Associate Professor
Hamilton Hall 722
402.472.3039
rpowers@unlserve.unl.edu

Powers Research Group
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Current Research
The availability of the Human Genome is providing an unprecedented opportunity to expand our understanding of cell biology, development, evolution and physiology with tremendous potential benefits to human health issues and drug discovery.

Capitalizing on this opportunity requires a concerted effort to identify the functional and therapeutic roles of the vast number of novel proteins being identified by genome sequencing. My research interest is focused on developing technologies that use bioinformatics, NMR spectroscopy, mass spectroscopy, metabolomics, molecular modeling and structural biology to assign a biological function to novel proteins. Determining protein structures by NMR and deciphering their biological function provides a starting point for a structure-based drug discovery effort (figure 1).

Figure 1 – NMR structure of AF2095 from the thermophilic archaea Archaeglobus fulgidis enabled its annotation as a peptidyl-tRNA hydrolase (Pth2)

We are developing the Functional Annotation Screening Technology by NMR (FAST-NMR) that combines high-throughput NMR screening for protein-ligand complexes (figure 2) with our Comparison of Protein Active-Site Structures (CPASS) database and software. A biological function for a novel protein can be inferred by identifying the ligands that bind the protein, from the identification of the protein's active-site and from a corresponding three-dimensional structure of a protein-ligand structure. The comparison of the identified active-site against the CPASS protein database will permit a function to be assigned based on structural similarities between active-sites.

Figure 2 – Our NMR sample preparation robot is an essential tool for high-throughput protein-ligand screening by NMR.

Similarly, we can follow the in vivo activity of a protein and more excitingly the efficacy of a drug by monitoring changes in metabolite concentrations by NMR. A statistical analysis (principal component) of the NMR data readily identifies correlations between various cell lines and the activity of a drug or protein.

Figure 3 – Principal component analysis (PCA) of NMR-based metabolomics data allows us to follow the in vivo activity of proteins and drugs.