A chemoinformatics approach to the discovery of lead-like molecules from marine and microbial sources en route to antitumor and antibiotic drugs.

A chemoinformatics approach to the discovery of lead-like molecules from marine and microbial sources en route to antitumor and antibiotic drugs.
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从海洋和微生物来源发现抗肿瘤和抗生素药物的铅样分子的化学信息学方法。

DOI:
10.3390/md12020757
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发表时间:
2014-01-27
期刊:
影响因子:
5.4
通讯作者:
Gaudêncio SP
Gaudêncio SP
中科院分区:
医学2区
文献类型:
--
作者:
Pereira F;Latino DA;Gaudêncio SP

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PubChem数据库中的小分子及其生物活性的全面信息允许化学信息学研究人员访问和利用大规模的生物活性数据,以提高药物分析的精度。使用PubChem的1804种化合物的数据集,使用定量结构-活性关系方法进行分类,用于相对于总体生物活性、抗肿瘤和抗生素活性预测活性/非活性化合物。利用最佳的抗生素和抗肿瘤活性的分类模型,从AntiMarin数据库中筛选了海洋和微生物天然产物的数据集-分别提出了57个和16个新的抗生素和抗肿瘤药物设计的先导化合物。我们的方法提出的所有化合物在AntiMarin数据库中被分类为非抗生素和非抗肿瘤化合物。最近,我们提出的几个类铅化合物在文献中被报道为具有活性。
The comprehensive information of small molecules and their biological activities in the PubChem database allows chemoinformatic researchers to access and make use of large-scale biological activity data to improve the precision of drug profiling. A Quantitative Structure–Activity Relationship approach, for classification, was used for the prediction of active/inactive compounds relatively to overall biological activity, antitumor and antibiotic activities using a data set of 1804 compounds from PubChem. Using the best classification models for antibiotic and antitumor activities a data set of marine and microbial natural products from the AntiMarin database were screened—57 and 16 new lead compounds for antibiotic and antitumor drug design were proposed, respectively. All compounds proposed by our approach are classified as non-antibiotic and non-antitumor compounds in the AntiMarin database. Recently several of the lead-like compounds proposed by us were reported as being active in the literature.
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