CR-I-TASSER: Assemble Protein Structures from Cryo-EM Density Maps using Deep Convolutional Neural Networks
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CR-I-TASSER is a hybrid method to integrate I-TASSER and cryo-EM density map for high-quality protein structure determination. Starting from density map, it first uses deep convolutional neural networks (CNNs) to predict C-alpha positions, which are used to improve threading templates by the sequence-independent template and C-alpha position superpositions. Next, the deep-learning boosted threading templates are reassembled by the I-TASSER based structure assembly simulations to generate full-length atomic models under the guidance of density map and template restraints. Large-scale benchmark tests showed a significant advantage of CR-I-TASSER over other de novo and refinement-based approaches in cryo-EM structure determination.

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Reference:
  • Xi Zhang, Biao Zhang, P. Lydia Freddolino, Yang Zhang. CR-I-TASSER: Assemble Protein Structures from Cryo-EM Density Maps using Deep Convolutional Neural Networks. Nature Methods, 19:195-204, 2022. [PDF] [Support Information]

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