Mimicking the folding pathway to improve homology-free protein structure prediction

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Protein 3D Structure Computed from Evolutionary Sequence Variation (2011, background): “distance constraints between highly conserved residues is a valuable feature of the DI algorithm presented here, and, in contrast to other homology-free protocols, allows direct deduction of structural information about disulfide bonds and binding sites [24].”
3D Protein Structure Predicted from Sequence (2011, unknown): “to-‐structure problem remains unsolved, methods that use fragment libraries [20,21] or other strategies to search conformational space [22,23], followed by sophisticated energy optimization or molecular d”
Protein 8-class secondary structure prediction using conditional neural fields (2010, unknown): “[1,2) [2,3) [3,4) [4,5) [5,6) [6,7) [7,8) [8,9) [9,20) 0.”
Sixty-five years of the long march in protein secondary structure prediction: the final stretch? (2016, background): “However, how to take advantage of these predicted non-local contacts (or structures) for improving secondary structure prediction remains to be further explored [118, 154], perhaps in the context of coupling of secondary and tertiary structure prediction [13, 120, 155].”
Knowledge-based machine learning methods for macromolecular 3D structure prediction (2016, methodology): “This detailed description of protein SS is used in solving various protein structure problems (DeBartolo et al, 2009; Boden et al, 2006; Cheng and Baldi, 2007).”