zinc;6-[[(6R,7R)-3-(acetyloxymethyl)-2-carboxy-8-oxo-5-thia-1-azabicyclo[4.2.0]oct-2-en-7-yl]imino]-2-amino-6-oxidohexanoate

• 分子结构分类: 有机化合物 - 有机杂环化合物 - 内酰胺类
• 英文名称: zinc;6-[[(6R,7R)-3-(acetyloxymethyl)-2-carboxy-8-oxo-5-thia-1-azabicyclo[4.2.0]oct-2-en-7-yl]imino]-2-amino-6-oxidohexanoate
• 化学式: C16H19N3O8SZn
• 分子量: 478.8
• InChiKey: TVMXJQZBKOMFQK-BJIHTTGYSA-L

计算性质

• 辛醇/水分配系数(LogP)：
  -3.8
• 重原子数：
  29
• 可旋转键数：
  8
• 环数：
  2.0
• sp3杂化的碳原子比例：
  0.56
• 拓扑面积：
  207
• 氢给体数：
  2
• 氢受体数：
  10

文献信息

• HIGH-THROUGHPUT IMAGING-BASED METHODS FOR PREDICTING CELL-TYPE-SPECIFIC TOXICITY OF XENOBIOTICS WITH DIVERSE CHEMICAL STRUCTURES
  申请人：Agency for Science, Technology and Research

  公开号：EP3377896A1

  公开（公告）日：2018-09-26
• US7790905B2
  申请人：——

  公开号：US7790905B2

  公开（公告）日：2010-09-07
• US7927613B2
  申请人：——

  公开号：US7927613B2

  公开（公告）日：2011-04-19
• [EN] HIGH-THROUGHPUT IMAGING-BASED METHODS FOR PREDICTING CELL-TYPE-SPECIFIC TOXICITY OF XENOBIOTICS WITH DIVERSE CHEMICAL STRUCTURES<br/>[FR] PROCÉDÉS BASÉS SUR UNE IMAGERIE À HAUT DÉBIT PERMETTANT DE PRÉDIRE LA TOXICITÉ SPÉCIFIQUE À UN TYPE DE CELLULE DE XÉNOBIOTIQUES AYANT DIVERSES STRUCTURES CHIMIQUES
  申请人：AGENCY SCIENCE TECH & RES

  公开号：WO2017091147A1

  公开（公告）日：2017-06-01

  The present invention provides methods for the prediction of in vivo cell-specific toxicity of a compound that combines high-throughput imaging of cultured cells, quantitative phenotypic profiling, and machine learning methods. More particularly, the invention provides a method for the prediction of in vivo renal proximal tubular-, bronchial-epithelial-, and alveolar-cell-specific toxicities of a soluble or particulate compound that comprises contacting cultured human kidney and pulmonary cells with the compound at a range of concentrations, then labelling the cells with DNA, yH2AX and actin markers and obtaining textural features, spatial correlation features, ratios of the markers, intensity features, cell count and morphology, estimating dose response curves and performing automatic classification of the compound using a random-forest algorithm.