15 October 2025
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Story Martinette Brits
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Photo Supplied
Dr Abdul Rashid Issahaku from the UFS Department of Chemistry received the Early Career Researcher Best Poster Award at the Fragment-Based Lead Discovery Conference in Cambridge, United Kingdom.
The conference is widely recognised as one of the foremost international forums for advancing fragment-based approaches to drug discovery, bringing together experts from academia, industry, and major pharmaceutical companies.
Advancing drug discovery through computational innovation
Dr Issahaku’s award-winning research focuses on using computational and structure-guided approaches to identify promising lead compounds from natural products. “The award affirms that my work resonates with experts in the field and has real potential to advance fragment-based drug discovery,” he says. “It provides a platform for visibility and collaboration and motivates me to continue exploring innovative computational strategies that push the boundaries of what’s possible in this field.”
At the conference, which took place from 21 to 24 September 2025, Dr Issahaku presented research on developing GABA mimetics from natural products by investigating the binding mechanisms of gamma-aminobutyric acid (GABA) – a key calming neurochemical in the brain – and muscimol, a mushroom-derived compound successfully isolated and synthesised by the Department of Chemistry at the UFS. His approach aims to identify and optimise natural-product-based compounds with potential therapeutic applications in modulating GABAergic activity.
He explains that the Fragment-Based Lead Discovery Conference is a premier multidisciplinary platform that brings together experts in chemistry, biochemistry, and related fields. “It is widely recognised as the foremost forum for advancing fragment-based approaches to drug discovery, making it an ideal venue to present my work, gain feedback from top researchers, and explore potential collaborations,” he says.
From molecular modelling to global impact
His research integrates advanced computational tools such as molecular dynamics, per-residue energy-based pharmacophore modelling, and multiparameter hit optimisation to refine the process of lead identification. This integration allows for a more rational, targeted framework that reduces ligand promiscuity and accelerates the discovery of promising drug candidates.
“The broader impact of my work lies in accelerating the discovery of safe and effective medicines from natural sources,” he explains. “Natural products remain an underexplored source of medicinal agents, and by applying computational strategies, we can make the discovery process more efficient and precise – helping to address global challenges such as the slow development of new treatments for neurological disorders.”
Dr Issahaku credits the University of the Free State environment and the mentorship of Prof Hendrik Visser and Prof Anke Wilhelm, which provided the support and conditions under which his research could flourish. “Like a seed that is viable only under the right conditions, I have thrived thanks to their guidance, access to experienced researchers, and opportunities for interdisciplinary collaboration.”
Looking ahead, he plans to further advance computational and structure-guided strategies for identifying and optimising natural-product-based drug candidates. “Building on this achievement, I hope to integrate emerging technologies such as AI-driven screening and contribute to more efficient and precise drug discovery pipelines that address pressing global health challenges,” he says.