Abstract: Next-generation sequencing (NGS), phage display technology and high throughput capacities enables biologists in drug discovery to characterize antibodies (Abs) based on their HCDR3 sequences and further group them into families before moving to hit-to-lead stage of drug discovery and development. This enables diversification of Ab portfolio and insures back up options if Ab candidate fails. However, there was no method or software available in-house to support Ab discovery with capacities to apply biophysical rules to classify the sequences. Shiny app "Group My Abs" was developed to apply biophysical properties for Ab characterization to the NGS data. Several Multiple Sequence Alignment algorithms implemented in the app enable sequence comparability. A method was developed to evaluate differences between comparable sequences and subsequently classify sequences into families. The app provides custom-made and interactive data visualization, enables refined Ab classification in a mathematical manner, considerably increases efficiency and insures reproducibility. This all decreases bias and enables informative decision making during the hit-to-lead stage in biologics drug discovery.
Speaker: Volha Tryputsen
Title: Antibody Characterization Using Next Generation Sequencing made easier with Group My Abs shiny app
Abstract_Sanitzed: Next-generation sequencing (NGS), phage display technology and high throughput capacities enables biologists in drug discovery to characterize antibodies (Abs) based on their HCDR3 sequences and further group them into families before moving to hit-to-lead stage of drug discovery and development. This enables diversification of Ab portfolio and insures back up options if Ab candidate fails. However, there was no method or software available in-house to support Ab discovery with capacities to apply biophysical rules to classify the sequences. Shiny app "Group My Abs" was developed to apply biophysical properties for Ab characterization to the NGS data. Several Multiple Sequence Alignment algorithms implemented in the app enable sequence comparability. A method was developed to evaluate differences between comparable sequences and subsequently classify sequences into families. The app provides custom-made and interactive data visualization, enables refined Ab classification in a mathematical manner, considerably increases efficiency and insures reproducibility. This all decreases bias and enables informative decision making during the hit-to-lead stage in biologics drug discovery.