cyclohexanesulfonic acid {4-[4-(3-nitrophenyl)piperazin-1-yl]butyl}amide | 896125-10-3

• 分子结构分类: 有机化合物 - 有机杂环化合物 - 二嗪烷类
• 英文名称: cyclohexanesulfonic acid {4-[4-(3-nitrophenyl)piperazin-1-yl]butyl}amide
• 英文别名: N-[4-[4-(3-nitrophenyl)piperazin-1-yl]butyl]cyclohexanesulfonamide
• CAS: 896125-10-3
• 化学式: C₂₀H₃₂N₄O₄S
• 分子量: 424.564
• InChiKey: NCEZCVDMRJOCTR-UHFFFAOYSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  3.3
• 重原子数：
  29
• 可旋转键数：
  8
• 环数：
  3.0
• sp3杂化的碳原子比例：
  0.7
• 拓扑面积：
  107
• 氢给体数：
  1
• 氢受体数：
  7

反应信息

• 作为反应物：
  描述：

  cyclohexanesulfonic acid {4-[4-(3-nitrophenyl)piperazin-1-yl]butyl}amide 在 盐酸 、 tin(ll) chloride 作用下， 以 甲醇 为溶剂， 以75%的产率得到cyclohexanesulfonic acid {4-[4-(3-aminophenyl)piperazin-1-yl]butyl}amide
  参考文献：
  名称：

  An Integrated in Silico 3D Model-Driven Discovery of a Novel, Potent, and Selective Amidosulfonamide 5-HT_1A Agonist (PRX-00023) for the Treatment of Anxiety and Depression

  摘要：

  We report the discovery of a novel, potent, and selective amidosulfonamide nonazapirone 5-HT1A agonist for the treatment of anxiety and depression, which is now in Phase III clinical trials for generalized anxiety disorder (GAD). The discovery of 20m (PRX-00023), N-{3-[4-(4-cyclohexylmethanesulfonylaminobutyl)piperazin-1-yl] phenyl} acetamide, and its backup compounds, followed a new paradigm, driving the entire discovery process with in silico methods and seamlessly integrating computational chemistry with medicinal chemistry, which led to a very rapid discovery timeline. The program reached clinical trials within less than 2 years from initiation, spending less than 6 months in lead optimization with only 31 compounds synthesized. In this paper we detail the entire discovery process, which started with modeling the 3D structure of 5-HT1A using the PREDICT methodology, and then performing in silico screening on that structure leading to the discovery of a 1 nM lead compound (8). The lead compound was optimized following a strategy devised based on in silico 3D models and realized through an in silico-driven optimization process, rapidly overcoming selectivity issues (affinity to 5-HT1A vs alpha(1)-adrenergic receptor) and potential cardiovascular issues (hERG binding), leading to a clinical compound. Finally we report key in vivo preclinical and Phase I clinical data for 20m tolerability, pharmacokinetics, and pharmacodynamics and show that these favorable results are a direct outcome of the properties that were ascribed to the compound during the rational structure-based discovery process. We believe that this is one of the first examples for a Phase III drug candidate that was discovered and optimized, from start to finish, using in silico model-based methods as the primary tool.

  DOI：

  10.1021/jm0508641
• 作为产物：
  描述：

  {4-[4-(3-nitrophenyl)piperazin-1-yl]butyl}carbamic acid tert-butyl ester 在 三乙胺 作用下， 以 二氯甲烷 为溶剂， 反应 2.5h， 生成 cyclohexanesulfonic acid {4-[4-(3-nitrophenyl)piperazin-1-yl]butyl}amide
  参考文献：
  名称：

  An Integrated in Silico 3D Model-Driven Discovery of a Novel, Potent, and Selective Amidosulfonamide 5-HT_1A Agonist (PRX-00023) for the Treatment of Anxiety and Depression

  摘要：

  We report the discovery of a novel, potent, and selective amidosulfonamide nonazapirone 5-HT1A agonist for the treatment of anxiety and depression, which is now in Phase III clinical trials for generalized anxiety disorder (GAD). The discovery of 20m (PRX-00023), N-{3-[4-(4-cyclohexylmethanesulfonylaminobutyl)piperazin-1-yl] phenyl} acetamide, and its backup compounds, followed a new paradigm, driving the entire discovery process with in silico methods and seamlessly integrating computational chemistry with medicinal chemistry, which led to a very rapid discovery timeline. The program reached clinical trials within less than 2 years from initiation, spending less than 6 months in lead optimization with only 31 compounds synthesized. In this paper we detail the entire discovery process, which started with modeling the 3D structure of 5-HT1A using the PREDICT methodology, and then performing in silico screening on that structure leading to the discovery of a 1 nM lead compound (8). The lead compound was optimized following a strategy devised based on in silico 3D models and realized through an in silico-driven optimization process, rapidly overcoming selectivity issues (affinity to 5-HT1A vs alpha(1)-adrenergic receptor) and potential cardiovascular issues (hERG binding), leading to a clinical compound. Finally we report key in vivo preclinical and Phase I clinical data for 20m tolerability, pharmacokinetics, and pharmacodynamics and show that these favorable results are a direct outcome of the properties that were ascribed to the compound during the rational structure-based discovery process. We believe that this is one of the first examples for a Phase III drug candidate that was discovered and optimized, from start to finish, using in silico model-based methods as the primary tool.

  DOI：

  10.1021/jm0508641

文献信息

• An Integrated in Silico 3D Model-Driven Discovery of a Novel, Potent, and Selective Amidosulfonamide 5-HT_1A Agonist (PRX-00023) for the Treatment of Anxiety and Depression
  作者：Oren M. Becker、Dale S. Dhanoa、Yael Marantz、Dongli Chen、Sharon Shacham、Srinivasa Cheruku、Alexander Heifetz、Pradyumna Mohanty、Merav Fichman、Anurag Sharadendu、Raphael Nudelman、Michael Kauffman、Silvia Noiman

  DOI：10.1021/jm0508641

  日期：2006.6.1

  We report the discovery of a novel, potent, and selective amidosulfonamide nonazapirone 5-HT1A agonist for the treatment of anxiety and depression, which is now in Phase III clinical trials for generalized anxiety disorder (GAD). The discovery of 20m (PRX-00023), N-3-[4-(4-cyclohexylmethanesulfonylaminobutyl)piperazin-1-yl] phenyl} acetamide, and its backup compounds, followed a new paradigm, driving the entire discovery process with in silico methods and seamlessly integrating computational chemistry with medicinal chemistry, which led to a very rapid discovery timeline. The program reached clinical trials within less than 2 years from initiation, spending less than 6 months in lead optimization with only 31 compounds synthesized. In this paper we detail the entire discovery process, which started with modeling the 3D structure of 5-HT1A using the PREDICT methodology, and then performing in silico screening on that structure leading to the discovery of a 1 nM lead compound (8). The lead compound was optimized following a strategy devised based on in silico 3D models and realized through an in silico-driven optimization process, rapidly overcoming selectivity issues (affinity to 5-HT1A vs alpha(1)-adrenergic receptor) and potential cardiovascular issues (hERG binding), leading to a clinical compound. Finally we report key in vivo preclinical and Phase I clinical data for 20m tolerability, pharmacokinetics, and pharmacodynamics and show that these favorable results are a direct outcome of the properties that were ascribed to the compound during the rational structure-based discovery process. We believe that this is one of the first examples for a Phase III drug candidate that was discovered and optimized, from start to finish, using in silico model-based methods as the primary tool.