• Chemistry, Medicine, Computer Science
  • Published in
    Journal of Computational…
    2014
  • DOI:10.1002/jcc.23718

Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network

@article{Lyons2014PredictingBC,
  title={Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network},
  author={James G. Lyons and Abdollah Dehzangi and Rhys Heffernan and Alok Sharma and Kuldip K. Paliwal and Abdul Sattar and Yaoqi Zhou and Yuedong Yang},
  journal={Journal of computational chemistry},
  year={2014},
  volume={35 28},
  pages={
          2040-6
        }
}
Because a nearly constant distance between two neighbouring Cα atoms, local backbone structure of proteins can be represented accurately by the angle between C(αi-1)-C(αi)-C(αi+1) (θ) and a dihedral angle rotated about the C(αi)-C(αi+1) bond (τ). θ and τ angles, as the representative of structural properties of three to four amino-acid residues, offer a description of backbone conformations that is complementary to φ and ψ angles (single residue) and secondary structures (>3 residues). Here, we… CONTINUE READING

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