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MIT Researchers Achieve Breakthrough in Protein Folding

Scientists at MIT have developed a new machine learning algorithm that can predict protein structures with 95% accuracy.

The research, published in Nature, builds on previous work in computational biology and represents a significant breakthrough.

Understanding protein folding has been one of biology's grand challenges for decades.

Proteins are the workhorses of cells, and their 3D shapes determine their functions.

The new algorithm uses deep learning to predict these shapes from amino acid sequences.

This could revolutionize drug discovery by allowing researchers to design molecules that target specific proteins.

Traditional methods for determining protein structures can take months or years.

New ML approach predicts protein structures at 95% accuracy, could speed up drug discovery. (1) Published in Nature, builds on computational biology (2) Major breakthrough in molecular interaction modeling (3) Drug development timelines could shrink significantly

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