Preparation of Conjugates for Affibody-Based PNA-Mediated Pretargeting

Dual-Modality PET-SPECT Image-Guided Pretargeting Delivery in HER2(+) Breast Cancer Models

Pretargeted drug delivery has been explored for decades as a promising approach in cancer therapy. An image-guided pretargeting strategy significantly enhances the intrinsic advantages of this approach since imaging the pretargeting step can be used for diagnostic purposes, while imaging of the drug delivery step can be utilized to evaluate drug distribution and assess therapeutic response. A trastuzumab (Tz)-based HER2 pretargeting component (Tz-TCO-[89Zr-DFO]) was developed by conjugating with trans-cyclooctene (TCO) bioorthogonal click chemistry functional groups and deferoxamine (DFO) to enable radiolabeling with a 89Zr PET tracer. The drug delivery component (HSA-DM1-Tt-[99mTc-HyNic]) was developed by conjugating human serum albumin (HSA) with mertansine (DM1), tetrazine (Tt) functional groups, and a HyNic chelator and radiolabeling with 99mTc. For ex vivo biodistribution studies, pretargeting and delivery components (without drug) were administered subsequently to mice bearing human HER2(+) breast cancer xenografts, and a high tumor uptake of Tz-TCO-[89Zr-DFO] (26.4% ID/g) and HSA-Tt-[99mTc-HyNic] (4.6% ID/g) was detected at 24 h postinjection. In vivo treatment studies were performed in the same HER2(+) breast cancer model using PET-SPECT image guidance. The increased tumor uptake of the pretargeting and drug delivery components was detected by PET-CT and SPECT-CT, respectively. The study showed a significant 92% reduction of the relative tumor volume in treated mice (RTV = 0.08 in 26 days), compared to the untreated control mice (RTV = 1.78 in 11 days) and to mice treated with only HSA-DM1-Tt-[99mTc-HyNic] (RTV = 1.88 in 16 days). Multimodality PET-SPECT image-guided and pretargeted drug delivery can be utilized to maximize efficacy, predict therapeutic response, and minimize systemic toxicity.

Genetic Algorithms Applied to Thermodynamic Rational Design of Mimetic Antibodies Based on the GB1 Domain of Streptococcal Protein G: An Atomistic Simulation Study

The development of mimetic antibodies (MA) capable of combining the high affinity and selectivity of antibodies with the small size of the peptides has enormous potential for applications in current biotechnology. In this work, we demonstrate that in silico MA design is possible through genetic algorithms (GA) developed from shell scripts capable of combining software commonly used for atomistic simulation. Our results demonstrate that, using the GB1 domain of the streptococcal G protein as a model, it is possible to optimize the molecular recognition capacity of a large MA population in a few generations. In the first case, GA was able to generate 10 MA with binding free energy (BFE) less than the vascular endothelial cell growth factor conjugated with the fms-type tyrosine kinase receptor. In the second case, it generated 13 MA with BFE less than that of the hepatitis C-E2 viral envelope conjugate with the antibody. Through the GA developed in this work, we demonstrate the use of a new protocol, capable of guiding experimental methods for the design of bioactive peptides that can assist in the development of new therapeutic molecules.

Efficient Sortase-Mediated Ligation Using a Common C-Terminal Fusion Tag

Sortase-mediated ligation is a powerful method for generating site-specifically modified proteins. However, this process is limited by the inherent reversibility of the ligation reaction. To address this, here we report the continued development and optimization of an experimentally facile strategy for blocking reaction reversibility. This approach, which we have termed metal-assisted sortase-mediated ligation (MA-SML), relies on the use of a solution additive (Ni2+) and a C-terminal tag (LPXTGGHH5) that is widely used for converting protein targets into sortase substrates. In a series of model systems utilizing a 1:1 molar ratio of sortase substrate and glycine amine nucleophile, we find that MA-SML consistently improves the extent of ligation. This enables the modification of proteins with fluorophores, PEG, and a bioorthogonal cyclooctyne moiety without the need to use precious reagents in excess. Overall, these results demonstrate the potential of MA-SML as a general strategy for improving reaction efficiency in a broad range of sortase-based protein engineering applications.