Protein sequence-to-structure learning: Is this the end(-to-end revolution)?

Understand

The potential of deep learning has been recognized in the protein structure prediction community for some time, and became indisputable after CASP13.

• In CASP14, deep learning has boosted the field to unanticipated levels reaching near-experimental accuracy.
• This success comes from advances transferred from other machine learning areas, as well as methods specifically designed to deal with protein sequences and structures, and their abstractions.
• Novel emerging approaches include (i) geometric learning, i.e.