Drug discovery is a complex and highly systematic process encompassing multiple critical stages,including target identification,bioactive molecule discovery,preclinical research,clinical trials,regulatory review,post-...Drug discovery is a complex and highly systematic process encompassing multiple critical stages,including target identification,bioactive molecule discovery,preclinical research,clinical trials,regulatory review,post-marketing surveillance,and others[1].This process typically spans many years and is often accompanied by high failure rates and substantial resource consumption.In recent years,driven by large amounts of biomedical data,artificial intelligence(AI)has begun to reshape every stage of drug discovery[2].Particularly,by integrating diverse,high-dimensional datasets with powerful predictive and generative models.展开更多
Non-peptide macrocyclic drugs possess unique structural advantages that allow them to target various biomolecules of interest and thus show therapeutic potential against various diseases such as cancer,infectious dise...Non-peptide macrocyclic drugs possess unique structural advantages that allow them to target various biomolecules of interest and thus show therapeutic potential against various diseases such as cancer,infectious diseases,etc.This review article examines 34 non-peptide macrocyclic drugs approved between 2000 and 2024,with a particular focus on the optimization process of representative macrocyclic drugs such as natural macrocycles,natural product-inspired macrocycles,and de novo-designed macrocycles.We discuss their structural characteristics,highlighting how conformational rigidity and enhanced target specificity contribute to their efficacy.Design details of these new macrocyclic drugs are illustrated through successful examples,offering insights for optimizing macrocycles.Of note,macrocyclization of U-shaped lead structures represents a novel molecular skeleton editing strategy in de novo macrocycle drug design.展开更多
Cancer immunotherapy,which harnesses the patient's own immune system to target malignant cells,has shown remarkable promise in reducing tumor burden and extending survival.However,the complex tumor microenvironmen...Cancer immunotherapy,which harnesses the patient's own immune system to target malignant cells,has shown remarkable promise in reducing tumor burden and extending survival.However,the complex tumor microenvironment(TME)limits therapeutic benefits to a subset of patients,making it challenging to develop accurate in vitro models for drug response prediction,drug discovery,and personalized medicine.Organoids,three-dimensional(3D)“mini-organs”derived from individual patients that faithfully recapitulate the structural,molecular,and gene expression profiles of primary tumors along with their complex TME in vitro,have emerged as powerful tools for patient-specific drug screening and therapeutic strategy development.Their versatility has led to widespread adoption across both clinical and basic cancer research.However,a key limitation of traditional organoid models is their lack of immune system components.Recent years have seen significant efforts to address this challenge through the integration of immune cells with organoids,aiming to create more physiologically relevant models.This review describes 3D culture methods for immunocompetent organoids,explores organoid–immune cell interactions,and discusses their applications in cancer immunotherapy and drug screening,along with recent advances in related clinical studies.展开更多
To the Editor:Tropomyosin receptor kinase A/B/C(TRKA/B/C)are encoded by neurotrophic tyrosine receptor kinase 1/2/3(NTRK1/2/3),respectively.NTRK gene fusions are the most common drivers of malignancies.Additionally,TR...To the Editor:Tropomyosin receptor kinase A/B/C(TRKA/B/C)are encoded by neurotrophic tyrosine receptor kinase 1/2/3(NTRK1/2/3),respectively.NTRK gene fusions are the most common drivers of malignancies.Additionally,TRKA is the most common oncogene in TRK family,which is detected in 7.4%of human tumors.展开更多
文摘Drug discovery is a complex and highly systematic process encompassing multiple critical stages,including target identification,bioactive molecule discovery,preclinical research,clinical trials,regulatory review,post-marketing surveillance,and others[1].This process typically spans many years and is often accompanied by high failure rates and substantial resource consumption.In recent years,driven by large amounts of biomedical data,artificial intelligence(AI)has begun to reshape every stage of drug discovery[2].Particularly,by integrating diverse,high-dimensional datasets with powerful predictive and generative models.
基金supported by the Noncommunicable Chronic Diseases-National Science and Technology Major Project(No.2023ZD0507700,China)National Natural Science Foundation of China(No.22277110 and 82473761)+2 种基金Joint Research Fund of Science and Technology R&D Plan of Henan Province(No.222301420068,China)Natural Science Foundation of Henan Province(No.242301420005 and 252300421243,China)Key Research Project for Basic Research in Henan Province Universities(No.25ZX001,China).
文摘Non-peptide macrocyclic drugs possess unique structural advantages that allow them to target various biomolecules of interest and thus show therapeutic potential against various diseases such as cancer,infectious diseases,etc.This review article examines 34 non-peptide macrocyclic drugs approved between 2000 and 2024,with a particular focus on the optimization process of representative macrocyclic drugs such as natural macrocycles,natural product-inspired macrocycles,and de novo-designed macrocycles.We discuss their structural characteristics,highlighting how conformational rigidity and enhanced target specificity contribute to their efficacy.Design details of these new macrocyclic drugs are illustrated through successful examples,offering insights for optimizing macrocycles.Of note,macrocyclization of U-shaped lead structures represents a novel molecular skeleton editing strategy in de novo macrocycle drug design.
基金supported by the National Natural Science Foundation of China(82472818 and 82273202)the Fundamental Research Funds for the Central Universities(2042024kf0021 and 2042022dx0003,China)+1 种基金National Key Research and Development Program 2022YFC2504200Interdisciplinary innovative foundation of Wuhan University XNJC202303.
文摘Cancer immunotherapy,which harnesses the patient's own immune system to target malignant cells,has shown remarkable promise in reducing tumor burden and extending survival.However,the complex tumor microenvironment(TME)limits therapeutic benefits to a subset of patients,making it challenging to develop accurate in vitro models for drug response prediction,drug discovery,and personalized medicine.Organoids,three-dimensional(3D)“mini-organs”derived from individual patients that faithfully recapitulate the structural,molecular,and gene expression profiles of primary tumors along with their complex TME in vitro,have emerged as powerful tools for patient-specific drug screening and therapeutic strategy development.Their versatility has led to widespread adoption across both clinical and basic cancer research.However,a key limitation of traditional organoid models is their lack of immune system components.Recent years have seen significant efforts to address this challenge through the integration of immune cells with organoids,aiming to create more physiologically relevant models.This review describes 3D culture methods for immunocompetent organoids,explores organoid–immune cell interactions,and discusses their applications in cancer immunotherapy and drug screening,along with recent advances in related clinical studies.
基金supported by the National Natural Science Foundation of China (Grants 81922064, 22177083, 82273770)Natural Science Foundation of Sichuan Province (Grant 2022NSFSC1290, China)the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (Grant 2020-JKCS-014, China)
文摘To the Editor:Tropomyosin receptor kinase A/B/C(TRKA/B/C)are encoded by neurotrophic tyrosine receptor kinase 1/2/3(NTRK1/2/3),respectively.NTRK gene fusions are the most common drivers of malignancies.Additionally,TRKA is the most common oncogene in TRK family,which is detected in 7.4%of human tumors.
