Auto-encoding NMR chemical shifts from their native vector space to a residue-level biophysical index.

ABSTRACT: Chemical shifts (CS) are determined from NMR experiments and represent the resonance frequency of the spin of atoms in a magnetic field. They contain a mixture of information, encompassing the in-solution conformations a protein adopts, as well as the movements it performs. Due to their intrinsically multi-faceted nature, CS are difficult to interpret and visualize. Classical approaches for the analysis of CS aim to extract specific protein-related properties, thus discarding a large amount of information that cannot be directly linked to structural features of the protein. Here we propose an autoencoder-based method, called ShiftCrypt, that provides a way to analyze, compare and interpret CS in their native, multidimensional space. We show that ShiftCrypt conserves information about the m

SUBMITTER: Orlando G 

PROVIDER: S-EPMC6555786 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature