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基于色谱和化学计量学方法对伊沙匹隆衍生物的物理化学性质进行评估

Evaluation of Physicochemical Properties of Ipsapirone Derivatives Based on Chromatographic and Chemometric Approaches.

作者信息

Nisterenko Wiktor, Kułaga Damian, Woziński Mateusz, Singh Yash Raj, Judzińska Beata, Jagiello Karolina, Greber Katarzyna Ewa, Sawicki Wiesław, Ciura Krzesimir

机构信息

Department of Physical Chemistry, Faculty of Pharmacy, Medical University of Gdańsk, Aleja Generała Józefa Hallera 107, 80-416 Gdańsk, Poland.

Department of Organic Chemistry and Technology, Faculty of Chemical Engineering and Technology, Cracow University of Technology, 24 Warszawska Street, 31-155 Cracow, Poland.

出版信息

Molecules. 2024 Apr 19;29(8):1862. doi: 10.3390/molecules29081862.

Abstract

Drug discovery is a challenging process, with many compounds failing to progress due to unmet pharmacokinetic criteria. Lipophilicity is an important physicochemical parameter that affects various pharmacokinetic processes, including absorption, metabolism, and excretion. This study evaluated the lipophilic properties of a library of ipsapirone derivatives that were previously synthesized to affect dopamine and serotonin receptors. Lipophilicity indices were determined using computational and chromatographic approaches. In addition, the affinity to human serum albumin (HSA) and phospholipids was assessed using biomimetic chromatography protocols. Quantitative Structure-Retention Relationship (QSRR) methodologies were used to determine the impact of theoretical descriptors on experimentally determined properties. A multiple linear regression (MLR) model was calculated to identify the most important features, and genetic algorithms (GAs) were used to assist in the selection of features. The resultant models showed commendable predictive accuracy, minimal error, and good concordance correlation coefficient values of 0.876, 0.149, and 0.930 for the validation group, respectively.

摘要

药物发现是一个具有挑战性的过程,许多化合物由于未满足的药代动力学标准而未能取得进展。亲脂性是一个重要的物理化学参数,它影响各种药代动力学过程,包括吸收、代谢和排泄。本研究评估了一组先前合成的用于影响多巴胺和5-羟色胺受体的ipsapirone衍生物的亲脂性。使用计算和色谱方法确定亲脂性指数。此外,使用仿生色谱方案评估对人血清白蛋白(HSA)和磷脂的亲和力。采用定量结构-保留关系(QSRR)方法来确定理论描述符对实验测定性质的影响。计算了多元线性回归(MLR)模型以识别最重要的特征,并使用遗传算法(GA)来协助特征选择。所得模型显示出可称赞的预测准确性、最小误差,验证组的良好一致性相关系数值分别为0.876、0.149和0.930。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3962/11054528/80befb899fe1/molecules-29-01862-g001.jpg

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