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A novel copper metabolism-related signature model for predicting the prognosis,target drugs,and immunotherapy in stomach adenocarcinoma

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Genes & Diseases 2024年第5期11卷 21-24页

作者： Kai Zhuang Siqi Tang Haixin Feng Jinying Zhang Ying Liu Yong Liu Yongjian Su Jiaqi Yu Zunnan Huang Key Laboratory of computer-aided Drug Design of Dongguan City The First Dongguan Affiliated HospitalGuangdong Medical UniversityDongguanGuangdong 523710China Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University Key Laboratory for Research and Development of Natural Drugs of Guangdong ProvinceSchool of PharmacyGuangdong Medical UniversityDongguanGuangdong 523808China School of Public Health Guangdong Medical UniversityDongguanGuangdong 523808China Marine Biomedical research Institute of Guangdong Zhanjiang ZhanjiangGuangdong 524203China

Stomach adenocarcinoma(STAD)is one of the most common gastric neoplasms with a high death ***,there is an urgent need to propose an efficient therapy for *** plays key roles in regulating the distribution of immune cells and affecting the tumor immune escape,and may be a novel indicator of immunotherapy in ***,the specific impact of copper metabolism-related genes(CMRGs)on the patient’s prognosis,tumor microenvironment,and immunotherapeutic response remains unelucidated.

关键词： metabolism stomach adenocarcinoma

Disruption of cyclin D1 degradation leads to the development of mantle cell lymphoma

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Acta Pharmaceutica Sinica B 2024年第7期14卷 2977-2991页

作者： Ke Lu Ming Zhang Hongyu Qin Siyu Shen Haiqing Song Hua Jiang Chunxiang Zhang Guozhi Xiao Liping Tong Qing Jiang Di Chen research Center for computer-aided Drug discovery Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Faculty of Pharmaceutical Sciences Shenzhen Institute of Advanced TechnologyShenzhen 518055China Oncology Department Johns Hopkins University School of MedicineBaltimoreMD 21205USA Division of Spine Surgery the First Affiliated Hospital of Guangxi Medical UniversityNanning 530021China Division of Sports Medicine and Adult Reconstructive Surgery Department of Orthopedic SurgeryNanjing Drum Tower HospitalAffiliated Hospital of Medical SchoolState Key Laboratory of Pharmaceutical BiotechnologyNanjing UniversityNanjing 210008China fWenzhou Institute University of Chinese Academy of SciencesWenzhou 325000China Department of Cardiology Basic Medicine Innovation Center for Cardiometabolic Diseases of Ministry of EducationInstitute of Cardiovascular Researchthe Affiliated HospitalSouthwest Medical UniversityLuzhou 646000China School of Medicine Southern University of Science and TechnologyShenzhen 518055China

Cyclin D1 has been recognized as an oncogene due to its abnormal upregulation in different types of ***,we demonstrated that cyclin D1 is SUMOylated,and we identified Itch as a specific E3 ligase recognizing SUMOylated cyclin D1 and mediating SUMO-induced ubiquitination and proteasome degradation of cyclin *** generated cyclin D1 mutant mice with mutations in the SUMOylation site,phosphorylation site,or both sites of cyclin D1,and found that double mutant mice developed a Mantle cell lymphoma(MCL)-like *** showed that arsenic trioxide(ATO)enhances cyclin D1 SUMOylation-mediated degradation through inhibition of cyclin D1 deSUMOylation enzymes,leading to MCL cell *** of severe combined immunodeficiency(SCID)mice grafted with MCL cells with ATO resulted in a significant reduction in tumor *** this study,we provide novel insights into the mechanisms of MCL tumor development and cyclin D1 regulation and discover a new strategy for MCL treatment.

关键词： Cyclin D1 SUMOylation Mantle cell lymphoma Arsenic trioxide SENP2 Proteasome degradation

αExtractor: a system for automatic extraction of chemical information from biomedical literature

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Science China(Life Sciences) 2024年第3期67卷 618-621页

作者： Jiacheng Xiong Xiaohong Liu Zhaojun Li Hongzhong Xiao Guangchao Wang Zhenjiang Niu Chaoyuan Fei Feisheng Zhong Gang Wang Wei Zhang Zunyun Fu Zhiguo Liu Kaixian Chen Hualiang Jiang Mingyue Zheng Drug discovery and Design Center State Key Laboratory of Drug ResearchShanghai Institute of Materia MedicaChinese Academy of SciencesShanghai 201203China University of Chinese Academy of Sciences Beijing 100049China AI Department Suzhou Alphama Biotechnology Co.Ltd.Suzhou 215125China College of computer and Information Engineering Dezhou UniversityDezhou 253023China

Dear Editor,Great progress has been made using artificial intelligence(AI) techniques in learning knowledge from biomedical databases in recent years, revolutionizing the study of many fields, such as protein structure prediction and protein design(Madani et al., 2023). However, there is massive biomedical knowledge not curated in the form of structured data but hidden in primary scientific literature.

关键词： has such knowledge

Deep simulated annealing for the discovery of novel dental anesthetics with local anesthesia and anti-inflammatory properties

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Acta Pharmaceutica Sinica B 2024年第7期14卷 3086-3109页

作者： Yihang Hao Haofan Wang Xianggen Liu Wenrui Gai Shilong Hu Wencheng Liu Zhuang Miao Yu Gan Xianghua Yu Rongjia Shi Yongzhen Tan Ting Kang Ao Hai Yi Zhao Yihang Fu Yaling Tang Ling Ye Jin Liu Xinhua Liang Bowen Ke State Key Laboratory of Oral Diseases and National Clinical research Center for Oral Diseases West China Hospital of StomatologySichuan UniversityChengdu 610041China College of computer Science Sichuan UniversityChengdu 610065China Department of Anesthesiology Laboratory of Anesthesia and Critical Care MedicineNational-Local Joint Engineering Research Centre of Translational Medicine of AnesthesiologyFrontiers Science Center for Disease-Related Molecular NetworkWest China HospitalSichuan UniversityChengdu 610041China

Multifunctional therapeutics have emerged as a solution to the constraints imposed by drugs with singular or insufficient therapeutic *** primary challenge is to integrate diverse pharmacophores within a single-molecule *** address this,we introduced DeepSA,a novel edit-based generative framework that utilizes deep simulated annealing for the modification of articaine,a wellknown local *** integrates deep neural networks into metaheuristics,effectively constraining molecular space during compound *** framework employs a sophisticated objective function that accounts for scaffold preservation,anti-inflammatory properties,and covalent *** a sequence of local editing to navigate the molecular space,DeepSA successfully identified AT-17,a derivative exhibiting potent analgesic properties and significant anti-inflammatory activity in various animal *** insights into AT-17 revealed its dual mode of action:selective inhibition of NaV1.7 and 1.8 channels,contributing to its prolonged local anesthetic effects,and suppression of inflammatory mediators via modulation of the NLRP3 inflammasome *** findings not only highlight the efficacy of AT-17 as a multifunctional drug candidate but also highlight the potential of DeepSA in facilitating AI-enhanced drug discovery,particularly within stringent chemical constraints.

关键词： Multifunctional drugs Deep simulated annealing Molecule generation Articaine derivatives AI-enhanced drug discovery

Microsnoop: A generalist tool for microscopy image representation

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The Innovation 2024年第1期5卷 109-117页

作者： Dejin Xun Rui Wang Xingcai Zhang Yi Wang Pharmaceutical Informatics Institute College of Pharmaceutical SciencesZhejiang UniversityHangzhou 310058China State Key Lab of computer-aided Design&computer Graphics Zhejiang UniversityHangzhou 310058China John A.Paulson School of Engineering and Applied Sciences Harvard UniversityCambridgeMA 02138USA Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University Hangzhou 310018China National Key Laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River DeltaZhejiang UniversityJiaxing 314100China

Accurate profiling of microscopy images from small scale to high throughput is an essential procedure in basic and applied biological ***,we present Microsnoop,a novel deep learning–based representation tool trained on large-scale microscopy images using masked self-supervised *** can process various complex and heterogeneous images,and we classified images into three categories:single-cell,full-field,and batch-experiment *** benchmark study on 10 high-quality evaluation datasets,containing over 2,230,000 images,demonstrated Microsnoop’s robust and state-ofthe-art microscopy image representation ability,surpassing existing generalist and even several custom *** can be integrated with other pipelines to perform tasks such as superresolution histopathology image and multimodal ***,Microsnoop can be adapted to various hardware and can be easily deployed on local or cloud computing *** will regularly retrain and reevaluate the model using communitycontributed data to consistently improve Microsnoop.

关键词： hardware image representation

Transfer learning enhanced graph neural network for aldehyde oxidase metabolism prediction and its experimental application

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Acta Pharmaceutica Sinica B 2024年第2期14卷 623-634页

作者： Jiacheng Xiong Rongrong Cui Zhaojun Li Wei Zhang Runze Zhang Zunyun Fu Xiaohong Liu Zhenghao Li Kaixian Chen Mingyue Zheng Drug discovery and Design Center State Key Laboratory of Drug ResearchShanghai Institute of Materia MedicaChinese Academy of SciencesShanghai 201203China University of Chinese Academy of Sciences Beijing 100049China College of computer and Information Engineering Dezhou UniversityDezhou 253023China AI Department Suzhou Alphama Biotechnology Co.Ltd.Suzhou 215000China Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and TechnologyShanghaiTech UniversityShanghai 200031China State Key Laboratory of Pharmaceutical Biotechnology Nanjing UniversityNanjing 210023China

Aldehyde oxidase(AOX)is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other ***-mediated metabolism can result in unexpected outcomes,such as the production of toxic metabolites and high metabolic clearance,which can lead to the clinical failure of novel therapeutic *** models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism *** this study,we developed a novel graph neural network called AOMP for predicting AOX-mediated *** integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction,while utilizing transfer learning from 13C nuclear magnetic resonance data to enhance its performance on both *** significantly outperformed the benchmark methods in both cross-validation and external *** AOMP,we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability,which were validated through in vitro ***,for the convenience of the community,we established the first online service for AOX metabolism prediction based on AOMP,which is freely available at https://***.

关键词： Drugmetabolism Aldehyde oxidase Transferlearning Graph neural network Kinase inhibitor

Empowering Diagnosis: Cutting-Edge Segmentation and Classification in Lung Cancer Analysis

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computers, Materials & Continua 2024年第6期79卷 4963-4977页

作者： Iftikhar Naseer Tehreem Masood Sheeraz Akram Zulfiqar Ali Awais Ahmad Shafiq Ur Rehman Arfan Jaffar Faculty of computer Sciences&Information Technology The Superior UniversityLahore54000Pakistan Intelligent Data Visual Computing research(IDVCR) Lahore54000Pakistan Information System Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia School of computer Science and Electronic Engineering(CSEE) University of EssexWivenhoe ParkColchesterCO43SQUK

Lung cancer is a leading cause of global mortality *** detection of pulmonary tumors can significantly enhance the survival rate of ***,various computer-aided Diagnostic(CAD)methods have been developed to enhance the detection of pulmonary nodules with high ***,the existing method-ologies cannot obtain a high level of specificity and *** present study introduces a novel model for Lung Cancer Segmentation and Classification(LCSC),which incorporates two improved architectures,namely the improved U-Net architecture and the improved AlexNet *** LCSC model comprises two distinct *** first stage involves the utilization of an improved U-Net architecture to segment candidate nodules extracted from the lung ***,an improved AlexNet architecture is employed to classify lung *** the first stage,the proposed model demonstrates a dice accuracy of 0.855,a precision of 0.933,and a recall of 0.789 for the segmentation of candidate *** suggested improved AlexNet architecture attains 97.06%accuracy,a true positive rate of 96.36%,a true negative rate of 97.77%,a positive predictive value of 97.74%,and a negative predictive value of 96.41%for classifying pulmonary cancer as either benign or *** proposed LCSC model is tested and evaluated employing the publically available dataset furnished by the Lung Image Database Consortium and Image Database Resource Initiative(LIDC-IDRI).This proposed technique exhibits remarkable performance compared to the existing methods by using various evaluation parameters.

关键词： Lung cancer segmentation AlexNet U-Net classification

Prescreening of large-effect markers with multiple strategies improves the accuracy of genomic prediction

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Journal of Integrative Agriculture 2024年第5期23卷 1634-1643页

作者： Keanning Li Bingxing An Mang Liang Tianpeng Chang Tianyu Deng Lili Du Sheng Cao Yueying Du Hongyan Li Lingyang Xu Lupei Zhang Xue Gao Junya LI Huijiang Gao Laboratory of molecular Biology and Bovine Breeding Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijing 100193China Shaanxi Key Laboratory of molecular Biology for Agriculture College of Animal Science and TechnologyNorthwest A&F UniversityYangling712100China College of computer and Information Engineering Tianjin Agricultural UniversityTianjin 300384China College of Animal Science and Technology Qingdao Agricultural UniversityQingdao 266109China Tongliao Animal Agriculture Development Service Center Tongliao 028000China

Presently,integrating multi-omics information into a prediction model has become a ameliorate strategy for genomic selection to improve genomic prediction ***,we set the genomic and transcriptomic data as the training population data,using BSLMM,TWAS,and eQTL mapping to prescreen features according to |β_(b)|>0,top 1%of phenotypic variation explained(PVE),expression-associated single nucleotide polymorphisms(eSNPs),and egenes(false discovery rate(FDR)<0.01),where these loci were set as extra fixed effects(named GBLUP-Fix)and random effects(GFBLUP)to improve the prediction accuracy in the validation population,*** results suggested that both GBLUP-Fix and GFBLUP models could improve the accuracy of longissimus dorsi muscle(LDM),water holding capacity(WHC),shear force(SF),and pH in Huaxi cattle on average from 2.14 to 8.69%,especially the improvement of GFBLUP-TWAS over GBLUP was 13.66%for *** methods also captured more genetic variance than *** study confirmed that multi-omics-assisted large-effects loci prescreening could improve the accuracyofgenomic prediction.

关键词： multi-omics data features prescreening eQTL mapping Huaxi cattle genomic selection

Multi-omics Approach Reveals Influenza-A Virus Target Genes Associated Genomic,Clinical and Immunological Characteristics in Cancers

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Biomedical and Environmental Sciences 2024年第7期37卷 698-715页

作者： Jiaojiao Wang Yong Liao Pinglian Yang Weile Ye Yong Liu Chunxia Xiao Weixiong Liao Chunbo Chen Zhiping Liu Zunnan Huang Center of Scientific research Department of CardiologyMaoming People’s HospitalMaoming 525000GuangdongChina Department of Pharmacy Maoming People’s HospitalMaoming 525000GuangdongChina State Key Laboratory of Bioactive Molecules and Druggability Assessment Jinan UniversityGuangzhou 510632GuangdongChina Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs research College of PharmacyJinan UniversityGuangzhou 510632GuangdongChina Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University Key Laboratory of Computer-Aided Drug Design of Dongguan CityKey Laboratory for Research and Development of Natural Drugs of Guangdong ProvinceSchool of PharmacyGuangdong Medical UniversityDongguan 523808GuangdongChina Department of Critical Care Medicine Maoming People’s HospitalMaoming 525000GuangdongChina

Objective To examine the precise function of influenza A virus target genes(IATGs)in *** Using multi-omics data from the TCGA and TCPA datasets,33 tumor types were evaluated for *** expression in cancer cells was analyzed using transcriptome *** number variation(CNV)was assessed using GISTICS ***’s analysis was used to correlate mRNA expression with methylation *** was used for the enrichment ***’s correlation analysis was used to examine the association between IATG mRNA expression and *** ImmuCellAI algorithm was used to calculate the infiltration scores of 24 immune cell *** In 13 solid tumors,IATG mRNA levels were atypically *** for UCS,UVM,KICH,PCPG,THCA,CHOL,LAMI,and MESO,most cancers contained somatic IATG *** main types of CNVs in IATGs are heterozygous amplifications and *** most tumors,IATG mRNA expression is adversely associated with ***-PCR demonstrated that EGFR,ANXA5,CACNA1C,CD209,UVRAG were upregulated and CLEC4M was downregulated in KIRC cell lines,consistent with the TCGA and GTEx *** Genomic changes and clinical characteristics of IATGs were identified,which may offer fresh perspectives linking the influenza A virus to cancer.

关键词： Genomic changes Immune microenvironment Prognosis Drug resistance Experimental validation