Biomimetic Materials
Biomimetics are artificial structures inspired by or that attempt to mimic biological structure and function. This research focuses on two types of biomimetics designed to better understand molecular biology: reverse micelles and foldamers. Reverse micelles mimic cellular crowding with a membrane-like surfactant. Foldamers are synthetic polymers that have biopolymer assembly behavior. This research employs both atomistic and course-grain computational modeling to provide fundamental understanding these biomimics and insight into their biological counterparts.
Confinement and interfacial interactions are fundamental biophysical phenomena. The complexity of biological interfaces makes them experimentally and computationally challenging to study. Reverse micelles (RMs), also called water-in-oil microemulsions, are nanoscale structures that have a variety of commercial and biological uses including microreactors in nanoparticle synthesis and vesicles for enzymology. RMs are constructed in a nonpolar solvent where a surfactant solubilizes a water core and are commonly characterized by their water loading which is well controlled during assembly1, Figure 1. RMs provide a tunable system making them ideal in probing effects of confinement, crowding, and hydration on biomolecules in a membrane mimetic manner. Confinement and interfacial interactions are common concerns in cellular systems and RMs provide a tractable and controllable environment to investigate these phenomena. Specific aims for the reverse micelle model are to (1) extend the Bagchi spin model4 to include more geometric shapes and a more physical intermolecular interaction to provide improved understanding of interfacial effects on water dynamics and (2) add solutes to this model and incorporate diffusion to understand how confinement affects solute structure.
An important goal of biophysical chemistry is to understand the ability of biopolymers (e.g. proteins, polynucleotides, etc) to spontaneously and reversibly fold and/or self-assemble. For example, how protein’s are able to quickly find the appropriate folded state has been a question for 80 years2. This has inspired chemists and material scientists to achieve similar folding dynamics with synthetic polymers. For example, meta-poly-phenylene ethynylene (mPPE), shown in Figure 2, has a well-defined helix-to-coil transition at different polymer lengths and in various solvents3. They have been functionalized to tune self-assembly and have inducible chiral behavior. These foldamers provide an opportunity to explore fundamental aspects of organization in a generally more controlled system than their biochemical counterparts. Further, understanding of these biomimics may allow for future application in molecular biology (e.g. creation of synthetic membrane channels). Specific aims for the foldamers project are to (1) develop and evaluate new force field parameters to properly model mPPE (and similar) foldamers to better understand their folding equilibrium and dynamics and (2) develop substitutions on these foldamers to tune structural properties for future application.
This research, designed to be performed by undergraduates, aims to answer fundamental biophysical questions of folding, confinement, and interfaces using computational modeling of biomimetic material. Developing insight into biomimetic materials will help refine their current applications, aid in new application development, and provide useful fundamental insight into the more complex biological systems they model.
1) Fayer M. D., Levinger E. N., Annu. Rev. Anal. Chem., 3 (2010), 89-107.
2) Dill K. A. Protein Science, 8 (1999), 1166-1180.
3) Ray C. R.; Moore J. S. Adv Polym Sci., 177 (2005), 91-149.
Adaptive Implicit Solvation & Phosphate Solvation
Implicit solvation models are widely used both in small ab initio and large biomolecular calculations for their generally good approximation of the aqueous condensed phase at a fraction of computational cost. Almost all of these models require the creation of a surface the separates the more computationally detailed solute from the more course grain solvent. Results from these solvation models are highly sensitive to this surface. Many methods are available, most based on static, atomic radii that are overlapped and clipped to form a surface. The drawback to many of these surfaces is that they are not general enough to be used on a wide range of varied molecules and the surfaces cannot respond to changes in the system (e.g. chemical reactions). The goal of this project is to base the surface construction on the solute electronic properties so the surface can adapt to reactive changes as well as provide a more general scheme for surface construction.
One motivation for development of a better implicit solvation model is for the description of RNA enzyme catalysis, which requires proper description of solvation of the phosphate backbone. Current computational models did not well describe the phosphate hydrolysis reaction where the deprotonated O2′ of the RNA ribose attacks phosphate backbone. Further, the question of the phosphate backbone pKa values is important as the protonation state influences reaction mechanism. This led to a question of how well phosphate solvation and reactivity can be described in general. To get a better idea of how well current models describe phosphate solvation, phosphoric acid was chosen as a test molecule. How well can solvation models describe phosphoric acid? What are the solvation free energies of phosphoric acid and its anions?