Computational and Theoretical Chemistry
Glênisson de Oliveira
In the de Oliveira group, our main area of research is theoretical chemistry.  Historically, this label is distinct from “computational chemistry” in that the former includes the development of new methods and theories, while the latter consists of the use of existing models to help elucidate practical issues in chemical fields.  In the area of methods development, our recent efforts have been focused on the choice of mathematical functions (basis sets) used in approximate solutions of the Schrödinger equation (ab initio methods).  We have modified existing basis sets to efficiently and accurately determine the infinite basis set limits for physical properties of molecules and molecular clusters.   In one case, our method became part of standard computational chemistry packages, leading to some 300 citations to a single paper.  Given the fact that quantum mechanical calculations are particularly expensive, and simply unattainable for large systems, part of our effort is geared towards the development of models based on classical physics.  More specifically, we are interested in models that explicitly account for electrostatic contributions to non-covalent interactions, including the effect of polarizabilities, hyperpolarizabilities, and high order terms of the permanent moment tensor (i.e. beyond dipole moments).  Models we develop are used to study specific chemical problems of interest to us, but they serve as potential tools for other unrelated studies.  Our work has been supported by Rhode Island College Faculty Research Funds,  Faculty Development Funds, INBRE (NIH), EPSCoR (NSF), MRI (NSF), and Title II Partnership Grant (RIOHE).
John Williams
The term in silico has become current in pharmacology research to describe all computational efforts to help select new drug molecules. This involves both the selection of likely compounds for synthesis and the management of large data sets generated by high throughput screening (HTS). Our group does molecular mechanics docking calculations of our molecules and DNA. We calculate QSAR data for all structures with particular attention to the Lipinski Rule of  Five.  There are correlations between these data and the in vitro toxicology data. Modeling structures to better fit the DNA-docking interaction is done computationally to select target molecules for synthesis. We plan to expand this to calculations of protein docking interactions.
This work is supported by the  RI College Faculty Research Fund, EPSCoR and RI-INBRE.