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Preparation of unnatural N-to-N and C-to-C protein fusions.

ABSTRACT: Standard genetic approaches allow the production of protein composites by fusion of polypeptides in head-to-tail fashion. Some applications would benefit from constructions that are genetically impossible, such as the site-specific linkage of proteins via their N or C termini, when a remaining free terminus is required for biological activity. We developed a method for the production of N-to-N and C-to-C dimers, with full retention of the biological activity of both fusion partners and without inflicting chemical damage on the proteins to be joined. We use sortase A to install on the N or C terminus of proteins of interest the requisite modifications to execute a strain-promoted copper-free cycloaddition and show that the ensuing ligation proceeds efficiently. Applied here to protein-protein fusions, the method reported can be extended to connecting proteins with any entity of interest.

SUBMITTER: Witte MD

PROVIDER: S-EPMC3409725 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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Publications

Preparation of unnatural N-to-N and C-to-C protein fusions.

Witte Martin D MD Cragnolini Juan J JJ Dougan Stephanie K SK Yoder Nicholas C NC Popp Maximilian W MW Ploegh Hidde L HL

Proceedings of the National Academy of Sciences of the United States of America 20120709 30

Standard genetic approaches allow the production of protein composites by fusion of polypeptides in head-to-tail fashion. Some applications would benefit from constructions that are genetically impossible, such as the site-specific linkage of proteins via their N or C termini, when a remaining free terminus is required for biological activity. We developed a method for the production of N-to-N and C-to-C dimers, with full retention of the biological activity of both fusion partners and without i ...[more]

PMID: 22778432

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Project description:Recombinant protein therapeutics have increased in number and frequency since the introduction of human insulin, 25 years ago. Presently, proteins and peptides are commonly used in the clinic. However, the incorporation of peptides into clinically approved nanomedicines has been limited. Reasons for this include the challenges of decorating pharmaceutical-grade nanoparticles with proteins by a process that is robust, scalable, and cost-effective. As an alternative to covalent bioconjugation between a protein and nanoparticle, we report that biologically active proteins may themselves mediate the formation of small multimers through steric stabilization by large protein polymers. Unlike multistep purification and bioconjugation, this approach is completed during biosynthesis. As proof-of-principle, the disintegrin protein called vicrostatin (VCN) was fused to an elastin-like polypeptide (A192). A significant fraction of fusion proteins self-assembled into multimers with a hydrodynamic radius of 15.9 nm. The A192-VCN fusion proteins compete specifically for cell-surface integrins on human umbilical vein endothelial cells (HUVECs) and two breast cancer cell lines, MDA-MB-231 and MDA-MB-435. Confocal microscopy revealed that, unlike linear RGD-containing protein polymers, the disintegrin fusion protein undergoes rapid cellular internalization. To explore their potential clinical applications, fusion proteins were characterized using small animal positron emission tomography (microPET). Passive tumor accumulation was observed for control protein polymers; however, the tumor accumulation of A192-VCN was saturable, which is consistent with integrin-mediated binding. The fusion of a protein polymer and disintegrin results in a higher intratumoral contrast compared to free VCN or A192 alone. Given the diversity of disintegrin proteins with specificity for various cell-surface integrins, disintegrin fusions are a new source of biomaterials with potential diagnostic and therapeutic applications.

Dataset Information

Preparation of unnatural N-to-N and C-to-C protein fusions.

Publications

Preparation of unnatural N-to-N and C-to-C protein fusions.

Similar Datasets

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