Cation Bulk and pK_a Modulate Diblock Polymer Micelle Binding to pDNA

Abstract

Polymer-based gene delivery relies on the binding, protection, and final release of nucleic acid cargo using polycations. Engineering polymeric vectors, by exploring novel topologies and cationic moieties, is a promising avenue to improve their performance, which hinges on the development of simple synthetic methods that allow facile preparation. In this work, we focus on cationic micelles formed from block polymers, which are examined as promising gene compaction agents and carriers. In this study, we report the synthesis and assembly of six amphiphilic poly(n-butyl acrylate)-b-poly(cationic acrylamide) diblock polymers with different types of cationic groups ((dialkyl)amine, morpholine, or imidazole) in their hydrophilic corona. The polycations were obtained through the parallel postpolymerization modification of a poly(n-butyl acrylate)-b-poly(pentafluorophenyl acrylate) reactive scaffold, which granted diblock polymers with equivalent degrees of polymerization and subsequent quantitative functionalization with cations of different pK a . Ultrasound-assisted direct dissolution of the polycations in different aqueous buffers (pH = 1−7) afforded micellar structures with low size dispersities and hydrodynamic radii below 100 nm. The formation and properties of micelle−DNA complexes ("micelleplexes") were explored via DLS, zeta potential, and dye-exclusion assays revealing that binding is influenced by the cation type present in the micelle corona where bulkiness and pK a are the drivers of micelleplex formation. Combining parallel synthesis strategies with simple direct dissolution formulation opens opportunities to optimize and expand the range of micelle delivery vehicles available by facile tuning of the composition of the cationic micelle corona.

Polycation Architecture Affects Complexation and Delivery of Short Antisense Oligonucleotides: Micelleplexes Outperform Polyplexes

“…Therefore, effective delivery vehicles are needed to allow for effective cellular delivery (transfection) in a safe manner. Cationic lipid-based nonviral gene delivery vehicles have also received recent attention; yet, lipids have drawbacks of their own, including complicated formulation devices to provide reliable and reproducible sized delivery vehicles and poor stability of liposomal complexes. , To overcome the challenges associated with both viral vehicles and lipid vehicles, the use of cationic polymers as nonviral gene delivery vehicles have increased in recent years due to their modular chemistry, easy scalability, affordable cost, and effectiveness. − Many groups have focused on the first aspect of gene delivery: creative design of polymers for gene therapy by modulating composition, − architecture, − molecular weight, − formulation parameters, etc. and examining their roles in cellular delivery efficiency.…”

Cationic Micelles Outperform Linear Polymers for Delivery of Antisense Oligonucleotides in Serum: An Exploration of Polymer Architecture, Cationic Moieties, and Cell Addition Order

“…This trend was previously seen when looking at these micelles and their binding to pDNA. 31 The overall trend of binding appears to correlate well with the transfection results; cationic moieties that bind more deliver the ASO more efficiently, whereas moieties that bind weaker tend to have less knockdown. Tighter binding can be important for getting the ASO into the cell; however, tighter binding can also be detrimental to delivery because the cargo must be released or unpackaged to perform its function.…”

“…Following a procedure developed by Santa Chalarca et al, a series of 10 polymers were synthesized . A homopolymer of pentafluoro phenyl acrylate (PFPA) as well as a diblock of PFPA and a hydrophobic block of n -butyl acrylate ( n BA) were synthesized to yield similar molecular weight PPFPA regions.…”

“…al 31. Briefly, diblock polymers were dissolved in MOPS (10 mM, ionic strength = 100 mM, pH = 7.0) at a 1 mg/mL concentration and stirred for 7 days.…”

Polymer Design via SHAP and Bayesian Machine Learning Optimizes pDNA and CRISPR Ribonucleoprotein Delivery

“…7,8 The advancement of controlled radical polymerization, [9][10][11][12][13][14][15] post-polymerization modi cation, [16][17][18] and parallel synthetic techniques, [19][20][21] have rapidly advanced and offers powerful tools to accelerate the next generation of bioactive polymer libraries. 17,[22][23][24] To this end, the eld of machine learning [25][26][27] coupled with parallel experimentation is aiding analysis and understanding of data sets identifying the chemical, physical, and biological factors involved in performance enhancement of polymers. 23,24,[28][29][30][31][32][33] However, we are limited by the vast chemical space and prediction of formulation chemistries indicating discrete selection and optimization of next generation systems.…”