How to Spend Your Oracle Budget: Practical Guidance for Protein Structure Prediction Models
Choosing the cheapest way to fix AI's protein-folding mistakes
Protein-prediction AI systems sometimes get the answer wrong, but checking their work costs money through lab experiments. Researchers tested four different strategies for spending a limited budget on these checks, and found that the best choice depends on how much you can afford to spend: one method wins at rock-bottom budgets, while others pull ahead as money increases.
Protein structure prediction is central to drug discovery and understanding disease, but current AI models are unreliable enough that researchers must experimentally validate their predictions. This work shows which verification strategies actually save money and time in practice, letting labs allocate scarce experimental resources more effectively rather than guessing which verification approach to use.