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2-[4-(3-Piperidin-1-ylpropoxy)phenyl]-4,5-dihydro-1,3-oxazole | 1334335-21-5

中文名称
——
中文别名
——
英文名称
2-[4-(3-Piperidin-1-ylpropoxy)phenyl]-4,5-dihydro-1,3-oxazole
英文别名
——
2-[4-(3-Piperidin-1-ylpropoxy)phenyl]-4,5-dihydro-1,3-oxazole化学式
CAS
1334335-21-5
化学式
C17H24N2O2
mdl
——
分子量
288.39
InChiKey
HZEJDUONRSVLKB-UHFFFAOYSA-N
BEILSTEIN
——
EINECS
——
  • 物化性质
  • 计算性质
  • ADMET
  • 安全信息
  • SDS
  • 制备方法与用途
  • 上下游信息
  • 反应信息
  • 文献信息
  • 表征谱图
  • 同类化合物
  • 相关功能分类
  • 相关结构分类

计算性质

  • 辛醇/水分配系数(LogP):
    2.7
  • 重原子数:
    21
  • 可旋转键数:
    6
  • 环数:
    3.0
  • sp3杂化的碳原子比例:
    0.59
  • 拓扑面积:
    34.1
  • 氢给体数:
    0
  • 氢受体数:
    4

上下游信息

  • 上游原料
    中文名称 英文名称 CAS号 化学式 分子量

反应信息

  • 作为产物:
    参考文献:
    名称:
    Novel and highly potent histamine H3 receptor ligands. Part 1: withdrawing of hERG activity
    摘要:
    Pre-clinical investigation of some aryl-piperidinyl ether histamine H3 receptor antagonists revealed a strong hERG binding. To overcome this issue, we have developed a QSAR model specially dedicated to H3 receptor ligands. This model was designed to be directly applicable in medicinal chemistry with no need of molecular modeling. The resulting recursive partitioning trees are robust (80-85% accuracy), but also simple and comprehensible. A novel promising lead emerged from our work and the structure-activity relationships are presented. (C) 2011 Elsevier Ltd. All rights reserved.
    DOI:
    10.1016/j.bmcl.2011.07.006
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文献信息

  • Novel and highly potent histamine H3 receptor ligands. Part 1: withdrawing of hERG activity
    作者:Nicolas Levoin、Olivier Labeeuw、Thierry Calmels、Olivia Poupardin-Olivier、Isabelle Berrebi-Bertrand、Jeanne-Marie Lecomte、Jean-Charles Schwartz、Marc Capet
    DOI:10.1016/j.bmcl.2011.07.006
    日期:2011.9
    Pre-clinical investigation of some aryl-piperidinyl ether histamine H3 receptor antagonists revealed a strong hERG binding. To overcome this issue, we have developed a QSAR model specially dedicated to H3 receptor ligands. This model was designed to be directly applicable in medicinal chemistry with no need of molecular modeling. The resulting recursive partitioning trees are robust (80-85% accuracy), but also simple and comprehensible. A novel promising lead emerged from our work and the structure-activity relationships are presented. (C) 2011 Elsevier Ltd. All rights reserved.
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