换一批Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches.
第一作者：
Liying,Zhang
第一单位：
Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.
作者：
关键词
17β-estradiolADADMETARAUCAhRDockingE(2)EDCsEDKBEDSPEFEPAEREndocrine disrupting chemicalsEstrogen receptorMTLMulti-task learningPDBProtein Data BankQSARQuantitative structure–activity relationships modelingRBAROCRPSESPSTLUS Environmental Protection AgencyVirtual screeningabsorption, distribution, metabolism, excretion, and toxicityandrogen receptorapplicability domainarea under the curvearyl hydrocarbon receptorendocrine disrupting chemicalsendocrine disruptor knowledge baseendocrine disruptor screening programenrichment factorestrogen receptork-nearest neighborskNNmulti-task learningquantitative structure–activity relationshipsreceiver operating characteristicrelative binding affinityrelative potencysensitivitysingle-task learningspecificity
医学主题词
算法(Algorithms);人工智能(Artificial Intelligence);计算机模拟(Computer Simulation);内分泌干扰物(Endocrine Disruptors);雌激素拮抗剂(Estrogen Antagonists);雌激素受体α(Estrogen Receptor alpha);雌激素受体β(Estrogen Receptor beta);高通量筛选分析(High-Throughput Screening Assays);人类(Humans);量化构效关系(Quantitative Structure-Activity Relationship);受体, 雌激素(Receptors, Estrogen);构效关系(Structure-Activity Relationship);用户计算机接口(User-Computer Interface)
DOI
10.1016/j.taap.2013.04.032
PMID
23707773
发布时间
2024-06-10
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