Gregory Hannum

ORCID: 0000-0002-9291-7259
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Research Areas
  • Monoclonal and Polyclonal Antibodies Research
  • vaccines and immunoinformatics approaches
  • RNA and protein synthesis mechanisms
  • Advanced Biosensing Techniques and Applications
  • Protein purification and stability

Abstract Traditional antibody optimization approaches involve screening a small subset of the available sequence space, often resulting in drug candidates with suboptimal binding affinity, developability or immunogenicity. Based on two distinct antibodies, we demonstrate that deep contextual language models trained high-throughput affinity data can quantitatively predict unseen variants. These variants span K D range three orders magnitude over large mutational space. Our reveal strong...

10.1101/2022.08.16.504181 preprint EN bioRxiv (Cold Spring Harbor Laboratory) 2022-08-17

Abstract Increasing recombinant protein expression is of broad interest in industrial biotechnology, synthetic biology, and basic research. Codon optimization an important step heterologous gene that can have dramatic effects on level. Several codon strategies been developed to enhance expression, but these are largely based bulk usage highly frequent codons the host genome, produce unreliable results. Here, we develop deep contextual language models learn rules from natural coding sequences...

10.1101/2023.02.11.528149 preprint EN cc-by-nc-nd bioRxiv (Cold Spring Harbor Laboratory) 2023-02-12
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