{2-[(9R)-9-(pyridin-2-yl)-6-oxaspiro[4.5]decan-9-yl]ethyl}(thiophen-2-ylmethyl)amine | 1401027-29-9

• 分子结构分类: 有机化合物 - 有机杂环化合物 - 吡啶及其衍生物
• 英文名称: {2-[(9R)-9-(pyridin-2-yl)-6-oxaspiro[4.5]decan-9-yl]ethyl}(thiophen-2-ylmethyl)amine
• 英文别名: 2-[(9R)-9-pyridin-2-yl-6-oxaspiro[4.5]decan-9-yl]-N-(thiophen-2-ylmethyl)ethanamine
• CAS: 1401027-29-9
• 化学式: C₂₁H₂₈N₂OS
• 分子量: 356.532
• InChiKey: PJLIHYXPEOMIMJ-HXUWFJFHSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  3.5
• 重原子数：
  25
• 可旋转键数：
  6
• 环数：
  4.0
• sp3杂化的碳原子比例：
  0.57
• 拓扑面积：
  62.4
• 氢给体数：
  1
• 氢受体数：
  4

文献信息

• Methods of treating hyperalgesia
  申请人：Trevena, Inc.

  公开号：US10588889B2

  公开（公告）日：2020-03-17

  This application describes compounds and methods that can be used to treat, reverse, or avoid hyperalgesia.

  本申请介绍了可用于治疗、逆转或避免痛觉减退的化合物和方法。
• OPIOID RECEPTOR LIGANDS AND METHODS OF USING AND MAKING SAME
  申请人：Trevena, Inc.

  公开号：EP2688403B1

  公开（公告）日：2017-05-31
• SYSTEMS AND METHODS FOR PREDICTING CARDIOTOXICITY OF MOLECULAR PARAMETERS OF A COMPOUND BASED ON MACHINE LEARNING ALGORITHMS
  申请人：UTI Limited Partnership

  公开号：US20180172667A1

  公开（公告）日：2018-06-21

  Systems and methods are provided for predicting cardiotoxicity of molecular parameters of a compound. A computer can provide as input to a machine learning algorithm the molecular parameters of the compound. The molecular parameters can include at least structural information about the compound. The machine learning algorithm can have been trained using respective molecular parameters of compounds known to have cardiotoxicity and of compounds known not to have cardiotoxicity. The computer can receive as output from the machine learning algorithm a representation of the predicted cardiotoxicity of each molecular parameter of at least a subset of the molecular parameters of the compound.
• DEUTERATED COMPOUNDS FOR TREATING PAIN AND RELATED DISEASES AND CONDITIONS, AND COMPOSITIONS AND METHODS THEREOF
  申请人：NeuForm Pharmaceuticals, Inc.

  公开号：US20200330444A1

  公开（公告）日：2020-10-22

  The invention provides novel chemical compounds useful for treating pain or a related disease or disorder thereof, and pharmaceutical composition and methods of preparation and use thereof.
• [EN] SYSTEMS AND METHODS FOR PREDICTING CARDIOTOXICITY OF MOLECULAR PARAMETERS OF A COMPOUND BASED ON MACHINE LEARNING ALGORITHMS<br/>[FR] SYSTÈMES ET PROCÉDÉS PERMETTANT DE PRÉDIRE LA CARDIOTOXICITÉ DE PARAMÈTRES MOLÉCULAIRES D'UN COMPOSÉ SUR LA BASE D'ALGORITHMES D'APPRENTISSAGE MACHINE
  申请人：UTI LIMITED PARTNERSHIP

  公开号：WO2016201575A1

  公开（公告）日：2016-12-22

  Systems and methods are provided for predicting cardiotoxicity of molecular parameters of a compound. A computer can provide as input to a machine learning algorithm the molecular parameters of the compound. The molecular parameters can include at least structural information about the compound. The machine learning algorithm can have been trained using respective molecular parameters of compounds known to have cardiotoxicity and of compounds known not to have cardiotoxicity. The computer can receive as output from the machine learning algorithm a representation of the predicted cardiotoxicity of each molecular parameter of at least a subset of the molecular parameters of the compound.