The strides made in malaria eradication efforts have been aided by a combination of vector control and chemoprevention. However, Plasmodium resistance to first-line artemisinin-based combination therapies (ACTs), and mosquito resistance to insecticides threatens the progress made. Innovative vector control measures, vaccines and antimalarial drugs with novel modes of action are key to disease eradication.
High-throughput phenotypic screening of chemical libraries tested directly against all the stages of the Plasmodium lifecycle have been the mainstay of antimalarial drug discovery efforts and have identified compounds that are effective in parasite clearance. Unfortunately, these screens are handicapped in that they are unable to specify the actual compound targets in the Plasmodium parasites. As a result, many candidate hits have had to be re-screened in specific assays to determine putative mechanisms of antiplasmodial action. Predictably, this has elevated target-specific screens as the next frontier in drug discovery. This shift has been aided by a number of factors, including the cost effectiveness of these screens and the fact that target-specific screens do not always require specialized access to parasites. When combined with knowledge of the target’s structure, where known, target-specific screens have the potential to give lead compounds with impeccable potency and selectivity. This approach has already been successfully put to use, for example, in the identification of P. falciparum p-type ATPase 4 (PfATP4) and P. falciparum phosphatidylinositol 4-kinase (PfPI(4)K) inhibitors. The new challenge now is the identification of quality targets. Here, computational biology ‘omics’ tools have proved to be an invaluable resource. Two of the more commonly used of these tools are genomics and metabolomics.
In-vitro evolution assays followed by whole genome sequencing analysis is a popular genomics approach and helps unveil novel target genes. Plasmodium parasites are exposed to sublethal doses of a compound until an upward shift in the half-maximal inhibitory concentration (IC50), indicative of resistant parasites, is observed in the culture. Sequenced genomes of the resistant parasite clones are compared to those of the drug-naive parent to reveal genetic changes, which include both single nucleotide polymorphisms (SNPs) and copy number variations (CNVs). While these genomic changes may point to genes encoding actual drug targets, they often reveal mediators of drug resistance or tolerance. Follow-up assays like SNP validation through gene editing are necessary to distinguish between actual targets, resistance mechanisms and random background mutations. Expectedly, genetic changes in uncharacterized Plasmodium genes are the bottle-necks in the identification of novel druggable targets. Even so, this genomics method has uncovered or reconfirmed novel antimalarial drug targets, including the proteasome, aminophospholipid-transporting P-type ATPase (PfAT-Pase2) and cGMP-dependent protein kinase (PfPKG).
Metabolomic profiling and transcriptomics narrows down a compound’s mode of action. Here, parasites are treated with a compound of interest and the metabolites extracted and analyzed using liquid chromatography-mass spectrometry (LC-MS). The metabolomics fingerprint or metaprint is then compared to that of untreated parasites. While this method rarely provides the exact drug target, it narrows down the compound’s mode of action, which is valuable for target validation and characterization. The issue of non-specific or non-viable phenotype metabolite signals is easily filtered out by treating parasites with various drug concentrations and/or over a period of time. Other areas that limit the effectiveness of this tool and need to be addressed include the analysis of compounds that do not act through metabolic pathway disruption and potential host contamination. Nonetheless, metabolomics are a key player in drug discovery and have successfully been used in the study of pantothenamides (MMV689258) where the observed CoA analog buildup helped identify their mechanism of action in sequestering coenzyme A to block acetyl-CoA anabolism.
Presented herein is a culmination of my graduate research in antimalarial drug discovery. Three independent projects are presented, and they all have either been published or are currently under reviewership. Chapter 1 is an introduction to malaria, a disease that has and continues to claim hundreds of thousands of lives, especially in my home continent of Africa. In chapter 2, I detail the experimental procedures used to generate the data presented in chapters 3-5. Chapter 3 is a detailed susceptibility profiling and metabolomic fingerprinting of Plasmodium falciparum asexual blood stages (ABS) to clinical and experimental antimalarials. This work, published in Cell Chemical Biology (2020), presents to the malaria research community a medium-throughput assay that can be utilized to identify new antimalarial lead compounds and novel assayable targets. Chapter 4 presents a detailed analysis of a novel ATP-binding cassette (ABC) transporter that confers pleiotropic antimalarial drug resistance in P. falciparum and that was first identified through in vitro evolution assays. This work is currently under review in Cell Chemical Biology. Chapter 5 presents work on an promising new preclinical compound, MMV688533, that provides single-dose cure and that was discovered using an innovative orthology-based screen by the Sanofi drug discovery team. In this chapter, I also present in detail the assays performed to better understand this compound’s mode of antiplasmodial action and the potential drivers of parasite resistance. This work has been accepted, pending minor textual revisions, in Science Translational Medicine. Finally in chapter 6, I summarize chapters 3-5 and share future follow-up work needed to strengthen and contextualize some of the experimental findings presented here.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-n6ja-7e15 |
| Date | January 2021 |
| Creators | Murithi, James Muriungi |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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