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非洲药用植物数据库(AfroDb):一个精选的来自非洲药用植物的高效且多样的天然产物库。

AfroDb: a select highly potent and diverse natural product library from African medicinal plants.

作者信息

Ntie-Kang Fidele, Zofou Denis, Babiaka Smith B, Meudom Rolande, Scharfe Michael, Lifongo Lydia L, Mbah James A, Mbaze Luc Meva'a, Sippl Wolfgang, Efange Simon M N

机构信息

Chemical and Bioactivity Information Centre, Department of Chemistry, Faculty of Science, University of Buea, Buea, Cameroon ; Center Atomic Molecular Physics, Optics and Quantum, Faculty of Science, University of Douala, Douala, Cameroon ; Department of Pharmaceutical Sciences, Martin-Luther University of Halle-Wittenberg, Halle (Saale), Germany.

出版信息

PLoS One. 2013 Oct 30;8(10):e78085. doi: 10.1371/journal.pone.0078085. eCollection 2013.

Abstract

Computer-aided drug design (CADD) often involves virtual screening (VS) of large compound datasets and the availability of such is vital for drug discovery protocols. We assess the bioactivity and "drug-likeness" of a relatively small but structurally diverse dataset (containing >1,000 compounds) from African medicinal plants, which have been tested and proven a wide range of biological activities. The geographical regions of collection of the medicinal plants cover the entire continent of Africa, based on data from literature sources and information from traditional healers. For each isolated compound, the three dimensional (3D) structure has been used to calculate physico-chemical properties used in the prediction of oral bioavailability on the basis of Lipinski's "Rule of Five". A comparative analysis has been carried out with the "drug-like", "lead-like", and "fragment-like" subsets, as well as with the Dictionary of Natural Products. A diversity analysis has been carried out in comparison with the ChemBridge diverse database. Furthermore, descriptors related to absorption, distribution, metabolism, excretion and toxicity (ADMET) have been used to predict the pharmacokinetic profile of the compounds within the dataset. Our results prove that drug discovery, beginning with natural products from the African flora, could be highly promising. The 3D structures are available and could be useful for virtual screening and natural product lead generation programs.

摘要

计算机辅助药物设计(CADD)通常涉及对大型化合物数据集的虚拟筛选(VS),而此类数据集的可用性对于药物发现方案至关重要。我们评估了一个相对较小但结构多样的数据集(包含1000多种化合物)的生物活性和“类药性”,该数据集来自非洲药用植物,这些植物已经过测试并证明具有广泛的生物活性。根据文献来源的数据和传统治疗师提供的信息,药用植物的采集地理区域覆盖了整个非洲大陆。对于每种分离出的化合物,其三维(3D)结构已用于计算基于Lipinski“五规则”预测口服生物利用度时所使用的物理化学性质。已与“类药”、“类先导物”和“类片段”子集以及《天然产物词典》进行了比较分析。已与ChemBridge多样数据库进行了多样性分析。此外,与吸收、分布、代谢、排泄和毒性(ADMET)相关的描述符已用于预测数据集中化合物的药代动力学特征。我们的结果证明,从非洲植物群中的天然产物开始进行药物发现可能非常有前景。这些3D结构是可用的,并且可能对虚拟筛选和天然产物先导物生成程序有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af70/3813505/7dcf6d0268a5/pone.0078085.g001.jpg

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