Cholesterol-directed nanoparticle assemblies based on single amino acid peptide mutations activate cellular uptake and decrease tumor volume

Abstract

Peptide drugs have been difficult to translate into effective therapies due to their low in vivo stability. Here, we report a strategy to develop peptide-based therapeutic nanoparticles by screening a peptide library differing by single-site amino acid mutations of lysine-modified cholesterol. Certain cholesterol-modified peptides are found to promote and stabilize peptide α-helix formation, resulting in selectively cell-permeable peptides. One cholesterol-modified peptide self-assembles into stable nanoparticles with considerable α-helix propensity stabilized by intermolecular van der Waals interactions between inter-peptide cholesterol molecules, and shows 68.3% stability after incubation with serum for 16 h. The nanoparticles in turn interact with cell membrane cholesterols that are disproportionately present in cancer cell membranes, inducing lipid raft-mediated endocytosis and cancer cell death. Our results introduce a strategy to identify peptide nanoparticles that can effectively reduce tumor volumes when administered to in in vivo mice models. Our results also provide a simple platform for developing peptide-based anticancer drugs.

Fig. 1. (a) Sequences of HAL-2, HAL-B, HAL-C and HAL-D. Heptad positions are shown in italics. (b) Helical wheel diagram of the HAL-C sequence. Z letter refers to a substituted heptad f position in HAL-2 (orientation as in (a)). Energy-minimized α-helical structure of HAL-C (side view) and the conceptual nanoparticle formed by HAL-C. The gold balls refer to the cholesterol structure. The cartoon helices of HAL-C formed nanoparticles via the interaction between cholesterol molecules. (c) A cholesterol structure unit is modified in the lysine side (Z).

Fig. 2. (a) Zeta potentials of HAL-2, HAL-B, HAL-C and HAL-D in TBS (10, 20 and 30 μM, pH 7.4). (b) Helix propensity of HAL-2, HAL-C and HAL-D in TBS (pH 7.4) as a function of peptide concentration.

Fig. 3. (a) AFM and (b) TEM images of HAL-C (10 μM) in TBS (pH 7.4). (c) DLS of HAL-C (10 μM) in TBS (pH 7.4). (d) HPLC spectra of peptides, serum, and peptides incubated with mouse serum taken at 1 h, 8 h and 16 h at 37 °C.

Fig. 4. (a) Dose-response curves of HAL-2, HAL-B, HAL-C and HAL-D for SKOV-3 cells. The data are presented as mean ± SD (n = 5). (b) IC₅₀ values of SKOV-3 cells incubated with the four peptide nanoparticles. (**P < 0.01, ***P < 0.001). (c) Live/dead assays of SKOV-3 cells incubated with HAL-2 (12 μM) and HAL-C (12 μM) imaged with CLSM.

Fig. 5. (a) CLSM images of SKOV-3 cells cultured for 1 h with the HAL-2/NR complex (15/0.2 μM), and HAL-C/NR complex at various concentrations (5/0.06, 10/0.12 and 15/0.2 μM), (NR, red), (DAPI, blue). (b) The fold-increase values of MFI for SKOV-3 cells treated with different concentrations of HAL-2/NR and HAL-C/NR complex (2/0.025, 4/0.05 and 8/0.1 μM) in 5A media, respectively. (c) Dose-response curves of HAL-2 and HAL-C in the presence of 100 μL DiBAC4 (5) for the membrane potential effects in SKOV-3 cells at various concentrations (0–15 μM). Data are normalized to DiBAC4 (5) fluorescence responses and presented as mean ± SD (n ≥ 3, ***P < 0.001).

Fig. 6. (a) CLSM images of SKOV-3 cell pre-treated with AM, CPZ or MBCD at 37 °C for 40 min, rinsed, and subsequently incubated with HAL-C/NR (10 μM) at 37 °C for 1 h. (b) SKOV-3 cells stained with Phalloidin-iFluor™ 488 (F-actin, green), DAPI (nuclei, blue), or tubulin tracker (red) after incubation with HAL-2 (10 μM) and HAL-C (10 μM) for 1 h.

Fig. 7. Evaluating therapeutic efficacy of HAL-C in vivo. (a) Time dependent relative tumor volume. (b) The tumor inhibitory rates (TIRs) of the tumors after 14 days treatment (**P < 0.01 and ***P < 0.001).