Gaussian Approximation Potential: an interatomic potential derived from first principles Quantum Mechanics

Simulation of materials at the atomistic level is an important tool in studying microscopic structure and processes. The atomic interactions necessary for the simulation are correctly described by Quantum Mechanics. However, the computational resources required to solve the quantum mechanical equations limits the use of Quantum Mechanics at most to a few hundreds of atoms and only to a small fraction of the available configurational space. This thesis presents the results of my research on the development of a new interatomic potential generation scheme, which we refer to as Gaussian Approximation Potentials. In our framework, the quantum mechanical potential energy surface is interpolated between a set of predetermined values at different points in atomic configurational space by a non-linear, non-parametric regression method, the Gaussian Process. To perform the fitting, we represent the atomic environments by the bispectrum, which is invariant to permutations of the atoms in the neighbourhood and to global rotations. The result is a general scheme, that allows one to generate interatomic potentials based on arbitrary quantum mechanical data. We built a series of Gaussian Approximation Potentials using data obtained from Density Functional Theory and tested the capabilities of the method. We showed that our models reproduce the quantum mechanical potential energy surface remarkably well for the group IV semiconductors, iron and gallium nitride. Our potentials, while maintaining quantum mechanical accuracy, are several orders of magnitude faster than Quantum Mechanical methods.

Fibers with integrated mechanochemical switches: minimalistic design principles derived from fibronectin.

Inspired by molecular mechanisms that cells exploit to sense mechanical forces and convert them into biochemical signals, chemists dream of designing mechanochemical switches integrated into materials. Using the adhesion protein fibronectin, whose multiple repeats essentially display distinct molecular recognition motifs, we derived a computational model to explain how minimalistic designs of repeats translate into the mechanical characteristics of their fibrillar assemblies. The hierarchy of repeat-unfolding within fibrils is controlled not only by their relative mechanical stabilities, as found for single molecules, but also by the strength of cryptic interactions between adjacent molecules that become activated by stretching. The force-induced exposure of cryptic sites furthermore regulates the nonlinearity of stress-strain curves, the strain at which such fibers break, and the refolding kinetics and fraction of misfolded repeats. Gaining such computational insights at the mesoscale is important because translating protein-based concepts into novel polymer designs has proven difficult.

Differentiated adipose-derived stem cells act synergistically with RGD-modified surfaces to improve neurite outgrowth in a co-culture model.

Peripheral nerve damage is a problem encountered after trauma and during surgery and the development of synthetic polymer conduits may offer a promising alternative to autografts. In order to improve the performance of the polymer to be used for nerve conduits, poly-ε-caprolactone (PCL) films were chemically functionalized with RGD moieties, using a chemical reaction previously developed. In vitro cultures of dissociated dorsal root ganglion (DRG) neurons provide a valid model to study different factors affecting axonal growth. In this work, DRG neurons were cultured on RGD-functionalized PCL films. Adult adipose-derived stem cells differentiated to Schwann cells (dASCs) were initially cultured on the functionalized PCL films, resulting in improved attachment and proliferation. dASCs were also co-cultured with DRG neurons on treated and untreated PCL to assess stimulation by dASCs on neurite outgrowth. Neuron response was generally poor on untreated PCL films, but long neurites were observed in the presence of dASCs or RGD moieties. A combination of the two factors enhanced even further neurite outgrowth, acting synergistically. Finally, in order to better understand the extracellular matrix (ECM)-cell interaction, a β1 integrin blocking experiment was carried out. Neurite outgrowth was not affected by the specific antibody blocking, showing that β1 integrin function can be compensated by other molecules present on the cell membrane. Copyright © 2013 John Wiley & Sons, Ltd.

Design and formulation of functional pluripotent stem cell-derived cardiac microtissues.

Access to robust and information-rich human cardiac tissue models would accelerate drug-based strategies for treating heart disease. Despite significant effort, the generation of high-fidelity adult-like human cardiac tissue analogs remains challenging. We used computational modeling of tissue contraction and assembly mechanics in conjunction with microfabricated constraints to guide the design of aligned and functional 3D human pluripotent stem cell (hPSC)-derived cardiac microtissues that we term cardiac microwires (CMWs). Miniaturization of the platform circumvented the need for tissue vascularization and enabled higher-throughput image-based analysis of CMW drug responsiveness. CMW tissue properties could be tuned using electromechanical stimuli and cell composition. Specifically, controlling self-assembly of 3D tissues in aligned collagen, and pacing with point stimulation electrodes, were found to promote cardiac maturation-associated gene expression and in vivo-like electrical signal propagation. Furthermore, screening a range of hPSC-derived cardiac cell ratios identified that 75% NKX2 Homeobox 5 (NKX2-5)+ cardiomyocytes and 25% Cluster of Differentiation 90 OR (CD90)+ nonmyocytes optimized tissue remodeling dynamics and yielded enhanced structural and functional properties. Finally, we demonstrate the utility of the optimized platform in a tachycardic model of arrhythmogenesis, an aspect of cardiac electrophysiology not previously recapitulated in 3D in vitro hPSC-derived cardiac microtissue models. The design criteria identified with our CMW platform should accelerate the development of predictive in vitro assays of human heart tissue function.