Building on the structural evaluation and hot spot characterization, Zymeworks’ protein engineers are able to use other components in the ZymeCAD™ platform to extensively model numerous single point and multisite mutations at specific positions of interest. Apart from remodeling and refining the structure with the altered side chain compositions and coupled backbone conformational changes, extensive scoring techniques are employed to evaluate the stability and other functionally relevant characteristics of the protein. A limited number of the promising protein candidates are expressed and assayed using a variety of in vitro techniques such as chromatography, differential scanning calorimetry, surface plasmon resonance or cell based methods where appropriate. This data is used to drive subsequent iterative optimization cycles of the lead candidates.
Zymeworks' protein engineering process uses a unique two-expert approach. Proprietary biophysical insight into the protein system and targets is generated by the ZymeCAD™ platform. In-house protein engineers then use the detailed insight gained from the ZymeCAD™ platform to make knowledge-based decisions regarding structural modifications. Zymeworks’ rigorous analysis of structural data coupled with ZymeCAD™ based computational modeling of protein dynamics, energetics and thermodynamics effectively expands the scope of traditional structure guided protein optimization. The successes in the development of the Azymetric™, AlbuCORE™, and EFECT™ platforms as well as critical contributions in the optimization of pipeline candidates points to the strength and the invaluable nature of Zymeworks' protein engineering process.
The protein engineering process initially involves a thorough understanding of the biological system of interest and involves an extensive system-related structure and data gathering effort that provides the groundwork for knowledge-driven model building and refinement. Different components in the ZymeCAD™ platform are applied to the resultant molecular model to calibrate a variety of biophysical characteristics compared to known experimental data about the system. The technique iteratively refines the quality of structural models using a tight integration of data and simulation-driven insights, providing a greater degree of realism for rational protein engineering.
For the protein system of interest, detailed structure, dynamics and energetic characterization help to profile critical hotspot positions in the protein where modifications are well tolerated for achieving the target activity of interest while maintaining the biophysical properties of the protein system. The insights generated provide invaluable information on proximal and distal effects of mutations on protein characteristics and enable the optimization of site-specific characteristics as well as global protein metrics.