通过基于自值的拓指数和非线性回归技术,预测β-乳糖抗生素物理化学性质的建模
A Yuvaraj1, G Kalaimurugan1, R Thamizhmaran1
1Department of Mathematics, Thiruvalluvar University, Vellore, 632 115, Tamil Nadu, India.
Scientific reports
|February 17, 2026
概括
用光谱图描述器对β-乳糖抗生素进行了定量结构-性质关系 (QSPR) 分析. 这些描述符有效地预测了与分子大小和连接性相关的属性,帮助QSPR建模.
科学领域:
- 药用化学 医学化学
- 计算化学计算化学
- 化学信息学 化学信息学
背景情况:
- 贝塔乳酸抗生素是关键的药品.
- 了解它们的物理化学特性对于药物设计至关重要.
- 定量结构与属性关系 (QSPR) 研究提供了预测性见解.
研究的目的:
- 在beta-lactam抗生素上进行QSPR分析.
- 调查光谱图描述器在预测物理化学性质方面的实用性.
- 建立分子拓和药物特性之间的相关性.
主要方法:
- 分子结构以图形表示.
- 从图形矩阵 (邻近,拉普拉斯,无符号的拉普拉斯,距离) 衍生出的基于自身价值的光谱描述符.
- 非线性回归模型 (二次数,对数,功率) 应用于与属性相关的描述符 (沸点,摩尔体积等). ) 的情况.
主要成果:
- 频谱描述符显示了与受分子大小和连接性影响的属性的显著相关性.
- 二次回归模型通常产生更好的预测性能 (较高的R平方,较低的误差).
- 对于电子或表面效应主导的属性,观察到的相关性较弱,这表明纯粹拓描述符的局限性.
结论:
- 谱图描述器是适用和可解释的工具,用于beta-lactam抗生素的QSPR建模.
- 该研究为未来的QSPR研究提供了基础,使用更大的数据集和多种描述符类型.
- 这种方法有助于理解抗生素药物发现的结构属性关系.
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