Intravascularly injectable nanovectors are a major class of nanotechnological devices of interest for use in cancer therapy. Nanovectors in general have at least a bipartite constitution, featuring a core-constituent material and a therapeutical payload. A third function, a biological surface modifier, may be present to enhance the biodistribution and/or tumor targeting of the nanovectors. Nanovector formulations are designed to reduce the clearance time of fast metabolized drugs, provide protection of active agents from enzymatic and environmental degradation, and avoid obstacles to the targeting of active moieties.
RNA interference (RNAi) was originally recognized as an evolutionary conserve defense mechanism in response to double-strand (ds) RNA and represents a powerful, naturally occurring biological strategy for specific gene silencing. It is mediated through 21-25nt double-stranded RNA molecules (small interfering RNA, or siRNAs), which are intracellularly generated from long, endogenous or exogenous ds RNAs, or directly transfected into the cells. Since RNAi is able to provide the relatively easy ablation of the expression of a target gene, it is now commonly used as a powerful tool in biological and medical research. This includes the strategy of siRNA-mediated targeting for functional studies of various genes whose expression is known to be upregulated in a given disease. Since siRNAs play a pivotal role in this process, the critical factors that determine the success of RNAi approaches are (i) the functionality of siRNAs, and (ii) the ability to deliver intact siRNA efficiently to the cells. Chemically unmodified siRNAs, in fact, are rapidly degraded, and mammalian cells do not readily take up naked nucleic acids. Thus, besides retroviruses, adenoviruses, and lentiviruses as vehicles for RNA interference constructs, strategies to deliver siRNA therapeutics to target cells in cell cultures include transduction by physical or chemical transfection by means of nanovectors.
Among these, block and graft co-polymers containing cationic polyelectrolytes, nonionic hydrophilic polymers, and positively charged hyperbranched polymeric structures such as dendrimers have gained significant interest. The task of the cationic moieties is to condense the nucleic acids, whereas the nonionic, hydrophilic parts should increase the solubility, stability and biocompatibility of the resulting supermolecular assembly. Branched polyethylenimine (PEI) has been shown to be one of the most efficient cationic polymers with regard to transfection efficiency. Linear polyethylene glycol (PEG) has been employed in several studies to optimize the biochemical/biophysical properties of transfection complexes. Different combinations of PEI with PEG have different effects on a series of important parameters of the siRNA/PEI complexes, including efficiency of nucleic acid complexation, complex stability in the presence of competing polyanions and nucleases, in vitro toxicity, cellular uptake and siRNA-induced gene silencing. However, the degree of PEGylation and molecular mass of PEG molecules affected the properties of siRNA/PEI complexes in apparently unpredictable ways. Furthermore, current knowledge of the interplay between the molecular structure of PEG-PEI copolymers and the resulting characteristics of siRNA/PEG-PEI complexes is very limited and rather empirical. Utterly analogous considerations can be drawn when the nanocarriers are dendrimeric families, such as the poly(amido amine) or PAMAM series.
Systematic investigation of the structure-activity relationship of the siRNA/nanocarrier assemblies is hindered by the absence of appropriated experimental techniques to study the fine ultra-structure of these nanocarrier-cargo complexes. Molecular modeling can provide a unique approach to simulate the structures of these assemblies and analyze their properties. In the current work, we applied in silico molecular simulation techniques to define the mode of the interaction of siRNAs with copolymeric and/or dendrimeric delivery agents and identify critical parameters for optimization of carrier/cargo interactions. The combination of computational and experimental approaches will provide essential information for rational design of improved delivery systems for siRNA therapeutics. Optimal delivery would increase the efficacy of these powerful gene-targeted agents and move this strategy toward clinical applications.