The AlphaFold educational summit provides insights into advancing global equity in computational structural biology

AlphaFold is a state-of-the-art protein structure prediction resource that offers immense potential for accelerating scientific discovery. Realising this potential, however, requires equitable access to technology, resources and expertise. To address this need, the AlphaFold Education Summit, held at the Wellcome Genome Campus in Hinxton, Cambridge, UK, convened researchers and trainers from 14 countries, with a focus on low- and middle-income countries (LMICs). Participants, selected for their AlphaFold expertise and training experience, shared crucial insights into dissemination strategies. Over a four-day train-the-trainer programme, participants advanced their AlphaFold knowledge, formulated adaptable training models, and collectively committed to facilitating the widespread application of AlphaFold in scientific exploration. This report details the summit’s objectives, key discussions, and outcomes, charting a course towards a sustainable and inclusive global AlphaFold community. Major barriers identified include limited computational infrastructure, inconsistent internet connectivity, and a shortage of skilled trainers in under-resourced regions. The summit underscored the importance of developing adaptable, high-quality training materials, implementing robust Train-the-Trainer (TtT) programmes, and fostering mentorship and community networks. Key strategic recommendations include collaborative resource sharing, sustainable funding models, integration of AlphaFold training into academic curricula, and establishing a global-south community with regional hubs to mitigate geopolitical and logistical challenges. The summit outcomes emphasise the necessity of a coordinated, community-driven approach to democratise access to AI-powered structural biology tools. This approach focuses on inclusivity, sustainability, and long-term capacity building, aiming to empower researchers globally, accelerate scientific discovery, and ensure the benefits of new AI methods, like AlphaFold, are accessible across diverse scientific and geographical contexts.