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Connecting the sequence dots: shedding light on the genesis of antibodies reported to be designed in silico.

Maximiliano VásquezEric KraulandLaura WalkerDane WittrupTillman Gerngross
Published in: mAbs (2019)
Two recent publications out of the same research laboratory report on structure-based in silico design of antibodies against viral targets without sequence disclosure. Cross-referencing the published data to patent databases, we established the sequence identity of said computationally designed antibodies. In both cases, the antibodies align with high sequence identity to previously reported antibodies of the same specificity. This clear underlying sequence relationship, which is far closer than the antibody templates reported to seed the computational design, suggests an alternative origin of the computationally designed antibodies. The lack of both reproducible computational algorithms and of output sequences in the initial publications obscures the relationship to previously reported antibodies, and sows doubt as to the genesis narrative described therein.
Keyphrases
  • machine learning
  • sars cov
  • amino acid
  • big data
  • molecular docking
  • deep learning
  • artificial intelligence
  • molecular dynamics simulations
  • high resolution
  • molecularly imprinted