Development of a structure-based computational simulation to optimize the blocking efficacy of pro-antibodies.

The on-target toxicity of monoclonal antibodies (Abs) is mainly due to the fact that Abs cannot distinguish target antigens (Ags) expressed in disease regions from those in normal tissues during systemic administration. In order to overcome this issue, we "copied" an autologous Ab hinge as an "Ab lock" and "pasted" it on the binding site of the Ab by connecting a protease substrate and linker in between to generate a pro-Ab, which can be specifically activated in the disease region to enhance Ab selectivity and reduce side effects. Previously, we reported that 70% of pro-Abs can achieve more than 100-fold blocking ability compared to the parental Abs. However, 30% of pro-Abs do not have such efficient blocking ability. This is because the same Ab lock linker cannot be applied to every Ab due to the differences in the complementarity-determining region (CDR) loops. Here we designed a method which uses structure-based computational simulation (MSCS) to optimize the blocking ability of the Ab lock for all Ab drugs. MSCS can precisely adjust the amino acid composition of the linker between the Ab lock and Ab drug with the assistance of molecular simulation. We selected αPD-1, αIL-1ß, αCTLA-4 and αTNFα Ab as models and attached the Ab lock with various linkers (L1 to L7) to form pro-Abs by MSCS, respectively. The resulting cover rates of the Ab lock with various linkers compared to the Ab drug were in the range 28.33-42.33%. The recombinant pro-Abs were generated by MSCS prediction in order to verify the application of molecular simulation for pro-Ab development. The binding kinetics effective concentrations (EC-50) for αPD-1 (200-250-fold), αIL-1ß (152-186-fold), αCTLA-4 (68-150-fold) and αTNFα Ab (20-123-fold) were presented as the blocking ability of pro-Ab compared to the Ab drug. Further, there was a positive correlation between cover rate and blocking ability of all pro-Ab candidates. The results suggested that MSCS was able to predict the Ab lock linker most suitable for application to αPD-1, αIL-1ß, αCTLA-4 and αTNFα Ab to form pro-Abs efficiently. The success of MSCS in optimizing the pro-Ab can aid the development of next-generation pro-Ab drugs to significantly improve Ab-based therapies and thus patients' quality of life.

Correction: Development of a structure-based computational simulation to optimize the blocking efficacy of pro-antibodies.

[This corrects the article DOI: 10.1039/D1SC01748A.].

Enhancement of tumor tropism of mPEGylated nanoparticles by anti-mPEG bispecific antibody for ovarian cancer therapy.

Ovarian cancer is highly metastatic, with a high frequency of relapse, and is the most fatal gynecologic malignancy in women worldwide. It is important to elevate the drug susceptibility and cytotoxicity of ovarian cancer cells, thereby eliminating resident cancer cells for more effective therapeutic efficacy. Here, we developed a bispecific antibody (BsAb; mPEG × HER2) that can easily provide HER2+ tumor tropism to mPEGylated liposomal doxorubicin (PLD) and further increase the drug accumulation in cancer cells via receptor-mediated endocytosis, and improve the cytotoxicity and therapeutic efficacy of HER2+ ovarian tumors. The mPEG × HER2 can simultaneously bind to mPEG molecules on the surface of PLD and HER2 antigen on the surface of ovarian cancer cells. Simply mixing the mPEG × HER2 with PLD was able to confer HER2 specificity of PLD to HER2+ ovarian cancer cells and efficiently trigger endocytosis and enhance cytotoxicity by 5.4-fold as compared to non-targeted PLD. mPEG × HER2-modified PLD was able to significantly increase the targeting and accumulation of HER2+ ovarian tumor by 220% as compared with non-targeted PLD. It could also significantly improve the anti-tumor activity of PLD (P < 0.05) with minimal obvious toxicity in a tumor-bearing mouse model. We believe that the mPEG × HER2 can significantly improve the therapeutic efficacy, potentially reduce the relapse freqency and thereby achieve good prognosis in ovarian cancer patients.

Double attack strategy for leukemia using a pre-targeting bispecific antibody (CD20 Ab-mPEG scFv) and actively attracting PEGylated liposomal doxorubicin to enhance anti-tumor activity.

BACKGROUND: Tumor-targeted nanoparticles hold great promise as new tools for therapy of liquid cancers. Furthermore, the therapeutic efficacy of nanoparticles can be improved by enhancing the cancer cellular internalization. METHODS: In this study, we developed a humanized bispecific antibody (BsAbs: CD20 Ab-mPEG scFv) which retains the clinical anti-CD20 whole antibody (Ofatumumab) and is fused with an anti-mPEG single chain antibody (scFv) that can target the systemic liquid tumor cells. This combination achieves the therapeutic function and simultaneously "grabs" Lipo-Dox® (PEGylated liposomal doxorubicin, PLD) to enhance the cellular internalization and anticancer activity of PLD. RESULTS: We successfully constructed the CD20 Ab-mPEG scFv and proved that CD20 Ab-mPEG scFv can target CD20-expressing Raji cells and simultaneously grab PEGylated liposomal DiD increasing the internalization ability up to 60% in 24 h. We further showed that the combination of CD20 Ab-mPEG scFv and PLD successfully led to a ninefold increase in tumor cytotoxicity (LC50: 0.38 nM) compared to the CD20 Ab-DNS scFv and PLD (lC50: 3.45 nM) in vitro. Importantly, a combination of CD20 Ab-mPEG scFv and PLD had greater anti-liquid tumor efficacy (P = 0.0005) in Raji-bearing mice than CD20 Ab-DNS scFv and PLD. CONCLUSION: Our results indicate that this "double-attack" strategy using CD20 Ab-mPEG scFv and PLD can retain the tumor targeting (first attack) and confer PLD tumor-selectivity (second attack) to enhance PLD internalization and improve therapeutic efficacy in liquid tumors.

Humanized bispecific antibody (mPEG × HER2) rapidly confers PEGylated nanoparticles tumor specificity for multimodality imaging in breast cancer.

BACKGROUND: Developing a universal strategy to improve the specificity and sensitivity of PEGylated nanoaparticles (PEG-NPs) for assisting in the diagnosis of tumors is important in multimodality imaging. Here, we developed the anti-methoxypolyethylene glycol (mPEG) bispecific antibody (BsAb; mPEG × HER2), which has dual specificity for mPEG and human epidermal growth factor receptor 2 (HER2), with a diverse array of PEG-NPs to confer nanoparticles with HER2 specificity and stronger intensity. RESULT: We used a one-step formulation to rapidly modify the nanoprobes with mPEG × HER2 and optimized the modified ratio of BsAbs on several PEG-NPs (Lipo-DiR, SPIO, Qdot and AuNP). The αHER2/PEG-NPs could specifically target MCF7/HER2 cells (HER2++) but not MCF7/neo1 cells (HER2+/-). The αHER2/Lipo-DiR and αHER2/SPIO could enhance the sensitivity of untargeted PEG-NPs on MCF7/HER2 (HER2++). In in vivo imaging, αHER2/Lipo-DiR and αHER2/SPIO increased the specific targeting and enhanced PEG-NPs accumulation at 175% and 187% on 24 h, respectively, in HER2-overexpressing tumors. CONCLUSION: mPEG × HER2, therefore, provided a simple one-step formulation to confer HER2-specific targeting and enhanced sensitivity and contrast intensity on HER2 positive tumors for multimodality imaging.