The interaction of 14 anti-inflammatory drugs with human serum albumin (HSA) was investigated using fluorescence quenching, molecular docking studies, and quantitative structure-activity relationship (QSAR) methodology. Binding of anti-inflammatory drugs to HSA plays a fundamental role in their transport, distribution, delivery, and elimination. Binding constants of these drugs to HSA, obtained using the fluorescence quenching method, were within the range 0.01 × 104 M-1 (acetaminophen) to 1881.05 × 104 M-1 (meloxicam). Binding sites and binding constants of these anti-inflammatory drugs were estimated using molecular docking. Inspection of the obtained values for docking score, logKb and Kb , showed that the drugs in this data set have a relatively strong binding constant for HSA. QSAR modelling was applied for binding constants obtained from fluorescence quenching and theoretical molecular descriptors. This modelling led to a linear two-parameter model with a correlation coefficient of 0.95 and adequate robustness. The descriptor results showed the importance of a bonding network and electronegativity as the discriminative structural factors in binding affinity for the HSA molecule.

中文翻译：

---

使用分子对接，定量构效关系和荧光光谱研究抗炎药与人血清白蛋白的相互作用。

使用荧光猝灭，分子对接研究和定量构效关系（QSAR）方法研究了14种抗炎药与人血清白蛋白（HSA）的相互作用。抗炎药与HSA的结合在其运输，分配，递送和消除中起着基本作用。使用荧光猝灭法获得的这些药物与HSA的结合常数在0.01×104 M-1（对乙酰氨基酚）至1881.05×104 M-1（美洛昔康）之间。这些抗炎药的结合位点和结合常数是通过分子对接估算的。对获得的对接得分值logKb和Kb的检查表明，该数据集中的药物具有与HSA相对较强的结合常数。将QSAR建模应用于从荧光猝灭和理论分子描述符获得的结合常数。这种建模导致了线性两参数模型，其相关系数为0.95，并且具有足够的鲁棒性。描述符结果表明，键合网络和电负性作为区分HSA分子亲和力的区分性结构因素的重要性。