Lévy-like movement patterns of metastatic cancer cells revealed in microfabricated systems and implicated in vivo.

Metastatic cancer cells differ from their non-metastatic counterparts not only in terms of molecular composition and genetics, but also by the very strategy they employ for locomotion. Here, we analyzed large-scale statistics for cells migrating on linear microtracks to show that metastatic cancer cells follow a qualitatively different movement strategy than their non-invasive counterparts. The trajectories of metastatic cells display clusters of small steps that are interspersed with long "flights". Such movements are characterized by heavy-tailed, truncated power law distributions of persistence times and are consistent with the Lévy walks that are also often employed by animal predators searching for scarce prey or food sources. In contrast, non-metastatic cancerous cells perform simple diffusive movements. These findings are supported by preliminary experiments with cancer cells migrating away from primary tumors in vivo. The use of chemical inhibitors targeting actin-binding proteins allows for "reprogramming" the Lévy walks into either diffusive or ballistic movements.

A Priori Estimation of Organic Reaction Yields.

A thermodynamically guided calculation of free energies of substrate and product molecules allows for the estimation of the yields of organic reactions. The non-ideality of the system and the solvent effects are taken into account through the activity coefficients calculated at the molecular level by perturbed-chain statistical associating fluid theory (PC-SAFT). The model is iteratively trained using a diverse set of reactions with yields that have been reported previously. This trained model can then estimate a priori the yields of reactions not included in the training set with an accuracy of ca. ±15 %. This ability has the potential to translate into significant economic savings through the selection and then execution of only those reactions that can proceed in good yields.

Synthesis of toroidal gold nanoparticles assisted by soft templates.

A three-component system comprising surfactant molecules and molecularly cross-linked metal centers assembles into nanoring structures. The thickness of the nanorings is determined by the dimensions of the surfactant bilayer while the dimensions of the ring opening depend on and can be regulated by the concentrations of the participating species. Once formed, these organic-inorganic hybrids can be transformed, by air plasma treatment, into all-metal nanorings exhibiting strong adsorption in the near IR.

Thermodynamically consistent force fields for the assembly of inorganic, organic, and biological nanostructures: the INTERFACE force field.

The complexity of the molecular recognition and assembly of biotic-abiotic interfaces on a scale of 1 to 1000 nm can be understood more effectively using simulation tools along with laboratory instrumentation. We discuss the current capabilities and limitations of atomistic force fields and explain a strategy to obtain dependable parameters for inorganic compounds that has been developed and tested over the past decade. Parameter developments include several silicates, aluminates, metals, oxides, sulfates, and apatites that are summarized in what we call the INTERFACE force field. The INTERFACE force field operates as an extension of common harmonic force fields (PCFF, COMPASS, CHARMM, AMBER, GROMACS, and OPLS-AA) by employing the same functional form and combination rules to enable simulations of inorganic-organic and inorganic-biomolecular interfaces. The parametrization builds on an in-depth understanding of physical-chemical properties on the atomic scale to assign each parameter, especially atomic charges and van der Waals constants, as well as on the validation of macroscale physical-chemical properties for each compound in comparison to measurements. The approach eliminates large discrepancies between computed and measured bulk and surface properties of up to 2 orders of magnitude using other parametrization protocols and increases the transferability of the parameters by introducing thermodynamic consistency. As a result, a wide range of properties can be computed in quantitative agreement with experiment, including densities, surface energies, solid-water interface tensions, anisotropies of interfacial energies of different crystal facets, adsorption energies of biomolecules, and thermal and mechanical properties. Applications include insight into the assembly of inorganic-organic multiphase materials, the recognition of inorganic facets by biomolecules, growth and shape preferences of nanocrystals and nanoparticles, as well as thermal transitions and nanomechanics. Limitations and opportunities for further development are also described.

Chemistry of aqueous silica nanoparticle surfaces and the mechanism of selective peptide adsorption.

Control over selective recognition of biomolecules on inorganic nanoparticles is a major challenge for the synthesis of new catalysts, functional carriers for therapeutics, and assembly of renewable biobased materials. We found low sequence similarity among sequences of peptides strongly attracted to amorphous silica nanoparticles of various size (15-450 nm) using combinatorial phage display methods. Characterization of the surface by acid base titrations and zeta potential measurements revealed that the acidity of the silica particles increased with larger particle size, corresponding to between 5% and 20% ionization of silanol groups at pH 7. The wide range of surface ionization results in the attraction of increasingly basic peptides to increasingly acidic nanoparticles, along with major changes in the aqueous interfacial layer as seen in molecular dynamics simulation. We identified the mechanism of peptide adsorption using binding assays, zeta potential measurements, IR spectra, and molecular simulations of the purified peptides (without phage) in contact with uniformly sized silica particles. Positively charged peptides are strongly attracted to anionic silica surfaces by ion pairing of protonated N-termini, Lys side chains, and Arg side chains with negatively charged siloxide groups. Further, attraction of the peptides to the surface involves hydrogen bonds between polar groups in the peptide with silanol and siloxide groups on the silica surface, as well as ion-dipole, dipole-dipole, and van-der-Waals interactions. Electrostatic attraction between peptides and particle surfaces is supported by neutralization of zeta potentials, an inverse correlation between the required peptide concentration for measurable adsorption and the peptide pI, and proximity of cationic groups to the surface in the computation. The importance of hydrogen bonds and polar interactions is supported by adsorption of noncationic peptides containing Ser, His, and Asp residues, including the formation of multilayers. We also demonstrate tuning of interfacial interactions using mutant peptides with an excellent correlation between adsorption measurements, zeta potentials, computed adsorption energies, and the proposed binding mechanism. Follow-on questions about the relation between peptide adsorption on silica nanoparticles and mineralization of silica from peptide-stabilized precursors are raised.