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综述沼生目植物中分离得到的化合物及其通过机器学习评估生物活性

Review on Compounds Isolated from Eriocaulaceae Family and Evaluation of Biological Activities by Machine Learning.

机构信息

Post-Graduate Program in Chemistry, Federal University of Espírito Santo, Av. Fernando Ferrari, 514, Vitória 29075-910, Brazil.

Post-Graduate Program in Natural Synthetic Bioactive Products, Federal University of Paraiba, R. Table Stanislau Eloy, 41-Conj. Pres. Castelo Branco III, João Pessoa 58050-585, Brazil.

出版信息

Molecules. 2022 Oct 24;27(21):7186. doi: 10.3390/molecules27217186.

DOI:10.3390/molecules27217186
PMID:36364014
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9654208/
Abstract

Eriocaulaceae is a pantropical family whose main center of biodiversity is in Brazil. In general, the family has about 1200 species, in which phytochemical and biological studies have shown a variety of structures and activities. The aim of this research is to compile the compounds isolated in the Eriocaulaceae family and carry out a computational study on their biological targets. The bibliographic research was carried out on six databases. Tables were built and organized according to the chemical class. In addition, a summary of the methods of isolating the compounds was also made. In the computational study were used ChEMBL platform, DRAGON 7.0, and the KNIME 4.4.0 software. Two hundred and twenty-two different compounds have been isolated in sixty-eight species, divided mainly into flavonoids and naphthopyranones, and minor compounds. The ligand-based virtual screening found promising molecules and molecules with multitarget potential, such as xanthones , , and saponin , with xanthone as the most promising. Several compounds with biological activities were isolated in the family, but the chemical profiles of many species are still unknown. The selected structures are a starting point for further studies to develop new antiparasitic and antiviral compounds based on natural products.

摘要

眼子菜科是一个泛热带科,其生物多样性的主要中心在巴西。一般来说,该科约有 1200 种,植物化学和生物研究表明其具有多种结构和活性。本研究旨在对眼子菜科中分离得到的化合物进行汇编,并对其生物靶标进行计算研究。文献研究在六个数据库中进行。根据化学类别构建和组织了表格。此外,还对化合物的分离方法进行了总结。在计算研究中,使用了 ChEMBL 平台、DRAGON 7.0 和 KNIME 4.4.0 软件。已从六十八种植物中分离出二百二十二种不同的化合物,主要分为黄酮类和萘并吡喃酮类,以及少量化合物。基于配体的虚拟筛选发现了有前景的分子和具有多靶标潜力的分子,如黄烷酮、和皂角苷,其中黄烷酮 最有前景。该科分离出了一些具有生物活性的化合物,但许多种的化学特征仍不清楚。所选结构为进一步研究开发基于天然产物的新型抗寄生虫和抗病毒化合物提供了起点。