机器学习技术和鉴定新的潜在活性化合物对抗幼利什曼原虫。

Naivi Flores Balmaseda, Susana Rojas Socarrás, J. A. C. Garit
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引用次数: 1

摘要

利什曼病被定义为由利什曼属专性细胞内寄生虫产生的一组临床表现非常不同的疾病。它们已被世界卫生组织列为第一类传染病,是被忽视的热带疾病的一部分。婴儿利什曼原虫主要影响五岁以下儿童,并与皮肤和内脏利什曼病的出现增加有关。寻找新的治疗方案仍然是一个挑战,而计算机研究是解决这一问题的替代工具。本研究的主要目的是通过计算机研究鉴定抗利什曼原虫的潜在有效化合物,在WEKA程序中实现的人工智能技术和DRAGON软件的分子描述符0D-2D被用于本研究。建立了一个新的数据库,并使用聚类分析(AC) k-means来设计训练和预测序列。采用IBk、J48、MLP和SMO四种技术对训练序列和预测序列的分类率均达到80%以上,并通过外部和内部验证程序确认了其预测能力。利用在国际数据库DrugBank和合成化合物的虚拟筛选中获得的模型,可以对120种新的抗利什曼原虫无马鞭毛体形式的潜在活性化合物进行最佳鉴定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine learning techniques and the identification of new potentially active compounds against Leishmania infantum.
Leishmaniasis is defined as a set of diseases of very varied clinical presentation produced by obligate intracellular parasites belonging to the genus Leishmania. They have been classified by the World Health Organization in category I of infectious diseases and are part of neglected tropical pathologies. Leishmania infantum mainly affects children under five years of age and has been associated with an increase in the appearance of cutaneous and visceral leishmaniasis. The search for new therapeutic alternatives remains a challenge and in silico studies are alternative tools to solve this problem. With the main objective of identify potentially effective compounds against Leishmania infantum through in silico studies, artificial Intelligence techniques implemented in the WEKA program and molecular descriptors 0D-2D of DRAGON software are used in this research. A new database was created and the clusters analysis (AC) k-means was used to design the training and prediction series. Four models were obtained with the following techniques: IBk, J48, MLP and SMO that reached percentages of classification higher than 80% for training and prediction series, whose predictive power was confirmed through external and internal validation procedures. The use of the models obtained in the virtual screening of the international database DrugBank and synthesis compounds allowed the optimal identification of 120 new potentially active compounds against Leishmania infantum amastigote form.
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