(205g) Engineering Ligand Biophysics to Enhance Tumor Targeting | AIChE

(205g) Engineering Ligand Biophysics to Enhance Tumor Targeting

Authors 

Hackel, B. J. - Presenter, University of Minnesota
Case, B., University of Minnesota



Proteins and small molecules can be engineered for specific, high affinity binding for applications in molecular targeting for tumor therapy and diagnostics. Yet, target affinity is only one element of delivery; biophysical parameters also play a significant role in dictating tumor uptake and off-target background. Molecular charge and hydrophilicity impact vascular permeability, plasma clearance kinetics, tumor retention, and physiological retention in multiple organs (especially kidneys and liver). Yet, we lack both fundamental understanding and systematic empirical data needed to empower rational engineering of charge and hydrophilicity in delivery molecules for specific applications.

We have demonstrated select cases of charge reduction as a means of reducing renal retention. Yet, this approach is not uniformly robust. We have now produced a systematic series of protein ligands with a range of net charge, total charge, and charge distributions. Conjugation of these ligands with positron emitters (64Cu) via metal chelators enables dynamic positron emission tomography and excised tissue gamma counting for both rapid kinetics upon injection as well as multi-day longitudinal monitoring of biodistribution with whole-body information at sub-organ (1 mm) resolution. We will present data on tumor targeting and off-target background, especially renal retention and plasma clearance kinetics. The results are nuanced but indicate benefit from charge removal. Yet, this removal is often detrimental to solubility, stability, and recombinant production. Thus, we are also studying the ability to efficiently engineer charge using data from structural studies, phylogenetic sequence analysis, and high throughput screening. We have performed yeast surface display stability studies and high throughput production assays. Ongoing studies suggest that minimal experimental efforts can yield significant predictive value of mutational tolerance.