Robert Powers


Professor

Educational Background
Postdoctoral, NIH-NIDDK, Bethesda, MD
Ph.D. Purdue University
B.A. Rutgers University

Research Interests
NMR Spectroscopy, Structural Biology


Powers Research Group
Current Research | Publications | Prospective Students


Robert Powers
Hamilton Hall 722
402.472.3039
rpowers3@unl.edu

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).

A.figA
B.figB
C.figC
D.figD
E.figE
 
Figure 1 – Examples of some of our recent NMR protein structures. (A) Archaeglobus fulgidis Peptidyl-tRNA Hydrolase (PDB ID 1rzw), (B) Pseudomonas putida protein PpPutA45 and its DNA Complex (PDB ID 2jxg, 2jxh, 2jxi), (C) Pseudomonas aeruginosa protein PA1324 (PDB ID 1xpn), (D) protein YndB from Bacillus subtilis (PDB ID 2kte) and, (E) Staphylococcus aureus C-terminal domain of primase.

 

We are developing the Functional Annotation Screening Technology by NMR (FAST-NMR) that combines high-throughput NMR screening for protein-ligand complexes with our Comparison of Protein Active-Site Structures (CPASS) database and software (http://cpass.unl.edu/) and our PROFESS (Protein Function Evolution Structure Sequence) database (http://cse.unl.edu/~profess/). 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. Similarly, PROFESS integrates numerous databases and provides extensive information related to protein structure and function. Recently, FAST-NMR has been expanded to include the similarity between ligand-binding profiles (set of ligands that bind a protein) to infer function.

CPASS   PROFESS

Figure 2 – Screen images from our CPASS and PROFESS databases.

 

We have also developed the differential NMR metabolomics method that 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. Also, we have developed metabolomic tree diagrams that provide quantitative measurement of the significance of clustering patterns in PCA scores plot. The inclusion of 13C-labled metabolites allows us to identify and quantify metabolite changes and construct a metabolite network.

fig3a
fig3b
fig3c
 

Figure 3 – Principal component analysis (PCA) of NMR-based metabolomics data allows us to follow the in vivo activity of proteins and drugs. Metabolomic tree diagrams simplify the analysis of PCA scores plot and metabolomic networks provide a visual interpretation of the details of the observed metabolome changes.

For more information, please visit the Powers Research Group Homepage.



Selected Publications

S. Halouska, R. Fenton, O. Barletta-Chacon, R. Barletta and R. Powers (2012) "Predicting in vivo Mechanisms of Action from NMR Metabolomics", ACS Chem. Biol., 7(1):166-171.

B. Worley, G. Richard, G. S. Harbison and Robert Powers (2012) "13C NMR Reveals No Evidence of n - π* Interactions in Proteins", PLoS ONE, 7(8): e42075.

B. Zhang and R. Powers (2012) "Analysis of bacterial biofilms using NMR-based metabolomics", Future Med. Chem., 4(10):1273-1306.

T. Gebregiworgis and R. Powers (2012) Application of NMR Metabolomics to Search for Human Disease Biomarkers, Comb. Chem. High Throughput Screening, in press.

N. V. Chaika, M. E. Behrens, T. Gebregiworgis, P. Radhakrishnan, B. Zhang, X. Liu, V. Purohit, K. Mehla, T. Caffrey, F. Yu, K. R. Johnson, R. Powers, M. A. Hollingsworth and P. K. Singh (2012) MUC1 stabilizes and activates HIF1α to regulate metabolism in pancreatic cancer., Proc. Natl. Acad. Sci. U. S. A., in press.

Complete list of publications