Abstract
Abstract AlphaFold2 is a deep-learning algorithm used to predict the tertiary structures of proteins based on their amino acid sequences. We examined whether AlphaFold2 could predict the heme-binding pocket by comparing the structures of heme proteins from the Protein Data Bank and AlphaFold Protein Structure Database. In most cases, the structures showed only minor differences. We also investigated the impact of heme binding on the protein conformation, showing the pocket rigidity. Therefore, AlphaFold2 can predict the structure of the heme-binding pocket.
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