AI's Potential and Limitations in Protein Design and Bioinformatics

Scientists at Skoltech Bio tested AlphaFold, the AI program that solved the central problem of structural bioinformatics, on another challenge in the field and found that the program's predictions contradicted experimental findings, suggesting that the AI is not a cure-all for structural bioinformatics. The findings refute claims by some AlphaFold enthusiasts that the program had mastered the ultimate protein physics and should work beyond the task it was designed for. The study highlights that even in the wake of AlphaFold, scientists in the field have one or two things to do, including predicting the structures of complexes made up of proteins and either small molecules or DNA or RNA, determining how mutations affect the binding energy of proteins with other molecules, and designing proteins with amino acid sequences that endow them with desired properties.
- The Limits of AlphaFold: High Schoolers Reveal AI's Flaws in Bioinformatics Challenge SciTechDaily
- This AI Can Design Complex Proteins Perfectly Tailored to Our Needs Singularity Hub
- Efficient evolution of human antibodies from general protein language models Nature.com
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