Coarse-grained molecular dynamics studies of the structure and stability of peptide-based drug amphiphile filaments

Abstract

Peptide-based supramolecular filaments, in particular filaments self-assembled by drug amphiphiles (DAs), possess great potential in the field of drug delivery. These filaments possess one hundred percent drug loading, with a release mechanism that can be tuned based on the dissociation of the supramolecular filaments and the degradation of the DAs [Cheetham et al., J. Am. Chem. Soc., 2013, 135(8), 2907]. Recently, much attention has been drawn to the competing intermolecular interactions that drive the self-assembly of peptide-based amphiphiles into supramolecular filaments. Recently, we reported on long-time atomistic molecular dynamics simulations to characterize the structure and growth of chiral filaments by the self-assembly of a DA containing the aromatic anti-cancer drug camptothecin [Kang et al., Macromolecules, 2016, 49(3), 994]. We found that the π-π stacking of the aromatic drug governs the early stages of the self-assembly process, while also contributing towards the chirality of the self-assembled filament. Based on these all-atomistic simulations, we now build a chemically accurate coarse-grained model that can capture the structure and stability of these supramolecular filaments at long time-scales (microseconds). These coarse-grained models successfully recapitulate the growth of the molecular clusters (and their elongation trends) compared with previously reported atomistic simulations. Furthermore, the interfacial structure and the helicity of the filaments are conserved. Next, we focus on characterization of the disassembly process of a 0.675 μm DA filament at microsecond time-scales. These results provide very useful tools for the rational design of functional supramolecular filaments, in particular supramolecular filaments for drug delivery applications.

Fig. 1

Coarse-grained and all-atomistic representations of the drug-amphiphile (DA) filaments. A. Atomistic model for ‘mCPT-buSS-Tau’, the DA in a CPK representation. B. CGed model for the DA shown as transparent VDW spheres, overlapping the atomistic model. The hydrophobic cancer drug camptothecin (CPT) is in red, the charged lysine and polar glutamine groups are shown in light green, while the rest residues are shown in yellow. CPT is expanded and rotated 90° to show the planar structure.

Fig. 2

Coarse-grained and all-atomistic representations of the drug-amphiphile (DA) filaments. A and B. Top and side views of the atomistic preassembled filament of the DA from the results of reference after 210 ns. In this representation, the atomistic CPT is also shown in red. In addition, β-sheets formed along the length of the filament are shown in yellow. C and D. The top and side views of the CGed preassembled filament of DAs after 1 μs simulation. The CGed DA is displayed in a licorice representation. The colors follow the same way as described in B. Water (transparent blue) is not shown for clarity in the side views.

Fig. 3

Structure of the preassembled system. A. Radial distributions in the preassembled system after 1 μs. The density is averaged for the last the last 100ns and 2 ns for the CGed and atomistic systems, respectively. The CPTs (black) remain buried in the core of the assembly, while the peptides (red) wrap around the core, forming the outer shell in both atomistic (dotted lines) and CGed (solid lines) models. In contrast to the water in the core in the atomistic model (blue dotted line), the CGed water (blue solid line) does not appear in the core of the assembly. The inset shows the density of the Cl⁻ ions. B. Probability distribution of the angle formed between the CPT’s long axis (Z1A–Z3A) and the radial direction, from the center of the filament on the same xy plane as the center of CPT to the center of CPT. The atomistic (AA), the CG-matched atomistic (AA′) and the CGed (CG) results are in black dotted, black solid, and red solid, respectively, in B, C, and D. For the direct comparison, CG-matched atomistic (AA′) results are calculated based on the center of all atoms corresponding to each CGed bead: pairs used for AA, AA′, and CG are C24–N14, (C24, C25, H45 and H46)-(N14, C15, H41 and H42), and Z1A–Z3A, respectively. C. Probability distribution of the angle formed between the peptides’ longest axis (LD of CYS-G8 of LYS) and the radial vector. Pairs used for AA, AA′, and CG are Cα of CYS-Cα of LYS, (CA, N, C, O, H and HA of CYS)-(CA, N, C, O, H and HA of LYS), and LD-G8, respectively. D. Probability distribution of the end-to-end distances of peptides. E. Stacking probability as the function of the distance between CPT planes. A cutoff for angle is 30 °. C(r,ϑ) = 1 (|ϑ| < 30°), C(r,ϑ) = 0 (|ϑ| > 30°). The CPT planes are defined with C24, N20, and C17 in the AA model and Z1A, Z2A and Z2B in the CGed model. F. Near-parallel CPTs are grouped and color-coded to show their stacking in the center of a CGed pre-assembled filament after 1 μs simulation time. G. From F, one group of parallel CPTs is highlighted in blue to show right-handed helical stacking.

Fig. 4

Cluster growth in a random system. A. A. The number of molecular clusters over time. The inset shows a snapshot of a random system of 16 mM at 1 μs. B. The number of CPT clusters over time. C. The average size of molecular clusters over time. D. The average size of CPT clusters over time. The results from the atomistic and the CGed models are in black, and red, respectively. The size of clusters increases, accompanying the gradual decrease of the number of molecular clusters. Compared with the atomistic results, the growth of molecular clusters of the CGed model matches well, while that of CPT clusters are slower in the CGed one.

Fig. 5

Elongation of clusters. A. A Cluster shows the shortest (R_min) and longest (R_max) axes. B. The average ratio of R_min/R_max of molecular clusters in the 16 mM random system. C. The average ratio of R_min/R_max of CPT clusters. The average ratio of R_min/R_max decreases as the size of clusters increases, indicating elongation of clusters over time. The elongation trend gets slightly weaker in the CGed model.

Fig. 6

π-π Stacking of CPTs. A. Clusters of DAs. The CPTs are highlighted in thicker red sticks. The rest parts of DAs and water are in yellow and transparent cyan, respectively. B. The distribution of angles between CPT planes within 7 Å in the random system. C. The distribution of angles between CPT planes within 7 Å in the preassembled system. The results from the AA and the CGed systems are displayed in black and red, respectively. The peaks near 0° and 180° indicate the near-parallel stackings of CPTs within 7 Å.

Fig. 7

Dissociation of the finite-length DA filament. The 0.675 μm filament (A) is equilibrated at 300 K for 0.2 μs (0.576 μm, B), and then the temperature is elevated to 350 K. During the disassembly, kinking, thinning, and budding are observed.