This talk will provide an overview of our group’s work using both standard and atypical high-performance computational chemistry modeling to elucidate atomic scale reaction mechanisms of catalytic reactions. I will introduce our toolkit of in silico methods for accurately modeling (electro)catalytic reactions in solvating environments. I will then present how in silico methods can be used for predictive insights into chemical and material design.
Antimicrobial, cytolytic, and cell-penetrating peptides, often called membrane-active peptides, belong to a variety of structural classes, including, alpha-helical, beta-sheet, unstructured, and cyclic polypeptides, among others. Those peptides were intensely studied in the 1990s and early 2000s with the hope of opening the door for urgently needed new antibiotics. For about 15 years we have studied the kinetics and thermodynamics of their interactions with lipid vesicles with the hope of understanding the mechanism of their function.
Increasingly, fluorescent tools are providing insight into the “dark matter” of the cellular milieu: small molecules, secondary metabolites, metals, and ions. One of the great promises of such tools is the ability to quantify cellular signals in precise locations with high temporal resolution. Yet this is coupled with the challenge of how to ensure that our tools are not perturbing the underlying biology and the need to systematically measure hundreds of individual cells over time.
I will present recent work from my lab on the development and applications of magic-angle spinning solid-state nuclear magnetic resonance (NMR) techniques toward the structural and dynamic analysis of supramolecular protein and protein-DNA assemblies.