Artificial Neural Network Approach to Predict the Solubility of C60 in Various Solvents

Natural Products to Fight Cancer: A Focus on Juglans regia

Even if cancer represents a burden for human society, an exhaustive cure has not been discovered yet. Low therapeutic index and resistance to pharmacotherapy are two of the major limits of antitumour treatments. Natural products represent an excellent library of bioactive molecules. Thus, tapping into the natural world may prove useful in identifying new therapeutic options with favourable pharmaco-toxicological profiles. Juglans regia, or common walnut, is a very resilient tree that has inhabited our planet for thousands of years. Many studies correlate walnut consumption to beneficial effects towards several chronic diseases, such as cancer, mainly due to the bioactive molecules stored in different parts of the plant. Among others, polyphenols, quinones, proteins, and essential fatty acids contribute to its pharmacologic activity. The present review aims to offer a comprehensive perspective about the antitumour potential of the most promising compounds stored in this plant, such as juglanin, juglone, and the ellagitannin-metabolites urolithins or deriving from walnut dietary intake. All molecules and a chronic intake of the fruit provide tangible anticancer effects. However, the scarcity of studies on humans does not allow results to be conclusive.

Permeation of skin with (C60) fullerene dispersions

Dispersions in transcutol/isopropyl myristate make C₆₀ fullerene molecules suitable for transdermal delivery. We found that C₆₀ can successfully permeate the skin using pig skin in Franz diffusion cells. Molecular dynamics simulations and transmission electron microscopy confirmed these observations. Basic cosmetic formulations with transcutol/isopropyl myristate without harsh organic solvents show a high potential for delivery of C₆₀ for biopharmaceutical and cosmetics applications.

Fullerenes in Aromatic Solvents: Correlation between Solvation-Shell Structure, Solvate Formation, and Solubility

In this work, an all-atom molecular dynamics simulation technique was employed to gain insight into the dynamic structure of the solvation shell formed around C60 and phenyl-C61-butyric acid methyl ester (PCBM) in nine aromatic solvents. A new method was developed to visualize and quantify the distribution of solvent molecule orientations in the solvation shell. A strong positive correlation was found between the regularity of solvent molecule orientations in the solvation shell and the experimentally obtained solubility limits for both C60 and PCBM. This correlation was extended to predict a solubility of 36 g/L for PCBM in 1,2,4-trimethylbenze. The relationship between solvation-shell structure and solubility provided detailed insight into solvate formation of C60 and solvation in relation to solvent molecular structure and properties. The determined dependence of the solvation-shell structure on the geometric shape of the solvent might allow for enhanced control of fullerene solution-phase behavior during processing by chemically tailoring the solvent molecular structure, potentially diminishing the need for costly and environmentally harmful halogenated solvents and/or additives.

Nanomaterials – the Next Great Challenge for Qsar Modelers

In this final chapter a new perspective for the application of QSAR in the nanosciences is discussed. The role of nanomaterials is rapidly increasing in many aspects of everyday life. This is promoting a wide range of research needs related to both the design of new materials with required properties and performing a comprehensive risk assessment of the manufactured nanoparticles. The development of nanoscience also opens new areas for QSAR modelers. We have begun this contribution with a detailed discussion on the remarkable physical–chemical properties of nanomaterials and their specific toxicities. Both these factors should be considered as potential endpoints for further nano-QSAR studies. Then, we have highlighted the status and research needs in the area of molecular descriptors applicable to nanomaterials. Finally, we have put together currently available nano-QSAR models related to the physico-chemical endpoints of nanoparticles and their activity. Although we have observed many problems (i.e., a lack of experimental data, insufficient and inadequate descriptors), we do believe that application of QSAR methodology will significantly support nanoscience in the near future. Development of reliable nano-QSARs can be considered as the next challenging task for the QSAR community.

Self-organization of double-C60 end-capped poly(ethylene oxide) in chloronaphthalene and benzene solvent mixtures

Well-defined and narrowly distributed double-C60 end-functionalized poly(ethylene oxide) (C60-PEO-C60) was prepared by reacting azido-terminated PEO with C60. The self-organization behavior of such C60-modified copolymers in different mixtures of chloronaphthalene (CN) and benzene (BN) was studied by a combination of static and dynamic laser light scattering. For C60-PEO-C60 in pure CN, a selective solvent only for C60, self-organization occurred to form a large micelle-like core-shell aggregate, probably with some C60 interlocking with each other with the collapsed PEO chains as the core. The addition of BN, a second selective solvent for core-forming PEO chains, has a significant effect on the structures and compactness of the resultant aggregates because the introduction of BN increases the stretching of the PEO chains inside the core and modifies the interfacial energy of the core-corona interface. On the other hand, for C60-PEO-C60 in pure BN, a non-solvent of C60, several smaller flower-like micelles may self-organize to form a large spherical-like aggregation complex.

Accurate Quantitative Structure−Property Relationship Model To Predict the Solubility of C60 in Various Solvents Based on a Novel Approach Using a Least-Squares Support Vector Machine

A least-squares support vector machine (LSSVM) was used for the first time as a novel machine-learning technique for the prediction of the solubility of C60 in a large number of diverse solvents using calculated molecular descriptors from the molecular structure alone and on the basis of the software CODESSA as inputs. The heuristic method of CODESSA was used to select the correlated descriptors and build the linear model. Both the linear and the nonlinear models can give very satisfactory prediction results: the square of the correlation coefficient R(2) was 0.892 and 0.903, and the root-mean-square error was 0.126 and 0.116, respectively, for the whole data set. The prediction result of the LSSVM model is better than that obtained by the heuristic method and the reference, which proved LSSVM was a useful tool in the prediction of the solubility of C60. In addition, this paper provided a new and effective method for predicting the solubility of C60 from its structures and gave some insight into the structural features related to the solubility of C60 in different solvents.