AUTHOR=Arras Paul , Yoo Han Byul , Pekar Lukas , Clarke Thomas , Friedrich Lukas , Schröter Christian , Schanz Jennifer , Tonillo Jason , Siegmund Vanessa , Doerner Achim , Krah Simon , Guarnera Enrico , Zielonka Stefan , Evers Andreas
TITLE=AI/ML combined with next-generation sequencing of VHH immune repertoires enables the rapid identification of de novo humanized and sequence-optimized single domain antibodies: a prospective case study
JOURNAL=Frontiers in Molecular Biosciences
VOLUME=Volume 10 - 2023
YEAR=2023
URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2023.1249247
DOI=10.3389/fmolb.2023.1249247
ISSN=2296-889X
ABSTRACT=Introduction: In this study, we demonstrate the feasibility of yeast surface display (YSD) and nextgeneration sequencing (NGS) in combination with artificial intelligence and machine learning methods (AI/ML) for the identification of de novo humanized single domain antibodies (sdAbs) with favorable early developability profiles.
Methods: The display library was derived from a novel approach, in which VHH-based CDR3 regions obtained from a llama (Lama glama), immunized against NKp46, were grafted onto a humanized VHH backbone library that was diversified in CDR1 and CDR2. Following NGS analysis of sequence pools from two rounds of fluorescence-activated cell sorting we focused on four sequence clusters based on NGS frequency and enrichment analysis as well as in silico developability assessment. For each cluster, long short-term memory (LSTM) based deep generative models were trained and used for the in silico sampling of new sequences. Sequences were subjected to sequence- and structure-based in silico developability assessment to select a set of less than 10 sequences per cluster for production.
Results: As demonstrated by binding kinetics and early developability assessment, this procedure represents a general strategy for the rapid and efficient design of potent and automatically humanized sdAb hits from screening selections with favorable early developability profiles.