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Effective nose-to-brain delivery of exendin-4 via coadministration with cell-penetrating peptides for improving progressive cognitive dysfunction.

ABSTRACT: In a recent study, we demonstrated the potential of a cell-penetrating peptide (CPP) penetratin to deliver the peptide drug insulin to the brain via nasal administration, and its pharmacological effect on the mild cognitive dysfunction in senescence-accelerated mouse (SAMP8). However, the therapeutic potential of intranasal insulin administration was attenuated when applied to the aged SAMP8 with severe cognitive dysfunction. The present study, therefore, aimed to overcome the difficulty in treating severe cognitive dysfunction using insulin by investigating potential alternatives, glucagon-like peptide-1 (GLP-1) receptor agonists such as exendin-4. Examination using normal ddY mice demonstrated that the distribution of exendin-4 throughout the brain was dramatically increased by intranasal coadministration with the L-form of penetratin. The activation of hippocampal insulin signaling after the simultaneous nose-to-brain delivery of exendin-4 and an adequate level of insulin were confirmed by analyzing the phosphorylation of Akt. Furthermore, spatial learning ability, evaluated in the Morris water maze test after daily administration of exendin-4 with L-penetratin and supplemental insulin for 4 weeks, suggested therapeutic efficacy against severe cognitive dysfunction. The present study suggests that nose-to-brain delivery of exendin-4 with supplemental insulin, mediated by CPP coadministration, shows promise for the treatment of progressive cognitive dysfunction in SAMP8.

SUBMITTER: Kamei N

PROVIDER: S-EPMC6281676 | biostudies-other | 2018 Dec

REPOSITORIES: biostudies-other

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Effective nose-to-brain delivery of exendin-4 via coadministration with cell-penetrating peptides for improving progressive cognitive dysfunction.

Kamei Noriyasu N Okada Nobuyuki N Ikeda Takamasa T Choi Hayoung H Fujiwara Yui Y Okumura Haruka H Takeda-Morishita Mariko M

Scientific reports 20181205 1

In a recent study, we demonstrated the potential of a cell-penetrating peptide (CPP) penetratin to deliver the peptide drug insulin to the brain via nasal administration, and its pharmacological effect on the mild cognitive dysfunction in senescence-accelerated mouse (SAMP8). However, the therapeutic potential of intranasal insulin administration was attenuated when applied to the aged SAMP8 with severe cognitive dysfunction. The present study, therefore, aimed to overcome the difficulty in trea ...[more]

PMID: 30518944

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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/.

Dataset Information

Effective nose-to-brain delivery of exendin-4 via coadministration with cell-penetrating peptides for improving progressive cognitive dysfunction.

Publications

Effective nose-to-brain delivery of exendin-4 via coadministration with cell-penetrating peptides for improving progressive cognitive dysfunction.

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