ArticleMethods in molecular biology (Clifton, N.J.)2023
SUMO: In Silico Sequence Assessment Using Multiple Optimization Parameters.
Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Review
- Article
- On the humanization of VHHs: Prospective case studies, experimental and computational characterization of structural determinants for functionality.Protein science : a publication of the Protein Society · 2024Article
- Biophysical cartography of the native and human-engineered antibody landscapes quantifies the plasticity of antibody developability.Communications biology · 2024Article
- NKp46-specific single domain antibodies enable facile engineering of various potent NK cell engager formats.Protein science : a publication of the Protein Society · 2023Article
- AI/ML combined with next-generation sequencing of VHH immune repertoires enables the rapid identification ofFrontiers in molecular biosciences · 2023Article
- Article
- Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To select the most promising screening hits from antibody and VHH display campaigns for subsequent in-depth profiling and optimization, it is highly desirable to assess and select sequences on properties beyond only their binding signals from the sorting process. In addition, developability risk criteria, sequence diversity, and the anticipated complexity for sequence optimization are relevant attributes for hit selection and optimization. Here, we describe an approach for the in silico developability assessment of antibody and VHH sequences. This method not only allows for ranking and filtering multiple sequences with regard to their predicted developability properties and diversity, but also visualizes relevant sequence and structural features of potentially problematic regions and thereby provides rationales and starting points for multi-parameter sequence optimization.
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Registered trials
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