ABSTRACT

Leishmaniasis affects mainly rural areas and the poorest people in the world. A computational study of the antileishmanial activity of organic selenium and tellurium compounds was performed. The 3D structures of the compounds were optimized at the wb97xd/lanl2dz level and used in the quantitative structure-activity relationship (QSAR) analysis. The antileishmanial activity was measured by L. donovani β carbonic anhydrase inhibition (Ki) and the half-maximal inhibitory concentration (IC₅₀) against L. infantum amastigotes. The dataset was divided into training (75%) and test sets (25%) by using a k-means clustering algorithm. For pKi prediction, model M3 with seven 3D topographic descriptors was characterized by the following statistical parameters: r ² = 0.879, Q ² _LOO = 0.822, and Q ² _ext = 0.840. For pIC₅₀ prediction, model M12 with six attributes was characterized by the following statistical parameters: r ² = 0.907, Q ² _LOO = 0.824, and Q ² _ext = 0.795. Both models met all the requirements of Tropsha´s test, which implies predictions of pIC₅₀ and pKi activities with high accuracy. Concomitantly, favourable interactions of the sulphonamide group with the Zn atom in the protein were revealed by the docking analysis.

摘要

利什曼病主要影响农村地区和世界上最贫穷的人。对有机硒和碲化合物的抗菌活性进行了计算研究。在wb97xd / lanl2dz水平上优化了化合物的3D结构，并用于定量结构-活性关系（QSAR）分析。通过杜氏乳杆菌β碳酸酐酶抑制作用（Ki）和对婴儿乳杆菌的半数最大抑制浓度（IC ₅₀）来测量抗菌活性。使用k均值聚类算法将数据集分为训练（75％）和测试集（25％）。对于pKi预测，具有七个3D地形描述符的模型M3由以下统计参数表征：r ²  = 0.879，Q ² _LOO  = 0.822，Q ² _ext  = 0.840。对于pIC ₅₀预测，通过以下统计参数来表征具有六个属性的模型M12：r ²  = 0.907，Q ² _LOO  = 0.824和Q ² _ext  = 0.795。两种模型均满足Tropsha测试的所有要求，这意味着对pIC ₅₀和pKi活动的预测具有很高的准确性。同时，通过对接分析揭示了磺酰胺基团与蛋白质中锌原子的有利相互作用。