Automated Protein Secondary Structure Assignment from Cα Positions Using Neural Networks.

ABSTRACT: The assignment of secondary structure elements in protein conformations is necessary to interpret a protein model that has been established by computational methods. The process essentially involves labeling the amino acid residues with H (Helix), E (Strand), or C (Coil, also known as Loop). When particular atoms are absent from an input protein structure, the procedure becomes more complicated, especially when only the alpha carbon locations are known. Various techniques have been tested and applied to this problem during the last forty years. The application of machine learning techniques is the most recent trend. This contribution presents the HECA classifier, which uses neural networks to assign protein secondary structure types. The technique exclusively employs Cα coordinates. The Ke

SUBMITTER: Saqib MN 

PROVIDER: S-EPMC9220970 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature