Deep learning approaches for conformational exibility and switching properties in protein design

HIGHLIGHTS

  • who: August et al. from the Toulouse Biotechnology Institute (CNRS, INRAE, INSA), France have published the research work: Deep learning approaches for conformational exibility and switching properties in protein design, in the Journal: (JOURNAL)
  • future: Most conformational state-based design studies continue to rely on re-engineering existing proteins known to occupy multiple states (Alberstein et_al 2022).

SUMMARY

    Despite the current limitations, the improvements gained by moving to DL-based prediction has motivated a similar change within the protein design community, with novel methods distancing themselves from the traditional design approaches . . .

     

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