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.

中文翻译：

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基于色谱和化学计量方法评价伊沙匹隆衍生物的理化性质

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药代动力学标准而未能取得进展。亲脂性是一个重要的理化参数，影响各种药代动力学过程，包括吸收、代谢和排泄。这项研究评估了先前合成的影响多巴胺和血清素受体的伊沙匹隆衍生物库的亲脂特性。使用计算和色谱方法测定亲脂性指数。此外，使用仿生层析方案评估了与人血清白蛋白（HSA）和磷脂的亲和力。定量结构-保留关系（QSRR）方法用于确定理论描述符对实验确定的特性的影响。计算多元线性回归（MLR）模型来识别最重要的特征，并使用遗传算法（GA）来协助选择特征。由此产生的模型显示出值得称赞的预测准确性、最小误差以及验证组良好的一致性相关系数值，分别为 0.876、0.149 和 0.930。