STEM与日常科技·英语30篇（3）
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Protein Folding Prediction and Its Impact on Drug Discovery
蛋白质折叠预测及其对药物研发的影响
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Proteins fold into precise 3D shapes that determine how they interact with other molecules in our bodies.
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Misfolded proteins cause diseases like Alzheimer’s, cystic fibrosis, and some cancers.
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AI tools like AlphaFold now predict protein structures from amino acid sequences with atomic accuracy.
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These predictions let scientists model how potential drug molecules might bind to disease targets.
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Virtual screening replaces months of lab trials by simulating millions of chemical interactions digitally.
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Researchers use predicted structures to design small molecules that stabilize healthy folds or block harmful ones.
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Accurate folding models also help engineer enzymes for green chemistry and biodegradable plastics.
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Before AI, solving one protein structure could take years; now it takes minutes on modern hardware.
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This speed-up accelerates personalized medicine, especially for rare genetic disorders with unique mutations.
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Understanding folding isn’t just biology—it’s computational physics, chemistry, and therapeutic design combined.