Moyo Phanankosi, Invernizzi Luke, Mianda Sephora M, Rudolph Wiehan, Andayi Warren A, Wang Mingxun, Crouch Neil R, Maharaj Vinesh J
Biodiscovery Center, Department of Chemistry, Faculty of Natural and Agricultural Sciences, University of Pretoria, Private Bag X 20, Hatfield, Pretoria, 0028, South Africa.
Department of Physical and Biological Sciences, Murang'a University of Technology, Murang'a, Kenya.
Nat Prod Bioprospect. 2023 Oct 5;13(1):35. doi: 10.1007/s13659-023-00396-x.
The antimalarial drug-resistance conundrum which threatens to reverse the great strides taken to curb the malaria scourge warrants an urgent need to find novel chemical scaffolds to serve as templates for the development of new antimalarial drugs. Plants represent a viable alternative source for the discovery of unique potential antiplasmodial chemical scaffolds. To expedite the discovery of new antiplasmodial compounds from plants, the aim of this study was to use phylogenetic analysis to identify higher plant orders and families that can be rationally prioritised for antimalarial drug discovery. We queried the PubMed database for publications documenting antiplasmodial properties of natural compounds isolated from higher plants. Thereafter, we manually collated compounds reported along with plant species of origin and relevant pharmacological data. We systematically assigned antiplasmodial-associated plant species into recognised families and orders, and then computed the resistance index, selectivity index and physicochemical properties of the compounds from each taxonomic group. Correlating the generated phylogenetic trees and the biological data of each clade allowed for the identification of 3 'hot' plant orders and families. The top 3 ranked plant orders were the (i) Caryophyllales, (ii) Buxales, and (iii) Chloranthales. The top 3 ranked plant families were the (i) Ancistrocladaceae, (ii) Simaroubaceae, and (iii) Buxaceae. The highly active natural compounds (IC ≤ 1 µM) isolated from these plant orders and families are structurally unique to the 'legacy' antimalarial drugs. Our study was able to identify the most prolific taxa at order and family rank that we propose be prioritised in the search for potent, safe and drug-like antimalarial molecules.
抗疟药物耐药性难题有可能使在遏制疟疾祸害方面取得的巨大进展发生逆转,因此迫切需要找到新的化学骨架,作为开发新型抗疟药物的模板。植物是发现具有独特潜在抗疟化学骨架的可行替代来源。为了加快从植物中发现新的抗疟化合物,本研究的目的是利用系统发育分析来确定可以合理优先用于抗疟药物发现的高等植物目和科。我们在PubMed数据库中查询了记录从高等植物中分离出的天然化合物抗疟特性的出版物。此后,我们手动整理了报告的化合物及其来源植物物种和相关药理学数据。我们系统地将与抗疟相关的植物物种归入公认的科和目,然后计算每个分类组中化合物的耐药指数、选择性指数和物理化学性质。将生成的系统发育树与每个进化枝的生物学数据相关联,从而确定了3个“热门”植物目和科。排名前三的植物目分别是:(i)石竹目,(ii)黄杨目,和(iii)金粟兰目。排名前三的植物科分别是:(i)钩枝藤科,(ii)苦木科,和(iii)黄杨科。从这些植物目和科中分离出的高活性天然化合物(IC≤1µM)在结构上与“传统”抗疟药物不同。我们的研究能够确定在目和科级别的最多产分类群,我们建议在寻找有效、安全和类药物的抗疟分子时优先考虑这些分类群。