DeepFold is a deep-learning based method for ab initio protein structure prediction. Starting from a query sequence, it first collects multiple sequence alignments (MSAs) from whole- and meta-genome sequence libraries. Spatial restraints (contact/distance maps and inter-residue orientations) are then predicted by DeepPotential, a convolutional residual neural network model. Finally, full-length structural models are constructed using an L-BFGS folding algorithm.
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