,031 (61.7%) were male; the mean (SD) age was 47.3 (13.3) years; and 6,515 (21.1%) had hyperuricemia. After adjusting for confounders, individuals in the highest group of thyroid hormone sensitivity indices were associated with an increased prevalence of hyperuricemia compared with the lowest group (TFQI: OR = 1.18, 95% CI 1.04-1.35; PTFQI: OR = 1.20, 95% CI 1.05-1.36; TT4RI: OR = 1.17, 95% CI 1.08-1.27; TSHI: OR = 1.12, 95% CI 1.04-1.21). BMI significantly mediated 32.35%, 32.29%, 39.63%, and 37.68% of the associations of TFQI, PTFQI, TT4RI and TSHI with hyperuricemia, respectively. CONCLUSIONS: Our research revealed that BMI mediated the association between impaired sensitivity to thyroid hormones and hyperuricemia in the euthyroid population. These findings could provide useful evidence for understanding the interaction between impaired sensitivity to thyroid hormone and hyperuricemia in euthyroid individuals and suggest the clinical implications of weight control in terms of impaired thyroid hormones sensitivity.
Assuntos
Hiperuricemia , Adulto , Masculino , Humanos , Feminino , Hiperuricemia/complicações , Estudos Transversais , Hormônios Tireóideos , Obesidade/complicações , Obesidade/epidemiologia , Tiroxina , TireotropinaRESUMO
BACKGROUND AND AIMS: Autoimmune hepatitis (AIH) is a rare and chronic autoimmune liver disease. While genetic factors are believed to play a crucial role in the etiopathogenesis of AIH, our understanding of these genetic risk factors is still limited. In this study, we aimed to identify susceptibility loci to further understand the pathogenesis of this disease. APPROACH AND RESULTS: We conducted a case-control association study of 1,622 Chinese patients with AIH type 1 and 10,466 population controls from two independent cohorts. A meta-analysis was performed to ascertain variants associated with AIH type 1. A single-nucleotide polymorphism within the human leukocyte antigen (HLA) region showed the strongest association with AIH (rs6932730: OR = 2.32; p = 9.21 × 10-73 ). The meta-analysis also identified two non-HLA loci significantly associated with AIH: CD28/CTLA4/ICOS on 2q33.3 (rs72929257: OR = 1.31; p = 2.92 × 10-9 ) and SYNPR on 3p14.2 (rs6809477: OR = 1.25; p = 5.48 × 10-9 ). In silico annotation, reporter gene assays, and CRISPR activation experiments identified a distal enhancer at 2q33.3 that regulated expression of CTLA4. In addition, variants near STAT1/STAT4 (rs11889341: OR = 1.24; p = 1.34 × 10-7 ), LINC00392 (rs9564997: OR = 0.81; p = 2.53 × 10-7 ), IRF8 (rs11117432: OR = 0.72; p = 6.10 × 10-6 ), and LILRA4/LILRA5 (rs11084330: OR = 0.65; p = 5.19 × 10-6 ) had suggestive association signals with AIH. CONCLUSIONS: Our study identifies two novel loci (CD28/CTLA4/ICOS and SYNPR) exceeding genome-wide significance and suggests four loci as potential risk factors. These findings highlight the importance of costimulatory signaling and neuro-immune interaction in the pathogenesis of AIH.
Assuntos
Hepatite Autoimune , Antígenos CD28/genética , Antígeno CTLA-4/genética , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Antígenos HLA , Hepatite Autoimune/genética , Humanos , Polimorfismo de Nucleotídeo ÚnicoRESUMO
OBJECTIVES: To develop a deep learning (DL) method that can determine the Liver Imaging Reporting and Data System (LI-RADS) grading of high-risk liver lesions and distinguish hepatocellular carcinoma (HCC) from non-HCC based on multiphase CT. METHODS: This retrospective study included 1049 patients with 1082 lesions from two independent hospitals that were pathologically confirmed as HCC or non-HCC. All patients underwent a four-phase CT imaging protocol. All lesions were graded (LR 4/5/M) by radiologists and divided into an internal (n = 886) and external cohort (n = 196) based on the examination date. In the internal cohort, Swin-Transformer based on different CT protocols were trained and tested for their ability to LI-RADS grading and distinguish HCC from non-HCC, and then validated in the external cohort. We further developed a combined model with the optimal protocol and clinical information for distinguishing HCC from non-HCC. RESULTS: In the test and external validation cohorts, the three-phase protocol without pre-contrast showed κ values of 0.6094 and 0.4845 for LI-RADS grading, and its accuracy was 0.8371 and 0.8061, while the accuracy of the radiologist was 0.8596 and 0.8622, respectively. The AUCs in distinguishing HCC from non-HCC were 0.865 and 0.715 in the test and external validation cohorts, while those of the combined model were 0.887 and 0.808. CONCLUSION: The Swin-Transformer based on three-phase CT protocol without pre-contrast could feasibly simplify LI-RADS grading and distinguish HCC from non-HCC. Furthermore, the DL model have the potential in accurately distinguishing HCC from non-HCC using imaging and highly characteristic clinical data as inputs. CLINICAL RELEVANCE STATEMENT: The application of deep learning model for multiphase CT has proven to improve the clinical applicability of the Liver Imaging Reporting and Data System and provide support to optimize the management of patients with liver diseases. KEY POINTS: ⢠Deep learning (DL) simplifies LI-RADS grading and helps distinguish hepatocellular carcinoma (HCC) from non-HCC. ⢠The Swin-Transformer based on the three-phase CT protocol without pre-contrast outperformed other CT protocols. ⢠The Swin-Transformer provide help in distinguishing HCC from non-HCC by using CT and characteristic clinical information as inputs.