In-vitro evolution by mutagenesis
Goal: Optimization of individual antibody hits that show promising binding characteristics with regards to affinity, specificity, selectivity or stability.
Principle: In the last years, it was more and more recognized that antibody binding is not necessarily determined solely by the CDRs but also by the framework regions. Mutations in the frameworks may lead to a shifted CDR orientation which impacts antibody binding. Furthermore, framework mutations may lead to a better binding by decreasing the entropy. Similarly, mutations in the framework regions also affect the antibody’s overall biochemical properties, such as stability, charge and hydrophobicity.
Technology: The VH:VL domain of antibody hits (or small pools thereof) is isolated and randomly mutated by error-prone PCR. Typically, a low (0-2 aa substitutions), medium (3-5 aa substitutions) and high mutation rate (5-7 aa substitutions) is targeted. The mutated VH:VL combinations are used to generate a new antibody sublibrary (>108 additional diversity) with predefined antigen specificity. Compared to the initial hit discovery, this library can be used for in-vitro selection under more stringent conditions to identify antibodies with improved characteristics.
Advantage: The introduced diversity is equally distributed and occurs in both, CDR and framework regions.
Disadvantage: The introduced mutations are not nature-derived and may lead to immunogenic neoepitopes.
Application: Improvement of tool antibodies and potential therapeutic candidates (internally generated or external antibodies).
In-silico analysis and optimization
Goal: The in-silico analysis & optimization is recommended to identify and optimize the final lead candidates with the best developability score.
Principle: First, the antibody developability characteristics are modeled and compared to more than 200 late-stage and market approved antibodies. Then, unwanted patches or motifs are removed in the antibody sequence from the top candidates by using a proprietary in-silico sequence optimization tool. Afterwards, the ‘polished’ antibodies are produced and tested in the final format to confirm the functionality.
Application: Optimization of antibodies with therapeutic effect for cell line development and preclinical phases (internally generated or external antibodies).