(6if) Multiscale Modeling and Enhanced Sampling to Probe Peptide and Peptidomimetic Assemblies

Recent progress in synthesis and fabrication techniques has given rise to a multitude of materials available for applications ranging from electronics to artificial implants. In many of these applications, synthetic materials form interfaces with biological matter, making it imperative to understand the interactions of biomolecules with inorganic substrates to improve material performance. Motivated by this, I will build a research program using the tools of computational materials science, with an emphasis on molecular dynamics (MD) simulations and enhanced sampling techniques (metadynamics, replica exchange, and umbrella sampling) to study molecular recognition patterns of polymeric substances to peptides and peptidomimetic matter. In order to probe these effects on a range of length and time scales, I will use atomistic and coarse-grained models. My future research themes will address challenges in (1) polymer membrane fouling due to the formation and build up of biofilms, (2) developing hybrid ‘bioink’ for additive manufacturing (3) drug delivery and therapeutics through the use of polymer-peptide conjugates

Research Experience:

The focus of my graduate research with Prof. Lisa Hall at the Ohio State University was to determine structure-property relationships in a class of charged polymers known as ionomers, from MD simulations. Ionomers contain a small fraction of ionic groups covalently bound to a non-polar backbone; these ions aggregate strongly along with counterions in a low dielectric medium. This work was in collaboration with the Sundaresan group, to aid in the development of ‘smart’ ionomer materials for 3D printing. To better map to typical experimental systems, I modified a coarse-grained ionomer model to include different ionic neutralization levels. Aggregate morphologies, as well as rheological properties were found to be in good agreement with experimental trends. By analyzing the long ranged ion correlations and calculating mechanical properties during uniaxial tensile deformation, I was able to provide molecular insight into an observed experimental phenomenon – increase in the mechanical strength of ionomers upon applying a static electric field. In addition, this model was employed to (1) delineate the effect of uniaxial strain on polymer backbone and ionic aggregates (2) study the structure and dynamics of ionic aggregates near a nanoparticle interface (3) examine the effect of a free interface on the adhesion of ionomer films.

In my current research with Prof. Jim Pfaendtner at the University of Washington (UW), I employ atomistic MD simulations to study biomolecules. Due to strong driving forces, these systems are difficult to investigate using traditional MD simulations, and my research has partially focused on developing new computational tools to address these challenges. With these tools, I work on three distinct projects (1) Binding Mechanisms of Solid Binding Peptides (SBPs) – SBPs are used in a wide range of applications, including targeted drug delivery and medical implants. This is due to the high degree of interfacial compatibility that can be achieved by precisely tailoring their sequence. By employing metadynamics, I construct free energy surfaces of these peptides as a function of different positional degrees of freedom. I calculate binding free energy of the peptide to compare with experimental dissociation constant, as a means to validate our model and system conditions. Detailed cluster analyses reveal an ensemble of peptide structures at the surface. This work is in collaboration with the Drobny group at UW. (2) Peptide Aggregation in Solution – Understanding biomineralization, the process by which living organisms produce hierarchically ordered structures with the aid of specific proteins, can help manufacture nanomaterials at ambient conditions. R5 and LKα14 peptides precipitate silica that is remarkably uniform in morphology; however, these peptides have completely different secondary structures in solution – R5 is random, and LKα14 is helical. This suggests that there are dominant interpeptide interactions that cause peptides, even random ones like R5 to assemble in a way that enables uniform templating of silica. By employing all atom MD simulations enhanced by metadynamics, I study the dominant driving forces of peptide aggregation, and ultimately compare the aggregates of R5 and LKα14 (3) Coarse-Grained Peptoid Model – Peptoids, positional isomers of peptides containing N-substituted glycine, are an excellent candidate for applications that require robust biopolymers, as they are easy to synthesize, and are stable over a wide range of conditions. Owing to their unique functionality, they have been shown to exhibit numerous self-assembled architectures, from tubes to sheets. An all atom peptoid forcefield was recently parameterized that accurately reproduced local structures from quantum mechanical calculations. To capture self-assembly properties of peptoids over long times, I have systematically developed a coarse-grained model using a bottom-up approach by explicitly parameterizing against the all atom forcefield. This work is in collaboration with the Ferguson group at the University of Chicago, and the Chen group at the Pacific Northwestern National Laboratory.

Teaching Interests:

I have served as a teaching assistant for undergraduate transport phenomena for one semester, during which I was a guest lecturer for two classes. I have also served as a teaching assistant for undergraduate process control for two semesters, during which I was a guest lecturer for three classes. Additionally, I volunteered to lecture on two grad level MD simulations classes. During my postdoc, I have given two lectures in a course titled Molecular Simulations.

Having been trained in chemical engineering throughout my career, I have the aptitude to teach any chemical engineering undergrad level course, although I am particularly interested in process control and thermodynamics. At the graduate level, I would like to teach advanced thermodynamics, encompassing statistical mechanics with an introduction to classical simulations.