Research - Biological Problems
Using our enhanced methods, we are studying the effect of sequence on folding, particularly for WW domains, and trying to extend simulation capabilities to larger molecules on the millisecond timescale. Of particular interest is the effect of flexibility on catalytic activity, the effect of phosphorylation and other post translational modifications in structure and dynamics, and the connection between correlated motions and phylogenetic co-evolution. We are collaborating with several experimental labs and theory groups in carrying out these studies.
Nearly 40% of the world's population is threatened by malaria . Every year, malaria infects 350-500 million and kills nearly 1 million people, mostly children . Vector control via the usage of insecticides has proven to be an effective means of controlling and eliminating malaria in areas such as southern part of the United States during the early 20th century . Unfortunately, resistance to the currently-used insecticides is increasing among vectors such as mosquitoes, and very few alternative insecticides that are safe and inexpensive are available . Needless to say, the problem is dire. In an effort to combat malaria, our lab is working with Dr. Frank Collins, Dr. Cate Hill (Purdue), and Dr. Mary Ann McDowell in an interdisciplinary collaboration to design the next generation of safe, inexpensive insecticides using a novel combination of in situ and in silico methods. Only just beginning, we are currently using bioinformatics techniques to identify viable insecticide targets in the proteomes of mosquitoes and other vectors which our collaborators can then verify experimentally. In addition, we will be drawing on our experience in molecular dynamics to perform virtual screening against the identified viable targets and provide a mechanism for measuring the toxicity to humans of potential insecticide compounds. It is our desire to develop general methods that can also be used to develop safe and inexpensive pesticides for other organisms.
The goal of this work, done in collaboration with The Center for Rare and Neglected Diseases at Notre Dame, is to investigate interactions between the parasite and host. In particular, we are looking at the relationship that P. falciparum has with the the β2 Adrenergic G-protein-coupled receptor. Some type of interaction was shown in 2003 by Harrison et al.  but an understanding of this process has proved elusive so far. By building a simulation based model of the GPCR our goal is twofold: 1) better understand the host-parasite interaction and 2) gain deeper insight into the activation mechanism of GPCRs.
Just as proteins are molecular machines, proteins are parts of inte racting networks that accomplish tasks such as responding to internal and external signals, perform metabolism, translation, and many other tasks in the cell. We combine different approaches to statistical inference of protein-protein interaction (PPI) networks, such as the use of error correction algorithms from information theory to clean experimental data and the use of weighted set cover algorithms to extract the most out of experimental data available. We combine these networks with biophysically-inspired models to study in greater details particular families of interactors of great biophysical interest, such as kinases and GPCR-G-proteins.