The rapid advancement of computational protein design, driven by artificial intelligence (AI), holds great promise for biotechnology, sustainability, and medicine. However, there are potential risks associated with this technology, including the creation of harmful biological agents. To address these concerns, it is crucial to establish repositories for collecting and storing synthetic gene sequence and synthesis data that can only be accessed in emergencies, in order to ensure the safe and secure progress of protein design.
Global challenges, such as global pathogens, neurodegenerative diseases, and ecosystem destruction, require innovative solutions. AI-accelerated protein design, utilizing machine learning-based methods, offers the ability to create biomolecules with diverse structures and functions, often without any similarity to known proteins. The June 29, 2022 approval of the COVID-19 vaccine, SKYCovione, generated through computational protein design, showcases the potential for groundbreaking innovations in AI drug development.
As the field continues to progress, it is crucial to consider the regulatory implications and potential impacts of AI regulations. While regulating AI may be complex, the specialized nature of AI tools for protein design offers a more straightforward path for risk mitigation. International conferences, such as the 2023 AI Safety Summit and the preceding gathering in Seattle, have focused on addressing these issues and emphasizing the importance of biosecurity controls, such as screening and logging all synthesized genetic sequences, to prevent the creation of harmful biomolecules.
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