1-(5-bromo-1-methyl-1H-pyrazol-3-yl)-3-(4-((4-methylpiperazin-1-yl)methyl)-3-(trifluoromethyl)phenyl)urea | 1428445-61-7

• 分子结构分类: 有机化合物 - 苯类化合物 - 苯和取代衍生物
• 英文名称: 1-(5-bromo-1-methyl-1H-pyrazol-3-yl)-3-(4-((4-methylpiperazin-1-yl)methyl)-3-(trifluoromethyl)phenyl)urea
• 英文别名: 1-(1-Methyl-5-bromo-1H-pyrazole-3-yl)-3-[3-(trifluoromethyl)-4-[(4-methylpiperazino)methyl]phenyl]urea；1-(5-bromo-1-methylpyrazol-3-yl)-3-[4-[(4-methylpiperazin-1-yl)methyl]-3-(trifluoromethyl)phenyl]urea
• CAS: 1428445-61-7
• 化学式: C₁₈H₂₂BrF₃N₆O
• 分子量: 475.311
• InChiKey: QYEXWTAGWHCLMI-UHFFFAOYSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  2.7
• 重原子数：
  29
• 可旋转键数：
  4
• 环数：
  3.0
• sp3杂化的碳原子比例：
  0.44
• 拓扑面积：
  65.4
• 氢给体数：
  2
• 氢受体数：
  7

反应信息

• 作为反应物：
  描述：

  1-(5-bromo-1-methyl-1H-pyrazol-3-yl)-3-(4-((4-methylpiperazin-1-yl)methyl)-3-(trifluoromethyl)phenyl)urea 、 tert-butyl ((1r,4r)-4-((8-ethyl-6-(4,4,5,5-tetramethyl-1,3,2-dioxaborolan-2-yl)quinazolin-2-yl)amino)cyclohexyl)carbamate 在 (1,1'-bis(diphenylphosphino)ferrocene)palladium(II) dichloride 、 potassium carbonate 、 三氟乙酸 作用下， 以 1,4-二氧六环 、 二氯甲烷 、 水 为溶剂， 反应 12.17h， 生成 1-(5-(2-(((1r,4r)-4-aminocyclohexyl)amino)-8-ethylquinazolin-6-yl)-1-methyl-1H-pyrazol-3-yl)-3-(4-((4-methylpiperazin-1-yl)methyl)-3-(trifluoromethyl)phenyl)urea
  参考文献：
  名称：

  [EN] IRE1 SMALL MOLECULE INHIBITORS
  [FR] INHIBITEURS DE PETITES MOLÉCULES IRE1

  摘要：

  本文提供了针对IRE1蛋白家族成员的小分子抑制剂。结合可以是直接的或间接的。此外，本文提供了使用IRE1小分子抑制剂用于治疗或改善受试者癌症的方法。此外，本文描述的IRE1小分子抑制剂用于治疗癌症，其中癌症是实体或血液系统的癌症。

  公开号：

  WO2018102751A1
• 作为产物：
  描述：

  N-甲基哌嗪 在 raney nickel (catcart) 作用下， 以 甲醇 、 二氯甲烷 、 二甲基亚砜 为溶剂， 反应 2.5h， 生成 1-(5-bromo-1-methyl-1H-pyrazol-3-yl)-3-(4-((4-methylpiperazin-1-yl)methyl)-3-(trifluoromethyl)phenyl)urea
  参考文献：
  名称：

  Rapid Discovery of a Novel Series of Abl Kinase Inhibitors by Application of an Integrated Microfluidic Synthesis and Screening Platform

  摘要：

  Drug discovery faces economic and scientific imperatives to deliver lead molecules rapidly and efficiently. Using traditional paradigms the molecular design, synthesis, and screening loops enforce a significant time delay leading to inefficient use of data in the iterative molecular design process. Here, we report the application of a flow technology platform integrating the key elements of structure activity relationship (SAR) generation to the discovery of novel Abl kinase inhibitors. The platform utilizes flow chemistry for rapid in-line synthesis, automated purification, and analysis coupled with bioassay. The combination of activity prediction using Random-Forest regression with chemical space sampling algorithms allows the construction of an activity model that refines itself after every iteration of synthesis and biological result. Within just 21 compounds, the automated process identified a novel template and hinge binding motif with pIC(50) > 8 against Abl kinase - both wild type and clinically relevant mutants. Integrated microfluidic synthesis and screening coupled with machine learning design have the potential to greatly reduce the time and cost of drug discovery within the hit-to-lead and lead optimization phases.

  DOI：

  10.1021/jm400099d

文献信息

• IRE1 small molecule inhibitors
  申请人：Cornell University

  公开号：US10934275B2

  公开（公告）日：2021-03-02

  Provided herein are small molecule inhibitors for the targeting or IRE1 protein family members. Binding may be direct or indirect. Further provided herein are methods of using IRE1 small molecule inhibitors for use in treating or ameliorating cancer in a subject. Moreover, IRE1 small molecule inhibitors described herein are for the treatment of cancer, where the cancer is a solid or hematologic cancer.

  本文提供的是用于靶向或 IRE1 蛋白家族成员的小分子抑制剂。结合可以是直接的或间接的。本文还提供了使用 IRE1 小分子抑制剂治疗或改善受试者癌症的方法。此外，本文所述的IRE1小分子抑制剂用于治疗癌症，其中癌症是实体癌或血液癌。
• IRE1 SMALL MOLECULE INHIBITORS
  申请人：Quentis Therapeutics, Inc.

  公开号：EP3548476A1

  公开（公告）日：2019-10-09
• IRE1 Small Molecule Inhibitors
  申请人：Quentis Therapeutics, Inc.

  公开号：US20190276434A1

  公开（公告）日：2019-09-12

  Provided herein are small molecule inhibitors for the targeting or IRE1 protein family members. Binding may be direct or indirect. Further provided herein are methods of using IRE1 small molecule inhibitors for use in treating or ameliorating cancer in a subject. Moreover, IRE1 small molecule inhibitors described herein are for the treatment of cancer, where the cancer is a solid or hematologic cancer.
• [EN] IRE1 SMALL MOLECULE INHIBITORS<br/>[FR] INHIBITEURS DE PETITES MOLÉCULES IRE1
  申请人：QUENTIS THERAPEUTICS INC

  公开号：WO2018102751A1

  公开（公告）日：2018-06-07

  Provided herein are small molecule inhibitors for the targeting or IRE1 protein family members. Binding may be direct or indirect. Further provided herein are methods of using IRE1 small molecule inhibitors for use in treating or ameliorating cancer in a subject. Moreover, IRE1 small molecule inhibitors described herein are for the treatment of cancer, where the cancer is a solid or hematologic cancer.

  本文提供了针对IRE1蛋白家族成员的小分子抑制剂。结合可以是直接的或间接的。此外，本文提供了使用IRE1小分子抑制剂用于治疗或改善受试者癌症的方法。此外，本文描述的IRE1小分子抑制剂用于治疗癌症，其中癌症是实体或血液系统的癌症。
• Rapid Discovery of a Novel Series of Abl Kinase Inhibitors by Application of an Integrated Microfluidic Synthesis and Screening Platform
  作者：Bimbisar Desai、Karen Dixon、Elizabeth Farrant、Qixing Feng、Karl R. Gibson、Willem P. van Hoorn、James Mills、Trevor Morgan、David M. Parry、Manoj K. Ramjee、Christopher N. Selway、Gary J. Tarver、Gavin Whitlock、Adrian G. Wright

  DOI：10.1021/jm400099d

  日期：2013.4.11

  Drug discovery faces economic and scientific imperatives to deliver lead molecules rapidly and efficiently. Using traditional paradigms the molecular design, synthesis, and screening loops enforce a significant time delay leading to inefficient use of data in the iterative molecular design process. Here, we report the application of a flow technology platform integrating the key elements of structure activity relationship (SAR) generation to the discovery of novel Abl kinase inhibitors. The platform utilizes flow chemistry for rapid in-line synthesis, automated purification, and analysis coupled with bioassay. The combination of activity prediction using Random-Forest regression with chemical space sampling algorithms allows the construction of an activity model that refines itself after every iteration of synthesis and biological result. Within just 21 compounds, the automated process identified a novel template and hinge binding motif with pIC(50) > 8 against Abl kinase - both wild type and clinically relevant mutants. Integrated microfluidic synthesis and screening coupled with machine learning design have the potential to greatly reduce the time and cost of drug discovery within the hit-to-lead and lead optimization phases.