In search of new medicinal substances

The leader of the project at UPWr is Dr Paulina Strugała-Danak. The project is called 'Application of artificial intelligence in the search for new therapeutic substances of natural origin with mechanisms of action aimed at reducing the concentration of free radicals in the body'.

The main project, led by Maciej Spiegel, concerns the process of organismal ageing – there are several theories attempting to explain the course of this phenomenon and thus identify factors responsible for its initiation and progression, which could constitute targets for potential drugs. 

Probably the best recognised theory is the programmed clock theory, according to which ageing is deliberately caused by evolved biological mechanisms in order to gain an evolutionary advantage. This would imply that there is no way to inhibit this process. At the same time, however, many scientific reports suggest that functional cellular ageing (senescence) is caused by the degradation of the biological structures that make up the cytosol and cell nucleus due to their excessive oxidation. 

This lays the foundations for the so-called error theory or, more precisely, the radical hypothesis of ageing, according to which free radicals are responsible for the accumulation of this damage and the result is a disruption in their function manifesting itself in the development of various chronic, severe, and often fatal ailments such as cancer or neurodegenerative changes. 

Although cells are able to protect themselves to some extent against oxidants thanks to an intracellular environment composed of reducing compounds, this mechanism is increasingly ineffective in today's world, where excessive exposure to ultraviolet radiation, smog and air pollution are the main sources of significantly elevated free radical concentrations in the body.

Traditional Chinese medicine, Ayurveda and shamanism used plants for therapeutic purposes, and knowledge of their use was passed down from generation to generation. However, until their chemical composition was studied, these mythical healing powers remained unknown. Among the newly discovered substances, one group aroused particular interest among scientists because of their activity similar to biological antioxidants - polyphenols. Since then, numerous studies have confirmed and continue to confirm their health-promoting effects. The aim of the project by the Medical University  and Wrocław University of Environmental and Life Sciences is to develop machine learning models that can support the design of new drugs with enhanced antioxidant potential on a matrix of well-recognised phytochemicals.

The scope of the research includes the analysis of two types of activity – direct radical scavenging and inhibition of radical-generating enzymes in vivo. In parallel to the laboratory tests conducted to quantify the process, studies will be performed to investigate the molecular mechanisms underlying the observed phenomena. To pinpoint the structural elements modulating these activities, the data obtained will be used to obtain quantitative models of structure-activity relationships. 

The ultimate goal of the project is to make it even more useful by transforming the models into machine learning algorithms and placing them on a publicly accessible server – as a result, other scientists will be able to directly influence their reliability by uploading their experimental results, which, when processed by the server, will adjust the models' parameters and improve their accuracy. Another important and expected benefit is that they can be used to reduce the cost and time spent on research by discarding inactive compounds at the outset.

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