• Corpus ID: 248665783

Learning Correlations between Internal Coordinates to improve 3D Cartesian Coordinates for Proteins

@inproceedings{Li2022LearningCB,
  title={Learning Correlations between Internal Coordinates to improve 3D Cartesian Coordinates for Proteins},
  author={Jie Li and Oufan Zhang and Seokyoung Lee and Ashley Namini and Ziqing Liu and Jo{\~a}o M. C. Teixeira and Julie Deborah Forman-Kay and Teresa Head-Gordon},
  year={2022}
}
Motivation . We consider a generic representation problem of internal coordinates (bond lengths, valence angles, and dihedral angles) and their transformation to 3-dimensional Cartesian coordinates of a biomolecule. Results . We show that the internal-to-Cartesian process relies on correctly predicting chem-ically subtle correlations among the internal coordinates themselves, and learning these correlations increases the fidelity of the Cartesian representation. We developed a machine learning… 
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