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运用拓扑指数通过多靶标 QSAR 虚拟筛选预测抗阿尔茨海默病和抗寄生虫 GSK-3 抑制剂。

Using topological indices to predict anti-Alzheimer and anti-parasitic GSK-3 inhibitors by multi-target QSAR in silico screening.

机构信息

Department of Organic Chemistry, Faculty of Chemistry, University of Vigo, Spain.

出版信息

Molecules. 2010 Aug 9;15(8):5408-22. doi: 10.3390/molecules15085408.

Abstract

Plasmodium falciparum, Leishmania, Trypanosomes, are the causers of diseases such as malaria, leishmaniasis and African trypanosomiasis that nowadays are the most serious parasitic health problems worldwide. The great number of deaths and the few drugs available against these parasites, make necessary the search for new drugs. Some of these antiparasitic drugs also are GSK-3 inhibitors. GSKI-3 are candidates to develop drugs for the treatment of Alzheimer's disease. In this work topological descriptors for a large series of 3,370 active/non-active compounds were initially calculated with the ModesLab software. Linear Discriminant Analysis was used to fit the classification function and it predicts heterogeneous series of compounds like paullones, indirubins, meridians, etc. This study thus provided a general evaluation of these types of molecules.

摘要

疟原虫、利什曼原虫、锥虫等是疟疾、利什曼病和非洲锥虫病等疾病的病原体,这些疾病是当今全球最严重的寄生虫健康问题。大量的死亡人数和针对这些寄生虫的可用药物数量有限,使得有必要寻找新的药物。其中一些抗寄生虫药物也是 GSK-3 抑制剂。GSKI-3 是开发治疗老年痴呆症药物的候选药物。在这项工作中,使用 ModesLab 软件最初计算了 3370 种活性/非活性化合物的拓扑描述符。线性判别分析用于拟合分类函数,它可以预测类似 paullones、indirubins、meridians 等异构系列的化合物。因此,这项研究提供了对这些类型分子的全面评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0430/6257681/8de000233252/molecules-15-05408-g001.jpg

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