Steven Gwaltney

Steven Gwaltney


  • Faculty


  • Computational
  • Physical

Research Summary

Quantum chemistry; Molecular dynamics


  • Professor



  • Hand Lab 1124

B.S. Indiana University, 1992
Ph.D. University of Florida, 1997

The Gwaltney group’s primary research interest has been to use molecular simulations to study chemical phenomena that are not accessible experimentally because of the time scales and length scales involved.  Our preferred approach is molecular dynamics (MD) calculations applied to synthetic polymers and to biopolymers combined with high-level ab initio calculations on small molecules.  Our synthetic polymer research involves building new force fields to describe polymers and polymer/metal interfaces.  We also study the interactions of polymers with surfaces.

Organophosphate Toxicity

As part of my group’s interest in organophosphate toxicity, long ago we began studying the serine hydrolases acetylcholinesterase and butrylcholinsterase.  Specifically, through a research project funded by the Defense Threat Reduction Agency (DTRA), we used MD simulations to calculate the mechanisms of binding and the binding affinities of next-generation oxime reactivators, which are used to treat organophosphate poisoning, including poisoning from exposure to organophosphate nerve gases.  As an outgrowth of our cholinesterase modeling, we became interested in the related carboxylesterase enzymes.  In collaboration with an experimental group and another computational group, we have modeled the effects of point mutations on the structure, function, and stability of the bacterial pnbCE enzyme, which in a model for the human carboxylesterase 1 enzyme.  The pnbCE work was supported through an NSF EPSCoR grant.  Most recently, we have been modeling the PON1 enzyme in order to develop small molecule enhancers that will increase its ability to hydrolyze organophosphates.  This research was funded through another DTRA grant.  We have shown through our modeling of the human PON1 enzyme that the standard model for this enzyme, a crystal structure of a recombinant PON1, has certain deficiencies that may have played a part in misunderstanding this enzyme’s function.

Polymer – Surface Interactions

My group is also interested in MD simulations of thermoset resins and polymers and the interactions of the resins and polymers with the surfaces of graphene nano-composites.  We have shown that the composition of the polymer near the surface differs significantly from the bulk composition, leading to the interphase region, the region of the polymer next to the graphene surface, have substantially different chemical and physical properties than the bulk polymer.  The key methodological advance in this work was our development of a new model for computationally curing the polymer that properly took into consideration the local concentration of the monomers, the regioselectivity of the polymerization reaction, and the relative reaction rates of the monomers with each other.  We would also like to study the interactions between polymers and metal surfaces.  However, the MD force fields typically used for polymer modeling are not compatible with the typical metal force fields.  Therefore, in collaboration with a group who specializes in modeling metals, we have been extending the modified embedded atom method (MEAM) force field, one of the main metals MD force fields, to be able to model polymers, as well.  We currently have the MEAM force field working for saturated and unsaturated hydrocarbons.  Next is to add nitrogen, oxygen, and sulfur to the force field.

Polymers for Water Quality Monitoring

The goal of this new project is to design new sensing technologies for deployment in the marine environment to detect pollutants (CO2, nitrates, phosphates, and polycyclic aromatic hydrocarbons (PAH’s)).  New modular receptor-analyte interactions for CO2, nitrates, phosphates, and polycyclic aromatic hydrocarbons (PAH’s) capable of specifically transducing an analyte-binding event into a useable signal are being designed and evaluated.  Computational (done by our group) and experimental (done by collaborators) approaches are being combined to gain understanding of the molecular parameters that control the strength and stability of analyte-receptor interactions of designed systems in complex aqueous environments.  Promising receptors will be incorporated into polymeric systems, where the influence of polymer structure on sensitivity of the sensors will be studied and used to develop predictive models.