Jessica Leigh Thibaud
RESEARCH PROJECT: Targeting Plasmodium falciparum cGMP-dependent Protein Kinase: Machine learning and Medicinal Chemistry Approaches.
With cum laude Undergraduate, Honours and Masters degrees in her pocket, and bursaries, awards and an early publication under her belt, Jessica is currently focusing on her PhD in chemistry, with specific focus on the application of computational processes to antimalarial drug discovery.
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“Malaria is a severe infectious disease and medicines that are usually prescribed to treat it are no longer effective. For this reason, there is an urgent need for new antimalarial treatments,” she explains. Current medicines work by inhibiting the function of a specific ‘target’ in the malaria parasite’s life cycle critical to its survival. Jessica’s project uses machine learning to do this. Simply put, a computer algorithm is trained in how to identify compounds that will most likely inhibit my chosen target. These compounds then get laboratory tested against the actual target itself. In this way, the model can learn from itself and get better.
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“For my project, I am trying to inhibit a protein in the malaria parasite that allows it to grow and reproduce. By preventing this protein from doing its job, the parasite will no longer be able to grow and will ultimately die.”
Malaria is a severe parasitic disease responsible for 627 000 deaths in 2020 alone. Of the 627 000 deaths in 2020, 96% occurred in sub-Saharan Africa and were primarily caused by the most lethal Anopheles mosquito-borne parasite, Plasmodium falciparum. Unfortunately, pregnant women and children are most at-risk of this disease, and worryingly, the global incidence rate of malaria is once again on the rise. The proposed research has great potential for positive socio-economic impact in South Africa, especially considering the extent of the world’s population at risk of contracting malaria.
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This project involves the application of computational techniques, including principal component analysis (PCA), molecular modelling and machine learning (ML), towards the discovery of structurally novel antimalarial compounds. This scientist is specifically interested in compounds that work by inhibiting an enzyme in the Plasmodium falciparum malaria parasite, referred to as cGMP dependent protein kinase or protein kinase G (PKG). This enzyme plays an essential role in the parasite’s lifecycle, and literature has shown that the inhibition of this enzyme leads to parasite death.
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If successful, this research project will have a substantial positive influence on people’s lives as the development of new treatments has direct implications for alleviation of the disease burden, and thus socio-economic upliftment, within some of the world’s poorest regions.
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These learning models are not disease-specific. “Their application to other neglected tropical diseases or cancers, for example, is a very real possibility.”
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Jessica started with general science studies, but became focused on medicinal chemistry, when she was exposed to it. “The lecturer at that time was my current supervisor, Dr. Katherine de Villiers, who plays an integral role in my project,” she says. “In addition, this project is close to my heart because it attempts to tackle a problem that is particularly prevalent in sub-Saharan Africa and affects mostly the poorest populations. This is science happening in Africa for Africans.”
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As with many women scientists, one of the constant challenges that she has had to face is the lack of bursaries and student funding available. “This is why initiatives like the L’Oréal-UNESCO FWIS are so important. Finding a source of funding is tough and can severely limit your growth as a young scientist.”
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Just as she was mentored, Jessica does the same as she enthusiastically encourages younger women to pursue careers in science.
“I would say that the three most important elements for me are passion, innovation, and confidence. I think that having a passion for science is essential if you want to pursue a career in it. The field of science is vast and so this requires exploration of the different fields to find what you enjoy. I strongly suggest talking to your teachers/parents/lecturers about your interests. Work experience is also a great way to explore the different research areas if you get the opportunity. University labs are always open to young students who want to have a look around their facilities. Secondly, innovation or a creative spirit and science go hand-in-hand. Science is all about problem-solving and investigating the unknown, this often requires one to think outside the box. Most importantly, work hard, persevere and be confident in your abilities. Science is a field historically dominated by men, however, this speaks to the cultural exclusion of women rather than a lack in our abilities. This is a reality which is slowly shifting, and my advice would be to play to your strengths as women, our attention to detail and nurturing, collaborative mindsets are essential to science. On a similar note, it may look like the scientific field is dominated by international countries who have bigger and better resources, however, this is not the case. South Africa is a major contributor to the scientific domain, we have excellent scientists doing exceptional science with the resources to do so. Take advantage of the opportunities our country has to offer.”
Research Summary
Malaria is a severe parasitic disease responsible for over 600 000 deaths in 2020. Of these, 96% occurred in sub-Saharan Africa.
Unfortunately, pregnant women and children are most at risk with regards to this disease, and the global incidence rate of malaria is once again on the rise.1 This, alongside the ever-increasing parasite resistance to currently used antimalarials, is why continued research of the disease and development of structurally and mechanistically novel treatments is crucial.
This research project utilizes a multidisciplinary approach to identify new inhibitors of the P. falciparum parasite’s cGMP-dependent protein kinase. As a preliminary filtration step, the investigation uses a novel computational tool developed in our research group - the Antiplasmodial Chemical Space (APCS) map - to identify a subset of compounds from large online databases that fall in regions of PfPKG inhibitor enrichment.2,3 The ability of these compounds to inhibit this target, as predicted by the APCS map, is refined using Random Forest machine learning algorithms trained on various descriptor sets. Subsequently model validation will be examined through biological testing of a subset of predicted PfPKG inhibitors. Any hits identified will be subject to a lead optimization phase in an attempt to produce analogs with improved potency.