smurray

“Electrochemistry as a Design Tool for Colloidal Syntheses of Polyhedral Metal Nanoparticles”

The funded work will use real-time electrochemical measurements to probe the growth of noble metal nanoparticles and to provide enhanced chemical understanding of how to predictively and controllably produce metal nanoparticles with well-defined shapes. The ability to tune the function of noble metal nanoparticles by tailoring not only their composition but also their shape makes them especially promising for applications in catalysis, particularly for improving the sustainable usage of energy resources and enabling the generation of sustainable fuels. However, the chemical environment under which these materials are made is complex and involves multiple competing parameters. As a result, it can be challenging to understand precisely how these materials form and, consequently, how to design methods for producing the new materials required for various applications. Electrochemistry provides a powerful means by which to address this challenge, and involves the measurement of current and voltage to understand chemical reactions, as well as the application of a current or voltage to drive chemical processes. An electrochemical approach that integrates both of these methods will be used to gain understanding of the chemical reactions involved in metal nanoparticle growth while they are happening and with a level of detail and insight that is not possible using existing methods. This research will establish core chemical principles to inform the deliberate, predictive design of new metal nanomaterials to meet the increasingly complex needs of emerging applications. Graduate, undergraduate, and high school students who are involved in this research will be prepared for future careers at the interface of chemistry, materials science, and chemical engineering. The project will also contribute to enhancing participation in science and research by developing publicly available resources to increase the accessibility of undergraduate science for students who are the first in their family to pursue this course of study.

“Protein Structure Refinement with Ensemble-Based Scoring of Experimental Restraints”

Experimental data has been critical for protein structure determination with the Rosetta biomolecular modeling software. However, a key limitation in the way Rosetta handles that data is that a single structure must satisfy all data simultaneously. This in stark contrast to the physical reality that experimental data is derived from an ensemble of different protein conformations. The single structure approximation can therefore introduce artifacts and inaccuracies in the resulting protein structure models. The proposed work will develop computer code in Rosetta that enables scoring and optimization of multiple conformations simultaneously with experimental restraints or other score terms that are based on the entire ensemble and not a single structure alone.

We expect this will enable Rosetta to extract dynamics information from experimental data sources that explicitly capture structural heterogeneity. Such techniques include nuclear magnetic resonance (NMR), electron paramagnetic resonance (EPR), X-ray crystallography, electron microscopy (EM), X-ray scattering (SAXS), cross-linking mass spectroscopy (XLMS), etc. The accuracy of several of those techniques is limited by the lack of explicit atomic modeling of the ensemble of states the chemical labels or cross linkers can take, which could also be addressed with the proposed ensemble scoring methodology.

Colin Smith, Professor of Chemistry

“Dynamics of Computationally Designed Fluorescent Proteins”

The goal of the research is to study and optimize the movement of microscopic, computationally designed proteins that use light to track the locations of biological molecules and reveal how living organisms work. While the structure of a protein is almost always necessary for function, it is often not sufficient. This project focuses on the critical but often neglected role of protein motion in enabling absorbance and reemission of light, a process known as fluorescence. We will first determine which protein shapes either enhance or inhibit fluorescence through detailed analysis of computer simulations and extensive experimental structural characterization. Second, we will test our models through redesign and experimental examination of brighter fluorescent protein variants. As part of these efforts, we will develop a general-purpose computer algorithm that enables rapid evaluation of how thousands of potential mutations affect the shape of the protein. Third, we will investigate the structural determinants of other important properties like the ability of the protein to prevent or facilitate switching fluorescence on and off. The ultimate aim of this project is to develop a detailed understanding of how these fluorescent proteins can be redesigned to make them truly useful tools for biological research. This will enable the creation of even more advanced versions of these and other protein machines (like enzymes) that can also help in the manufacture and recycling of materials at the chemical level.