Molecular recognition is an essential process in biological systems, providing a means for external inputs, such as small molecule ligands, to be translated into cellular responses. Many drugs take advantage of this phenomenon by mimicking ligands and binding to target proteins. During the process of ligand binding, proteins often undergo conformational changes. The mechanism underpinning this transition can be considered as a combination of two major pathways, known as "induced fit" and "conformational sampling." Determining contribution from these routes can be difficult, as intermediate states along the pathways exist at populations that most techniques cannot detect. Additionally, it is not known how a crowded environment, such as the inside of a cell, will affect these intermediate states or the affinity of proteins for their ligands as a result. I will be using seveal techniques to investigate the contribution of conformational selection to ligand binding affinity fr two periplasmic binding proteins. I will quantify the populations of two distinct unbound protein states in both dilute and crowded conditions by paramagnetic relaxation enhancement. It is expected that the These results will be combined with a simulation-based approach, using a technique developed in our lab known as "postprocessing" to predict the expected shift in equilibrium between conformations as a result of crowding. Ligand titrations will be performed in similar conditions, monitored by intrinsic tryptophan fluorescence to assess binding affinities. These results will be complemented with simulations designed to generate a potential of mean force for the closing and opening process of periplasmic binding proteins in liganded and unliganded forms. The results of this simulation will be analyzed to determine the ratios of binding affinities of open and closed forms of the proteins, and will be repeated in dilute and crowded conditions to predict changes in overall affinity. This project will produce some of the first studies that connect directly observed conformational equilibria in the unbound state to ligand binding properties. Using crowding agents in solution will provide insight into differences between dilute solution studies and biological conditions, and strengthen our understanding of molecular recognition as it occurs in biological systems.
Study of molecular recognition is essential to understanding how signaling processes function in living systems. Increased knowledge of ligand binding will result in additional insight when protein-ligand interactions do not function properly, often leading to unsuccessful signaling pathways that can cause disease states. Periplasmic binding proteins provide an excellent model system for investigating conformational changes and ligand binding in cell-like conditions, the results of which will create a more comprehensive picture of molecular recognition processes in living systems.
|Miklos, Andrew C; Sumpter, Matthew; Zhou, Huan-Xiang (2013) Competitive interactions of ligands and macromolecular crowders with maltose binding protein. PLoS One 8:e74969|