EAN 2023 | Challenges and promises of AI in protein folding and therapeutic interventions

Tiago Outeiro, PhD, University Medical Center Göttingen, Göttingen, Germany, discusses the key challenges faced in applying artificial intelligence (AI) to the study and prediction of protein folding. With limited experimental data on how all proteins fold, the understanding of basic rules exists but lacks insights into how different cellular and chemical environments influence protein structure. Therefore, acquiring more experimental data to enhance AI systems’ predictive abilities is an important next step. Furthermore, AI holds great potential for therapeutic interventions by providing information on the three-dimensional structures of proteins in both normal and pathological states associated with various diseases. By understanding protein structures, better strategies can be developed to impede protein aggregation, a common problem in many diseases. AI presents immense opportunities for healthcare professionals, paving the way for advancements in understanding protein folding and developing effective therapeutic interventions. This interview took place at the European Academy of Neurology (EAN) 2023 Congress in Budapest, Hungary.

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