BACKGROUND Chemoinformatics has several applications in the field of drug design, helping to identify new compounds against a range of ailments. Among these are Leishmaniasis, effective treatments for which are currently limited. OBJECTIVE To construct new indole 2-aminothiophene molecules using computational tools and to test their effectiveness against Leishmania amazonensis (sp.). METHODS Based on the chemical structure of thiophene-indol hybrids, we built regression models and performed molecular docking, and used these data as bases for design of 92 new molecules with predicted pIC50 and molecular docking. Among these, six compounds were selected for the synthesis and to perform biological assays (leishmanicidal activity and cytotoxicity). RESULTS The prediction models and docking allowed inference of characteristics that could have positive influences on the leishmanicidal activity of the planned compounds. Six compounds were synthesized, one-third of which showed promising antileishmanial activities, with IC50 ranging from 2.16 and 2.97 μM (against promastigote forms) and 0.9 and 1.71 μM (against amastigote forms), with selectivity indexes (SI) of 52 and 75. CONCLUSION These results demonstrate the ability of Quantitative Structure-Activity Relationship (QSAR)-based rational drug design to predict molecules with promising leishmanicidal potential, and confirming the potential of thiophene-indole hybrids as potential new leishmanial agents.

中文翻译：

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噻吩-吲哚杂合体作为利什曼制剂的计算机辅助设计。

背景技术化学信息学在药物设计领域中具有多种应用，有助于识别针对多种疾病的新化合物。其中有利什曼病，目前对其有效治疗方法有限。目的使用计算工具构建新的吲哚2-氨基噻吩分子，并测试其对亚马逊利什曼原虫的有效性。方法基于噻吩-吲哚杂化物的化学结构，建立回归模型并进行分子对接，并将这些数据用作设计具有预测的pIC50和分子对接的92个新分子的基础。在这些化合物中，选择了六种化合物进行合成并进行生物学测定（杀人类活性和细胞毒性）。结果预测模型和对接允许推断出可能对计划中的化合物的杀菌活性产生积极影响的特性。合成了六种化合物，其中三分之一表现出有希望的抗菌活性，IC50范围为2.16和2.97μM（反对前鞭毛体形式）以及0.9和1.71μM（反对鞭毛体形式），选择性指数（SI）为52和75。结论这些结果证明了基于定量结构-活性关系（QSAR）的合理药物设计能够预测具有良好杀人潜力的分子，并证实了噻吩-吲哚杂合体作为潜在的新型利什曼病制剂的潜力。