[Study of loading, cytotoxicity, uptake, and release of curcumin from a novel gemini surfactant nanocarrier]

Objective: Numerous researches have been conducted to comprehend the anti-cancer effects of curcumin [Cu]. Although the anti-proliferative properties of Cu on cancerous cells is known, the clinical application of this gold substrate is limited. This limitation is mostly due to low solubility, inefficient bioavailability, rapid metabolism, and improper uptake. In this study, we have synthesized a novel biodegradable gemini surfactant [Gs], after which the curcumin [Cu] molecules were encapsulated within the polymer to overcome its physicochemical limitations

Methods: We prepared Gs-Cu nanoparticles by the nanoprecipitation method. Size and polydispersity index of the nanoparticles were determined by the dynamic light scattering [DLS] technique. The release profile of Cu from the polymer matrix was studied, and the MTT assay and cellular uptake of Gs-Cu on MDA-MB-231 cells were investigated in vitro

Results: The Gs polymer had the capability to form polymersomes in an aqueous solution; a narrow size distribution was obtained [PDI=0.3]. The encapsulation efficiency approximated 87%. We observed a sustained release profile due to incorporation of Cu into the polymer matrix. The Gs-Cu complex showed more cytotoxicity compared to free Cu because of the higher rate of cellular internalization

Conclusions: The data indicate that Gs polymersomes can be regarded as nanocarriers for hydrophobic curcumin molecules

Helix segment assignment in proteins using fuzzy logic

The automatic assignment of protein secondary structure from three dimensional coordinates is an essential step in the characterization of protein structure. Although, the recognition of secondary structures such as alpha-helices and beta-sheets seem straightforward, but there are many different definitions, each regarding different criteria. We have developed a new algorithm for protein helix assignment, by using fuzzy logic based on backbone torsion angles. In this method, each residue takes a number from 0 to 100 that indicates the helical membership degree of that residue. This method can be converted to a classical method whenever we assume that any residue with a membership degree greater than 83 is a helix. Comparison of the results with structures reported in protein data bank [PDB], dictionary of secondary structure of proteins [DSSP] and structure identification [STRIDE] for 324 proteins indicate that our algorithm works as well as DSSP showing 93% agreement. We believe that the fuzzy secondary structure assignment has more advantages than the other classical approaches used for protein structure comparisons and alignments