| ORIGINAL ARTICLES |
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Leveraging off higher plant phylogenetic insights for antiplasmodial drug discovery |
| Phanankosi Moyo1, Luke Invernizzi1, Sephora M. Mianda1, Wiehan Rudolph1, Warren A. Andayi2, Mingxun Wang3, Neil R. Crouch4,5, Vinesh J. Maharaj1 |
1. Biodiscovery Center, Department of Chemistry, Faculty of Natural and Agricultural Sciences, University of Pretoria, Private Bag X 20, Hatfield, Pretoria, 0028, South Africa;
2. Department of Physical and Biological Sciences, Murang'a University of Technology, Murang'a, Kenya;
3. Computer Science and Engineering, University of California Riverside, 900 University Ave, Riverside, CA, 92521, USA;
4. Biodiversity Research and Monitoring Directorate, South African National Biodiversity Institute, Berea Road, P. O. Box 52099, Durban, 4007, South Africa;
5. School of Chemistry and Physics, University of KwaZulu-Natal, Durban, 4041, South Africa |
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Abstract 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 (IC50≤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.
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| Keywords
Natural products
Plants
Phylogenetics
Malaria
Drug-resistance
‘Hot’ plants
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| Fund:Foundation L’Oréal (4500453975). |
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Corresponding Authors:
Vinesh J. Maharaj,E-mail:vinesh.maharaj@up.ac.za
E-mail: vinesh.maharaj@up.ac.za
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Issue Date: 03 November 2023
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[1] Cox FE. History of the discovery of the malaria parasites and their vectors. Parasit Vectors. 2010;3(1):1-9.
[2] WHO, World malaria report 2022. 2022: World Health Organization.
[3] Ippolito MM, et al. Antimalarial drug resistance and implications for the WHO global technical strategy. Curr Epidemiol Rep. 2021;8:46-62.
[4] Matthews H, Duffy CW, Merrick CJ. Checks and balances? DNA replication and the cell cycle in Plasmodium. Parasit Vectors. 2018;11(1):216.
[5] Gupta DK, et al. DNA damage regulation and its role in drug-related phenotypes in the malaria parasites. Sci Rep. 2016;6(1):23603.
[6] Blasco B, Leroy D, Fidock DA. Antimalarial drug resistance: linking Plasmodium falciparum parasite biology to the clinic. Nat Med. 2017;23(8):917-28.
[7] Newman DJ, Cragg GM. Natural products as sources of new drugs over the nearly four decades from 01/1981 to 09/2019. J Nat Prod. 2020;83(3):770-803.
[8] Wells TNC. Natural products as starting points for future anti-malarial therapies: going back to our roots? Malar J. 2011;10(1):S3.
[9] Yang J, et al. Advances in the research on the targets of anti-malaria actions of artemisinin. Pharmacol Ther. 2020;216: 107697.
[10] Institute of Medicine Committee on the Economics of Antimalarial D. In Arrow KJ, Panosian C, Gelband H, editors. Saving lives, buying time: economics of malaria drugs in an age of resistance. National Academies Press (US); 2004. Copyright 2004 by the National Academy of Sciences. All rights reserved.: Washington (DC).
[11] Milliken W, et al. Plants used traditionally as antimalarials in Latin America: mining the tree of life for potential new medicines. J Ethnopharmacol. 2021;279: 114221.
[12] Christenhusz MJ, Byng JW. The number of known plants species in the world and its annual increase. Phytotaxa. 2016;261(3):201-17.
[13] Douwes E, et al. Regression analyses of southern African ethnomedicinal plants: informing the targeted selection of bioprospecting and pharmacological screening subjects. J Ethnopharmacol. 2008;119(3):356-64.
[14] Holzmeyer L, et al. Evaluation of plant sources for antiinfective lead compound discovery by correlating phylogenetic, spatial, and bioactivity data. Proc Natl Acad Sci. 2020;117(22):12444-51.
[15] Zhu F, et al. Clustered patterns of species origins of nature-derived drugs and clues for future bioprospecting. Proc Natl Acad Sci. 2011;108(31):12943-8.
[16] Rønsted N, et al. Phylogenetic selection of Narcissus species for drug discovery. Biochem Syst Ecol. 2008;36(5-6):417-22.
[17] Mawalagedera SM, et al. Combining evolutionary inference and metabolomics to identify plants with medicinal potential. Front Ecol Evol. 2019;7:267.
[18] Prasad MA, Zolnik CP, Molina J. Leveraging phytochemicals: the plant phylogeny predicts sources of novel antibacterial compounds. Fut Sci OA. 2019;5(7):FSO407.
[19] Mahajan GB, Balachandran L. Antibacterial agents from actinomycetes—a review. Front Biosci-Elite. 2012;4(1):240-53.
[20] Aminov R. History of antimicrobial drug discovery: major classes and health impact. Biochem Pharmacol. 2017;133:4-19.
[21] Berkov S, et al. Chemodiversity, chemotaxonomy and chemoecology of Amaryllidaceae alkaloids. Alkaloids Chem Biol. 2020;83:113-85.
[22] Li X, et al. What makes species productive of anti-cancer drugs? Clues from drugs’ species origin, druglikeness, target and pathway. Anti-Cancer Agents Med Chem (Formerly Current Medicinal Chemistry-Anti-Cancer Agents). 2019;19(2):194-203.
[23] Egieyeh SA, et al. Prioritization of anti-malarial hits from nature: chemo-informatic profiling of natural products with in vitro antiplasmodial activities and currently registered anti-malarial drugs. Malar J. 2016;15:1-23.
[24] Schoch CL, et al. NCBI Taxonomy: a comprehensive update on curation, resources and tools. Database. 2020. 2020.
[25] Letunic I, Bork P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 2021;49(W1):W293-6.
[26] Borsch T, et al. World Flora Online: placing taxonomists at the heart of a definitive and comprehensive global resource on the world’s plants. Taxon. 2020;69(6):1311-41.
[27] Lipinski CA, et al. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev. 2001;46:3-26.
[28] Veber DF, et al. Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem. 2002;45(12):2615-23.
[29] Ghose AK, Viswanadhan VN, Wendoloski JJ. A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. J Comb Chem. 1999;1(1):55-68.
[30] Trauner D, Roßmann K. A conversation with Gerhard Bringmann. ACS Publications; 2020. p. 1248-1252.
[31] Charman SA, et al. An in vitro toolbox to accelerate anti-malarial drug discovery and development. Malar J. 2020;19(1):1-27.
[32] Kim HW, et al. NPClassifier: a deep neural network-based structural classification tool for natural products. J Nat Prod. 2021;84(11):2795-807.
[33] Cihan Sorkun M, et al. ChemPlot, a Python library for chemical space visualization. Chemistry-Methods. 2022;2(7): e202200005.
[34] Lianaa D, Rungsihirunrata K. Using phylogeny approach on ethnobotanical bioprospecting for leading antimalarial plant-based drug discovery.
[35] Nondo RS, et al. Ethnobotanical survey and in vitro antiplasmodial activity of medicinal plants used to treat malaria in Kagera and Lindi regions, Tanzania. J Med Plants Res. 2015;9(6):179-92.
[36] Yetein MH, et al. Ethnobotanical study of medicinal plants used for the treatment of malaria in plateau of Allada, Benin (West Africa). J Ethnopharmacol. 2013;146(1):154-63.
[37] Hovlid ML, Winzeler EA. Phenotypic screens in antimalarial drug discovery. Trends Parasitol. 2016;32(9):697-707.
[38] O’Neill MJ, et al. Plants as sources of antimalarial drugs, part 4: activity of Brucea javanica fruits against chloroquine-resistant Plasmodium falciparum in vitro and against Plasmodium berghei in vivo. J Nat Prod. 1987;50(1):41-8.
[39] Szabó LU, et al. Antiprotozoal nor-triterpene alkaloids from Buxus sempervirens L. Antibiotics. 2021;10(6):696.
[40] Pei Y, et al. Quassinoid analogs with enhanced efficacy for treatment of hematologic malignancies target the PI3Kγ isoform. Commun Biol. 2020;3(1):267.
[41] Francois G, et al. Naphthylisoquinoline alkaloids against malaria: evaluation of the curative potentials of dioncophylline C and dioncopeltine A against Plasmodium berghei in vivo. Antimicrob Agents Chemother. 1997;41(11):2533-9.
[42] Tajuddeen N, et al. The stereoselective total synthesis of axially chiral naphthylisoquinoline alkaloids. Acc Chem Res. 2022;55(17):2370-83.
[43] Bringmann G, et al. Synthesis and antiprotozoal activities of simplified analogs of naphthylisoquinoline alkaloids. Eur J Med Chem. 2008;43(1):32-42.
[44] Dechering KJ, et al. Replenishing the malaria drug discovery pipeline: screening and hit evaluation of the MMV Hit Generation Library 1 (HGL1) against asexual blood stage Plasmodium falciparum, using a nano luciferase reporter read-out. SLAS Discov. 2022;27(6):337-48.
[45] Plouffe D, et al. In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen. Proc Natl Acad Sci. 2008;105(26):9059-64.
[46] White J. PubMed 2.0. Medical Reference Services Quarterly. 2020. 39(4): 382-387.
[47] Kim S, et al. PubChem substance and compound databases. Nucleic Acids Res. 2016;44(D1):D1202-13.
[48] Pence HE, Williams A. ChemSpider: an online chemical information resource. ACS Publications; 2010.
[49] Mendelsohn LD. ChemDraw 8 ultra, windows and macintosh versions. J Chem Inf Comput Sci. 2004;44(6):2225-6.
[50] Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep. 2017;7(1):42717. |
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