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  1. 首页
  2. 研究领域
  3. 生物医学和临床科学
  4. 药理学和制药科学
  5. 药物基因组学
  6. 从结构到策略:用于预测药物的终端半衰期的化学建模及其在未来治疗中的作用
  1. 首页
  2. 研究领域
  3. 生物医学和临床科学
  4. 药理学和制药科学
  5. 药物基因组学
  6. 从结构到策略:用于预测药物的终端半衰期的化学建模及其在未来治疗中的作用

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从结构到策略:用于预测药物的终端半衰期的化学建模及其在未来治疗中的作用

Pabitra Samanta1, Shubha Das1, Dipika Mandal2

  • 1Drug Discovery and Development Laboratory (DDD Lab), Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700032, India.

Molecular diversity
|August 21, 2025

在PubMed 上查看摘要

概括
此摘要是机器生成的。

这项研究开发了一种定量读透结构-活性关系 (q-RASAR) 模型,以预测药物终端半衰期,改善药物开发. 该模型确定了影响药物持续时间的结构特征,有助于制造更安全,更有效的药物.

科学领域:

  • 药理动力学和药物代谢
  • 计算化学
  • 医学化学

背景情况:

  • 终端半衰期 (t1⁄2) 对药物的剂量和疗效至关重要,但从化学结构来预测它是具有挑战性的.
  • 现有的与药物动力学参数相关的化学结构方法往往耗时且昂贵.
  • 根据分子性质需要有效可靠的方法来估计药物的终端半衰期.

研究的目的:

  • 为预测各种药物的终端半衰期,开发一个定量读透结构-活性关系 (q-RASAR) 模型.
  • 为了提高预测能力,将阅读原则与定量结构-活动关系 (QSAR) 方法相结合.
  • 确定特定的化学子结构和特性,积极或消极地影响药物的终端半衰期.

主要方法:

  • 用895种药物的数据集进行描述器计算和模型构建.
  • 为了生成模型,采用了结合式q-RASAR方法,合并阅读和QSAR.
  • 基于部分最小平方 (PLS) 的q-RASAR模型被开发并根据经合组织原则严格验证.

主要成果:

  • 与标准QSAR模型相比,开发的q-RASAR模型显示出更高的统计意义,可靠性和稳定性.
  • 具有较长终端半衰期的关键结构特征包括RA功能和六条环.
  • 影响终端半衰期的特征包括//碳酸组,正电荷,可溶性和平均分子量.
关键词:
医药产品在QSAR终端半衰期q-RASAR 的使用

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结论:

  • q-RASAR模型为预测药物终端半衰期提供了有效的工具,促进了药物开发.
  • 该模型的预测用于选DrugBank数据库,有助于估计新药的剂量频率和积累概况.
  • 这种方法支持制定和优化更安全,更环保的制药剂.