Antibody Engineering

Usually, the optimization of the initial antibody candidates is necessary for the development of therapeutic antibodies. The Yumab platform provides two in-vitro evolution technologies for the optimization of the antibody’s affinity, stability, specificity or selectivity:

  • in-vitro evolution by YUlight shuffling
  • in-vitro evolution by mutagenesis

Additionally, in-silico analysis can be applied to identify and optimize antibodies with the best developability score.

  • in-silico analysis and optimization

in-vitro evolution by YUlight shuffling:

Goal: Optimization of individual antibodies with promising binding characteristics with respect to affinity, specificity, selectivity or stability.

Principal: For most antibodies, the VH domain is predominantly responsible for the antigen binding. However, the VL domain stabilizes the interaction, and therefore a perfect VH:VL pairing is most often needed to achieve the best antibody binding and overall biochemical properties.

Technology: The VH domain of antibody Hits (or small pools thereof) are isolated and shuffled with the full YUMAB library VL repertoire. The new VH:VL combinations are used to generate a new antibody sublibrary (>108 additional VL 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 based on fully human, nature-derived sequences. Major class-switches can occur.
Disadvantage: If the early antibody lead candidate contains a potent VH:VL combination, VL germline switches will be limited. In these cases, the VL germline will remain identical and differences are mainly restricted to the LCDR3.
Application: Improvement of tool antibodies and potential therapeutic candidates (internally generated or external antibodies).

in-vitro evolution by mutagenesis

Goal: Optimization of individual antibody Hits that show promising binding characteristics with regards to affinity, specificity, selectivity or stability.

Principal: In the last years, it was more and more recognized that the antibody binding is not necessarily determined solely by the CDRs but also the framework regions. Mutations in the frameworks may lead to a shifted CDR orientation which impacts the 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 like 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).

Contact

YUMAB GMBH
Science Campus Braunschweig-Süd
Inhoffenstr. 7
38124 Braunschweig – Germany

Email: info@yumab.com
Phone: +49 531 481170-0