Experimental Modulation And Computational Model Of Nano-hydrophobicity

Nanomaterials are novel substances that differ from their bulk conterparts. Reaching nano levels, unusual properties appear for many substances, which make them posess special functions that others don’t have, nanomaterials are honoured as the most promising novel materials in the 21th century.The development of nanotechnology has been mading the wide application of nanomaterials in many areas, nanomaterials play irreplaceable roles especially in biomedicine field. Due to small size effect, nanomaterials have well cell permeability, they can not only prolong the circulation time of drugs in vivo after unique modification and entrapment of drugs, but also can be recognized by cell surface receptor when they arrive at the diseased tissues, thus drugs can be delivered targetly and efficiently released in cells to achieve better therapeutic effect. In addition, because of their large surface area volume ratio, nanomaterials can adsorbe more molecules, the signal can be magnified and sensitivity can be improved in the process when they interact with the biomolecules in the diseased tissue, from the measurement of the outer equipment, some diseases can be diagnosed, prevented and treated in early stages. However, many factors influence the applications of nanomaterials. After entering organism, the bioactivity of nanomaterials can not only be influenced by their bioenvironment (such as acidity and ionic strength) but also can be interfered by biomolecules (they may adsorb onto surface of nanoparticle because of the electrostatic or hydrophobic interactions) existed in circulatory systems and properties of nanomaterials. The bioenvironment and biomolecular in the circulatory system are hard to interfere with and controll for humans, so researches and manipulation on nanomaterials with both compatibility and specific bioactivities are crucial for the development of biomedicine.It has been found that the size, shape, surface roughness of nanomaterials can affect the nano-bio interactions. Besides, surface charges, surface hydorphobicity,π bond, hydrogen donors and receptors of nanomaterials are also important factors, of which one key factor is nano-hydrophobicity. Understanding factors influencing nano-hydrophobicity, revealing their relationships, regulating nano-hydrophobicity will interfere effectively with bioactivities of nanomaterials.Surface groups are important factors for nano-hydrophobicity. To investigate relationships between nano-hydrophobicity and their surface groups, we selected GNPs as models which are of low toxicity, well biocompatibility, easy to modify, synthesized 42 surface ligands of diverse structure to modify GNPs, obtained a GNP library 1 containing 42 GNPs (GNP 1-42). Nano-hydrophobocity was examined by shaking flask method, and the traditional group contribution approach (Traditional-GCA) was used here to predict LogP of GNPs’surface ligands. Results showed that there are large gaps between experimental LogP (ELogP) and calculation LogP (KLogP), this may because in the actural situation, surface ligands of GNPs were constrained in the surroundings of Au nuclei, they can not act freely like small molecular, moreover, the atoms or groups close to the Au nuclei may also be buried by their outer parts, and they can not be fully touched by solvent molecular, so it isn’t reasonable to use the whole ligand for LogP calculation. In order to testify our speculation, we calculated LogP values for different substructures, KLogP2 and KLogP3. From the calculation results, KLogP3 are more close to ELogP compared with KLogP2 and KLogP1, which implies that nano-hydrophobicity are mostly determined by the outermost portion of surface ligands. Because in the Traditonal-GCA, each group is equivalently weighted and steric hindrance is not considered. To fully consider the steric hindrance from surface ligands and the size of water molecules, a new calculation approach, Nano-GCA was established and applied to the computation. In this method, the closer the groups or atoms of surface ligand to the Au nuclei, the smaller of their contributions to LogP values. Results showed that LogP calculated by Nano-GCA was further improved Compared with KLogP3.Although calculation by Nano-GCA was improved obviously compared with KLogP3 calculated by Traditinal-GCA, the results were still not satisfactory (R2=0.51). This may be caused by the lack of careful consideration of effects of ligand density on LogP calculation in Nano-GCA, ligand density can also affect the effective touchment of groups for solvent molecules. To better undertand impact of ligand density on LogP, and to further testify the accuracy of Nano-GCA, we designed and synthesized a new GNP library-library 2 (GNP43-49). Unlike single-ligand modified GNP library 1, dual ligand (hydrophilic ligand A and hydrophobic liangd B) modification were selected in GNP library 2. GNP library 2 were obtained by NaBH4 reduction method through adjusting the ratios of ligand A and B in the synthesis process,I2 cleavage and HPLC/UV/MS method were used to quantify the ligand number on GNP surface in library 2, and results confirmed the successful synthesis of continuous change of ligand A and B on GNPs from GNP43 to GNP49. Shaking flask method was again used to measure LogP of GNP43-49, their ELogP increased as the decrease of hydrophilic ligand A and the increase of hydrophobic ligand B from GNP43 to GNP49. Traditional-GCA and Nano-GCA were both applied to the LogP calculation of surface ligands. Traditional-GCA indicated the failure of this approach, and Nano-GCA predicted successfully for nano-hydrophobocity after consideration of effects of ligand density (Dj) on LogP calculation, highlighting the importance of Dj in the calculation.The accurate prediction of nano-hydrophobicity is important for potential biological and medical applications of nanomaterials. To demonstrate the influences of nano-hydrophobicity on NP’s bioactivities, we observed relationships between nano-hydrophobicity and cytotoxicity. We selected THP-1 stimulated by PMA as cell model, and investigated their cell uptake and cytotoxicity for GNP43-49. Results demonstrated that macrophages internalized more hydrophobic GNPs within the same time period and were more susceptible to toxicity by hydrophobic nanoparticles than hydrophilic ones. This can be interpreted by the phospholipid bilayer in cell membrane, which can facilitate the permeation of more hydrophobic nanomaterials.In summary, nano-hydrophobicity are mostly determined by the outermost region of ligand, and the Nano-GCA can predict accurately for nano-hydrophobicity. In the computation process, ligand density (Dj) is an important factor that can not be ignored. More hydrophobic NPs are more inclined to be swallowed by macrophages than hydrophilic ones. The research will be helpful in predicting LogP values of novel nanoparticles and will promote the design, synthesis and application of nanomaterials with special bioactivities.