Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Ave. Eugenio Garza Sada 2501, Monterrey 64849, Mexico.
Departamento de Ciencias Básicas, División de CBI (Ciencias Básicas e Ingeniería), Universidad Autónoma Metropolitana, Unidad Azcapotzalco, Área de Física Atómica Molecular Aplicada, San Pablo 180, Ciudad de México 02200, Mexico.
Int J Mol Sci. 2022 May 3;23(9):5086. doi: 10.3390/ijms23095086.
A study of 250 commercial drugs to act as corrosion inhibitors on steel has been developed by applying the quantitative structure-activity relationship (QSAR) paradigm. Hard-soft acid-base (HSAB) descriptors were used to establish a mathematical model to predict the corrosion inhibition efficiency (IE%) of several commercial drugs on steel surfaces. These descriptors were calculated through third-order density-functional tight binding (DFTB) methods. The mathematical modeling was carried out through autoregressive with exogenous inputs (ARX) framework and tested by fivefold cross-validation. Another set of drugs was used as an external validation, obtaining SD, RMSE, and MSE, obtaining 6.76%, 3.89%, 7.03%, and 49.47%, respectively. With a predicted value of IE% = 87.51%, lidocaine was selected to perform a final comparison with experimental results. By the first time, this drug obtained a maximum IE%, determined experimentally by electrochemical impedance spectroscopy measurements at 100 ppm concentration, of about 92.5%, which stands within limits of 1 SD from the predicted ARX model value. From the qualitative perspective, several potential trends have emerged from the estimated values. Among them, macrolides, alkaloids from species, cephalosporin, and rifamycin antibiotics are expected to exhibit high IE% on steel surfaces. Additionally, IE% increases as the energy of HOMO decreases. The highest efficiency is obtained in case of the molecules with the highest and Δ values. The most efficient drugs are found with p ranging from 1.70 to 9.46. The drugs recurrently exhibit aromatic rings, carbonyl, and hydroxyl groups with the highest IE% values.
采用定量结构-活性关系（QSAR）范式，对 250 种商业药物进行了研究，以作为钢的缓蚀剂。硬软酸碱（HSAB）描述符用于建立数学模型，以预测几种商业药物在钢表面的腐蚀抑制效率（IE%）。这些描述符是通过第三阶密度泛函紧束缚（DFTB）方法计算得出的。数学建模是通过自回归与外部输入（ARX）框架进行的，并通过五重交叉验证进行了测试。另一组药物被用作外部验证，得到 SD、RMSE 和 MSE，分别为 6.76%、3.89%、7.03%和 49.47%。IE%预测值为 87.51%，选择利多卡因进行最终实验结果比较。该药物首次获得了 100ppm 浓度下电化学阻抗谱测量实验确定的最大 IE%，约为 92.5%，与预测 ARX 模型值相差 1 SD 以内。从定性角度来看，从估计值中出现了几个潜在趋势。其中，大环内酯类、来自 种的生物碱、头孢菌素和利福霉素类抗生素有望在钢表面表现出高 IE%。此外，随着 HOMO 能量的降低，IE%增加。在 值和Δ值最高的情况下，效率最高。具有 1.70 至 9.46 范围内 p 值的药物具有最高的 IE%。具有最高 IE%值的药物反复出现芳香环、羰基和羟基。
