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• W3022674773 startingPage "117793222091524" @default.
• W3022674773 abstract "Phage display is a powerful technique to select high-affinity antibodies for different purposes, including biopharmaceuticals. Next-generation sequencing (NGS) presented itself as a robust solution, making it possible to assess billions of sequences of the variable domains from selected sublibraries. Handling this process, a central difficulty is to find the selected clones. Here, we present the AutomaTed Tool For Immunoglobulin Analysis (ATTILA), a new tool to analyze and find the enriched variable domains throughout a biopanning experiment. The ATTILA is a workflow that combines publicly available tools and in-house programs and scripts to find the fold-change frequency of deeply sequenced amplicons generated from selected VH and VL domains. We analyzed the same human Fab library NGS data using ATTILA in 5 different experiments, as well as on 2 biopanning experiments regarding performance, accuracy, and output. These analyses proved to be suitable to assess library variability and to list the more enriched variable domains, as ATTILA provides a report with the amino acid sequence of each identified domain, along with its complementarity-determining regions (CDRs), germline classification, and fold change. Finally, the methods employed here demonstrated a suitable manner to combine amplicon generation and NGS data analysis to discover new monoclonal antibodies (mAbs)." @default.
• W3022674773 created "2020-05-13" @default.
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• W3022674773 date "2020-01-01" @default.
• W3022674773 modified "2023-10-01" @default.
• W3022674773 title "Discovering Selected Antibodies From Deep-Sequenced Phage-Display Antibody Library Using ATTILA" @default.
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• W3022674773 doi "https://doi.org/10.1177/1177932220915240" @default.
• W3022674773 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7218273" @default.
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