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Protein structure prediction is the process of determining the three-dimensional structure of a protein based on its amino acid sequence. It is an important field in computational biology and is used to understand how proteins work and potentially modify their function. Current techniques for protein structure determination include X-ray crystallography and nuclear magnetic resonance (NMR). However, advancements in artificial intelligence, such as AlphaFold, have greatly improved the accuracy and speed of protein structure prediction. AlphaFold's AI system provides open access to a database of over 200 million protein structure predictions, which aids in accelerating scientific research. Protein structure prediction experiments, like CASP, are conducted to assess the state of the art in modeling protein structures. Participants are given target protein sequences and develop corresponding three-dimensional structure models. Overall, protein structure prediction plays a vital role in expanding our understanding of proteins and their functions.
