enteropeptidase

Mucin-16 (MUC16) is a target for antibody-mediated immunotherapy in pancreatic ductal adenocarcinoma (PDAC) amongst other malignancies. The MUC16 specific monoclonal antibody AR9.6 has shown promise for PDAC immunotherapy and imaging. Here, we report the structural and biological characterization of the humanized AR9.6 antibody (huAR9.6). The structure of huAR9.6 was determined in complex with a MUC16 SEA (Sea urchin sperm, Enterokinase, Agrin) domain. Binding of huAR9.6 to recombinant, shed, and cell-surface MUC16 was characterized, and anti-PDAC activity was evaluated in vitro and in vivo. huAR9.6 bound a discontinuous, SEA domain epitope with an affinity of ~90 nM. Binding affinity depended on the specific SEA domain(s) present, and glycosylation enhanced affinity by 3-7-fold driven by favorable entropy and enthalpy and via distinct transition state thermodynamic pathways. Treatment with huAR9.6 reduced the in vitro growth, migration, invasion, and clonogenicity of MUC16-positive PDAC cells and patient-derived organoids (PDOs). HuAR9.6 blocked MUC16-mediated ErbB and AKT activation in PDAC cells, PDOs and patient-derived xenografts and induced antibody-dependent cellular cytotoxicity and complement-dependent cytotoxicity. More importantly, huAR9.6 treatment caused substantial PDAC regression in subcutaneous and orthotopic tumor models. The mechanism of action of huAR9.6 may depend on dense avid binding to homologous SEA domains on MUC16. The results of this study validate the translational therapeutic potential of huAR9.6 against MUC16-positive PDACs.

Despite recent advances in computational protein science, the dynamic behavior of proteins, which directly governs their biological activity, cannot be gleaned from sequence information alone. To overcome this challenge, we propose a framework that integrates the peptide sequence, protein structure, and protein dynamics descriptors into machine learning algorithms to enhance their predictive capabilities and achieve improved prediction of the protein variant function. The resulting machine learning pipeline integrates traditional sequence and structure information with molecular dynamics simulation data to predict the effects of multiple point mutations on the fold improvement of the activity of bovine enterokinase variants. This study highlights how the combination of structural and dynamic data can provide predictive insights into protein functionality and address protein engineering challenges in industrial contexts.

Activin A belongs to the transforming growth factor (TGF) family member, which exhibits a wide range of biological activities, including the regulation of cellular proliferation and differentiation and the promotion of neuronal survival. The isolation of AA from natural sources can only produce limited quantities of this bioactive protein. In this study, the whole gene of the precursor form of recombinant human activin A (rhAA) contains a signal peptide, and a pro-region and a mature region were cloned into an expression vector under the control of the rice α-amylase 3D (RAmy3D) promoter. To obtain the mature (active) form of rhAA, an enterokinase cleavage site was inserted between the pro-region and mature region of rhAA. The rice seed (Oryza sativa L. cv. Dongjin) was transformed with recombinant vectors by the Agrobacterium-mediated method, and the integration of the target gene into the plant genome was confirmed by genomic PCR. The transcript expression of rhAA in transgenic rice calli was confirmed by a Northern blot analysis of mRNA. The production of rhAA was verified by Western blot analysis and ELISA. The accumulation of secreted rhAA in the culture medium was purified by Ni²⁺-NTA. The mature form of AA was released from the precursor form of rhAA after proteolytically processing with enterokinase. Western blot shows that the mature AA was split into monomer and homodimer with molecular weights of 14 kDa and 28 kDa under reducing and non-reducing conditions, respectively. These results suggest that the mature form of rhAA could be produced and purified using transgenic rice cell suspension culture.