Literature DB >> 30370862

What Makes Species Productive of Anti-Cancer Drugs? Clues from Drugs' Species Origin, Druglikeness, Target and Pathway.

Xiaofeng Li1,2, Xiaoxu Li1,2, Yinghong Li1,2, Chunyan Yu1,2, Weiwei Xue2, Jie Hu3, Bo Li2, Panpan Wang2, Feng Zhu1,2.   

Abstract

BACKGROUND: Despite the substantial contribution of natural products to the FDA drug approval list, the discovery of anti-cancer drugs from the huge amount of species on the planet remains looking for a needle in a haystack.
OBJECTIVE: Drug-productive clusters in the phylogenetic tree are thus proposed to narrow the searching scope by focusing on much smaller amount of species within each cluster, which enable prioritized and rational bioprospecting for novel drug-like scaffolds. However, the way anti-cancer nature-derived drugs distribute in phylogenetic tree has not been reported, and it is oversimplified to just focus anti-cancer drug discovery on the drug-productive clusters, since the number of species in each cluster remains too large to be managed.
METHODS: In this study, 260 anti-cancer drugs approved in the past 70 years were comprehensively analyzed by hierarchical clustering of phylogenetic distribution.
RESULTS: 207 out of these 260 drugs were derived from or inspired by the natural products isolated from 58 species. Phylogenetic distribution of those drugs further revealed that nature-derived anti-cancer drugs originated mostly from drug-productive families that tend to be clustered rather than scattered on the phylogenetic tree. Moreover, based on their productivity, drug-producing species were categorized into productive (CPS), newly emerging (CNS) and lessproductive (CLS). Statistical significances in druglikeness between drugs from CPS and CLS were observed, and drugs from CNS were found to share similar drug-like properties to those from CPS.
CONCLUSION: This finding indicated a great raise in drug approval standard, which suggested us to focus bioprospecting on the species yielding multiple drugs and keeping productive for long period of time. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Entities:  

Keywords:  Anti-cancer drugs; druglikeness; medicinal chemistry; nature-derived drugs; phylogenetic distribution; target and pathway.

Mesh:

Substances:

Year:  2019        PMID: 30370862     DOI: 10.2174/1871520618666181029132017

Source DB:  PubMed          Journal:  Anticancer Agents Med Chem        ISSN: 1871-5206            Impact factor:   2.505


  5 in total

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Journal:  Brief Bioinform       Date:  2020-07-15       Impact factor: 11.622

2.  Prediction of GluN2B-CT1290-1310/DAPK1 Interaction by Protein⁻Peptide Docking and Molecular Dynamics Simulation.

Authors:  Gao Tu; Tingting Fu; Fengyuan Yang; Lixia Yao; Weiwei Xue; Feng Zhu
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4.  Synthesis and potent cytotoxic activity of a novel diosgenin derivative and its phytosomes against lung cancer cells.

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Journal:  Beilstein J Nanotechnol       Date:  2019-09-24       Impact factor: 3.649

5.  Clinical trials, progression-speed differentiating features and swiftness rule of the innovative targets of first-in-class drugs.

Authors:  Ying Hong Li; Xiao Xu Li; Jia Jun Hong; Yun Xia Wang; Jian Bo Fu; Hong Yang; Chun Yan Yu; Feng Cheng Li; Jie Hu; Wei Wei Xue; Yu Yang Jiang; Yu Zong Chen; Feng Zhu
Journal:  Brief Bioinform       Date:  2020-03-23       Impact factor: 11.622

  5 in total

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