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Clustered patterns of species origins of nature-derived drugs and clues for future bioprospecting

机译:天然药物物种起源的聚类模式和未来生物勘探的线索

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摘要

Many drugs are nature derived. Low drug productivity has renewed interest in natural products as drug-discovery sources. Nature-derived drugs are composed of dozens of molecular scaffolds generated by specific secondary-metabolite gene clusters in selected species. It can be hypothesized that drug-like structures probably are distributed in selective groups of species. We compared the species-origins of 939 approved and 369 clinical-trial drugs with those of 119 preclinical drugs and 19,721 bioactive natural products. In contrast to the scattered distribution of bioactive natural products, these drugs are clustered into 144 of the 6,763 known species families in nature, with 80% of the approved drugs and 67% of the clinical-trial drugs concentrated in 17 and 30 drug-prolific families, respectively. Four lines of evidence from historical drug data, 13,548 marine natural products, 767 medicinal plants, and 19,721 bioactive natural products suggest that drugs are derived mostly from preexisting drug-productive families. Drug-productive clusters expand slowly by conventional technologies. The lack of drugs outside drug-productive families is not necessarily the result of under-exploration or late exploration by conventional technologies. New technologies that explore cryptic gene clusters, pathways, interspecies crosstalk, and high-throughput fermentation enable the discovery of novel natural products. The potential impact of these technologies on drug productivity and on the distribution patterns of drug-productive families is yet to be revealed.
机译:许多药物是自然界衍生的。药物生产率低下已经使人们对天然产物作为药物发现来源的兴趣重新出现。大自然衍生的药物由数十种分子支架组成,这些分子支架是由选定物种中特定的次级代谢物基因簇产生的。可以假设药物样结构可能分布在物种的选择性组中。我们将939种经批准的药物和369种临床试验药物的物种起源与119种临床前药物和19,721种生物活性天然产物的物种起源进行了比较。与分散的生物活性天然产物相反,这些药物被归类为自然界中6763个已知物种家族中的144个,其中80%的批准药物和67%的临床试验药物集中在17种和30种药物中家庭。从历史毒品数据,13,548种海洋天然产物,767种药用植物和19,721种生物活性天然产物得到的四行证据表明,毒品主要来自先前存在的毒品生产家庭。毒品生产集群通过传统技术缓慢扩张。毒品生产家庭之外缺乏毒品,不一定是传统技术未充分开发或较晚开发的结果。探索隐秘基因簇,途径,种间串扰和高通量发酵的新技术可以发现新的天然产物。这些技术对毒品生产率和毒品生产家庭分布模式的潜在影响尚待揭示。

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    Key Laboratory of Chemical Biology, Guangdong Province Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong 518055, People's Republic of China Department of Bioinformatics and Drug Design Group,National University of Singapore, Singapore 117543 Department of Pharmacy Center for Computational Science and Engineering, National University of Singapore, Singapore 117543;

    Department of Bioinformatics and Drug Design Group,National University of Singapore, Singapore 117543 Department of Pharmacy Center for Computational Science and Engineering, National University of Singapore, Singapore 117543 Department of Pharmacy, National University of Singapore Graduate School for Integrative Sciences and Engineering, Singapore 117456;

    Department of Bioinformatics and Drug Design Group,National University of Singapore, Singapore 117543 Department of Pharmacy Center for Computational Science and Engineering, National University of Singapore, Singapore 117543 Department of Pharmacy, National University of Singapore Graduate School for Integrative Sciences and Engineering, Singapore 117456;

    Department of Bioinformatics and Drug Design Group,National University of Singapore, Singapore 117543 Department of Pharmacy Center for Computational Science and Engineering, National University of Singapore, Singapore 117543;

    Department of Bioinformatics and Drug Design Group,National University of Singapore, Singapore 117543 Department of Pharmacy Center for Computational Science and Engineering, National University of Singapore, Singapore 117543;

    Department of Bioinformatics and Drug Design Group,National University of Singapore, Singapore 117543 Department of Pharmacy Center for Computational Science and Engineering, National University of Singapore, Singapore 117543;

    Department of Bioinformatics and Drug Design Group,National University of Singapore, Singapore 117543 Department of Pharmacy Center for Computational Science and Engineering, National University of Singapore, Singapore 117543;

    Key Laboratory of Chemical Biology, Guangdong Province Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong 518055, People's Republic of China;

    Key Laboratory of Chemical Biology, Guangdong Province Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong 518055, People's Republic of China;

    Key Laboratory of Chemical Biology, Guangdong Province Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong 518055, People's Republic of China;

    Key Laboratory of Chemical Biology, Guangdong Province Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong 518055, People's Republic of China;

    Key Laboratory of Chemical Biology, Guangdong Province Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong 518055, People's Republic of China School of Medicine and Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China;

    Key Laboratory of Chemical Biology, Guangdong Province Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong 518055, People's Republic of China Department of Bioinformatics and Drug Design Group,National University of Singapore, Singapore 117543 Department of Bioinformatics and Drug Design Group,National University of Singapore, Singapore 117543;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    biodiversity; drug-prolific species; phylogenetic tree; herb;

    机译:生物多样性;药物丰富的物种;进化树;药草;

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