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An effective cell-penetrating antibody delivery platform.

ABSTRACT: Despite their well-recognized success in the clinic, antibodies generally do not penetrate cellular membranes to target intracellular molecules, many of which underlie incurable diseases. Here we show that covalently conjugating phosphorothioated DNA oligonucleotides to antibodies enabled their efficient cellular internalization. Antibody cell penetration was partially mediated by membrane potential alteration. Moreover, without an antigen to bind, intracellular levels of the modified antibodies underwent cellular clearance, which involved efflux and lysosomal degradation, enabling detection of intended intracellular molecules as tested in fibroblasts, tumor cells, and T cells. This target-dependent cellular retention of modified antibodies extended to in vivo studies. Both local and systemic administrations of low doses of modified antibodies effectively inhibited intracellular targets, such as transcription factors Myc, interferon regulatory factor 4, and tyrosine-protein kinase SRC, and expression of their downstream genes in tumors, resulting in tumor cell apoptosis and tumor growth inhibition. This simple modification enables the use of antibodies to detect and modulate intracellular molecules in both cultured living cells and in whole animals, forming the foundation for a new paradigm for antibody-based research, diagnostics, and therapeutics.

SUBMITTER: Herrmann A

PROVIDER: S-EPMC6675557 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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An effective cell-penetrating antibody delivery platform.

Herrmann Andreas A Nagao Toshikage T Zhang Chunyan C Lahtz Christoph C Li Yi-Jia YJ Yue Chanyu C Mülfarth Ronja R Yu Hua H

JCI insight 20190725 14

Despite their well-recognized success in the clinic, antibodies generally do not penetrate cellular membranes to target intracellular molecules, many of which underlie incurable diseases. Here we show that covalently conjugating phosphorothioated DNA oligonucleotides to antibodies enabled their efficient cellular internalization. Antibody cell penetration was partially mediated by membrane potential alteration. Moreover, without an antigen to bind, intracellular levels of the modified antibodies ...[more]

PMID: 31341104

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Project description:BackgroundCell penetrating peptides have gained much recognition as a versatile transport vehicle for the intracellular delivery of wide range of cargoes (i.e. oligonucelotides, small molecules, proteins, etc.), that otherwise lack bioavailability, thus offering great potential as future therapeutics. Keeping in mind the therapeutic importance of these peptides, we have developed in silico methods for the prediction of cell penetrating peptides, which can be used for rapid screening of such peptides prior to their synthesis.MethodsIn the present study, support vector machine (SVM)-based models have been developed for predicting and designing highly effective cell penetrating peptides. Various features like amino acid composition, dipeptide composition, binary profile of patterns, and physicochemical properties have been used as input features. The main dataset used in this study consists of 708 peptides. In addition, we have identified various motifs in cell penetrating peptides, and used these motifs for developing a hybrid prediction model. Performance of our method was evaluated on an independent dataset and also compared with that of the existing methods.ResultsIn cell penetrating peptides, certain residues (e.g. Arg, Lys, Pro, Trp, Leu, and Ala) are preferred at specific locations. Thus, it was possible to discriminate cell-penetrating peptides from non-cell penetrating peptides based on amino acid composition. All models were evaluated using five-fold cross-validation technique. We have achieved a maximum accuracy of 97.40% using the hybrid model that combines motif information and binary profile of the peptides. On independent dataset, we achieved maximum accuracy of 81.31% with MCC of 0.63.ConclusionThe present study demonstrates that features like amino acid composition, binary profile of patterns and motifs, can be used to train an SVM classifier that can predict cell penetrating peptides with higher accuracy. The hybrid model described in this study achieved more accuracy than the previous methods and thus may complement the existing methods. Based on the above study, a user-friendly web server CellPPD has been developed to help the biologists, where a user can predict and design CPPs with much ease. CellPPD web server is freely accessible at http://crdd.osdd.net/raghava/cellppd/.

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An effective cell-penetrating antibody delivery platform.

Publications

An effective cell-penetrating antibody delivery platform.

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