ArticleNature communications2019
Auto-encoding NMR chemical shifts from their native vector space to a residue-level biophysical index.
Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Data-driven probabilistic definition of the low energy conformational states of protein residues.NAR genomics and bioinformatics · 2024Article
- Investigating and Quantifying Molecular Complexity Using Assembly Theory and Spectroscopy.ACS central science · 2024Article
- PyUUL provides an interface between biological structures and deep learning algorithms.Nature communications · 2022Article
- b2bTools: online predictions for protein biophysical features and their conservation.Nucleic acids research · 2021Article
- ShiftCrypt: a web server to understand and biophysically align proteins through their NMR chemical shift values.Nucleic acids research · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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 most common structural features. In addition, it can be used to identify hidden similarities between diverse proteins and peptides, and differences between the same protein in two different binding states.
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