Page not found

Molecular and Cellular Biosciences at Wake Forest University

Wake Forest University Graduate School » Molecular and Cellular Biosciences

Jacquelyn S Fetrow, Ph.D.

Jacquelyn S Fetrow, Ph.D.

Principal Investigator

Dean of the College of Arts and Sciences
Reynolds Professor of Computational Biophysics
Departments of Physics and Computer Science


Professional Credentials:
  • BS, Albright College
  • PhD, Penn State University
  • Postdoctoral positions:
    • University of Rochester Medical School
    • The Whitehead Instititue for Biomedical Research (MIT)
  • Professional positions:
    • University at Albany, SUNY
    • The Scripps Research Institute
    • GeneFormatics, Inc.
    • Wake Forest University
Teaching Interests:

My teaching interests include Bioinformatics, Physics of Biological Macromolecules, Computational Biophysics Laboratory, General Physics, Research Topics in Structural and Computational Biophysics and Biophysics Journal Club.



Peer-reviewed Publications


    1. Loeser R.F., Olex A.L., McNulty M.A., Carlson C.S., Callahan M., Ferguson C., Chou J., Leng X. and Fetrow J.S. Microarray Analysis Reveals Age-related Differences in Gene Expression During the Development of Osteoarthritis in Mice. Arthritis & Rheumatism, accepted in Sept 2011.
    2. Olex A.L and Fetrow J.S. SC2ATmd: a tool for integration of the figure of merit with cluster analysis for gene expression data.Bioinformatics 2011, 27(9):1330-1331.
    3. Nelson K.J., Knutson S.T., Soito L., Klomsiri C., Poole L.B. and Fetrow J.S. Analysis of the peroxiredoxin family: Using active-site structure and sequence information for global classification and residue analysis. Proteins: Structure, Function, and Bioinformatics, 2011, 79:947�964.


    1. Soito L., Williamson C., Knutson S.T., Fetrow J.S., Poole L.B., and Nelson K.J. PREX: PeroxiRedoxin classification indEX, a database of subfamily assignments across the diverse peroxiredoxin family. Nucleic Acids Res. 2010, Oct 29, [Epub ahead of print], PMID: 21036863
    2. John D.J., Fetrow J.S., and Norris J.L. Continuous Cotemporal Probabilistic Modeling of Systems Biology Networks from Sparse Data. IEEE/ACM Trans Comput Biol Bioinform 2010, Sep 10. [Epub ahead of print], PMID: 20855920
    3. Olex A.L., Hiltbold E.M., Leng X., and Fetrow J.S. Dynamics of dendritic cell maturation are identified through a novel filtering strategy applied to biological time-course microarray replicates. BMC Immunology 2010, Aug 8, 11:41.
    4. Yuan Y., Knaggs M.H., Poole L.B., Fetrow J.S., and Salsbury F.R. Jr. Conformational and oligomeric effects on the cysteine pK(a) of tryparedoxin peroxidase. J Biomol Struct Dyn. 2010, 28(1):51-70


    1. Salsbury, F.R. Jr., Knutson, S.T., Poole, L.B., Fetrow, J.S. Functional site profiling and electrostatic analysis of cysteines modifiable to cysteine sulfenic acid. Protein Sci 2008, 17(2):299-312.


    1. Poole, L.B., Klomsiri, C., Knaggs, S.A., Furdui, C.M., Nelson, K.J., Thomas, M.J., Fetrow, J.S., Daniel, L.W., King, S.B. Fluorescent and affinity-based tools to detect cysteine sulfenic acid formation in proteins. Bioconjug Chem 2007, 18(6):2004-2017.
    2. Michalek, R.D., Nelson, K.J., Holbrook, B.C., Yi, J.S., Stridiron, D., Daniel, L.W., Fetrow, J.S., King, S.B., Poole, L.B., Grayson, J.M. The requirement of reversible cysteine sulfenic acid formation for T cell activation and function. J Immunol 2007, 179(10):6456-6467.
    3. Knaggs, M.H., Salsbury, F.R. Jr., Edgell, M.H., Fetrow, J.S. Insights into correlated motions and long-range interactions in CheY derived from molecular dynamics simulations. Biophys J 2007, 92(6):2062-2079.
    4. Olex, A.L., John, D.J., Hiltbold, E.M., Fetrow, J.S. Additional limitations of the clustering validation method figure of merit. In: 45th ACM Southeast Annual Conference: 2007; Winston-Salem, NC; 2007: 238-243.
    5. Budiman, M.E., Knaggs, M.H., Fetrow, J.S., Alexander, R.W. Using molecular dynamics to map interaction networks in an aminoacyl-tRNA synthetase. Proteins 2007, 68(3):670-689.


    1. Baxter, S.M., Day, S.W., Fetrow, J.S., Reisinger, S.J. Scientific software development is not an oxymoron. PLoS Comput Biol2006, 2(9):e87.
    2. Allen, E.E., Fetrow, J.S., John, D.J., Pecorella A. and Turkett, W. Re-constructing networks using co-temporal functions.Proceedings of the 44th ACM Southeast Conference, (Marius Silaghi, ed), Melbourne, Florida. March 2006, 417-422.
    3. Knaggs, M.H., Salsbury, F.R., Edgell, M.H., Fetrow, J.S. Insights into CheY relaxation and relaxation derived from molecular dynamics simulations. Biophys. J. [Epub ahead of print 2006 Dec 15]
    4. Fetrow, J.S. and John, D.J. Bioinformatics and computing curriculum: A new model for interdisciplinary courses. Inroads--SIGSCE Bulletin. 2006. 38:185-190.
    5. Fetrow, J.S., Knutson, S.T. and Edgell, M.H. Mutations in α-helical solvent exposed sites of eglin c have long-range effects: evidence from molecular dynamics simulations. Proteins: Struct Funct Bioinform. 2006 May 1;63(2):356-72. [Epub 2005 Dec 9]
    6. Allen, E.E., Fetrow, J.S., Daniel, L.W., Thomas, S.J., John, D.J. Algebraic dependency models of protein signal transduction networks from time-series data. J. Theor. Biol. 2006 Jan 21;238(2):317-30. [Epub 2005 Jul 5]


    1. Huff, R. G., Bayram, E., Tan, H., Knutson, S.T., Knaggs, M.H., Richon, A.B., Santago II, P., and Fetrow, J.S. Chemical and Structural Diversity in Cyclooxygenase Protein Active Sites. Chemistry and Biodiversity. 2005. 2:1533-1552.
    2. Allen, E.E., Fetrow, J.S., John, D.J., Thomas, S.J. Heuristic dependency conjectures in proteomic signaling pathways.Proceedings of the 43 rd Annual Association for Computing Machinery Southeast Conference (Victor A. Clincy, ed.) Kennesaw, Georgia, March 2005.


    1. Baxter, S.M., Rosenblum, J.S., Knutson, S.T., Nelson, M.R., Montimurro, J.S., Di Gennaro, J.A., Speir, J.A., Burbaum, J.J. and Fetrow, J.S. Synergistic computational and experimental proteomics approaches for more accurate detection of active serine hydrolases in yeast. Mol Cell Proteomics. 2004 Mar;3(3):209-25.


    1. Cammer, S.A., Hoffman, B.T., Speir, J.A., Canady, M., Nelson, M.R., Knutson, S.T., Gallina, M., Baxter, S.M., and Fetrow, J.S. Structure-based active site profiles for genome analysis and sub-family classification. J. Mol. Biol. 2003 Nov 28;334(3):387-401.
    2. Herrgard, S., Cammer, S.A., Speir, J.A., Hoffman, B.T., Knutson, S., Gallina, M., Fetrow, J.S., Baxter, S.M. Prediction of deleterious functional effects of amino acid mutations using a library of structure-based function descriptors. Proteins 2003, 53(4):806-816.
    3. Zhou, H., Gallina, M., Mao, H., Betz, S.F., Fetrow, J.S., and Domaille, P.J. 1H, 13C, and 15N resonance assignments and secondary structure for the human protein tyrosine phosphatase, PRL-2. J. Biomol. NMR. 2003 27(4):397-398.


    1. DeWeerd, K., Grigoryants, V., Sun, Y., Fetrow, J.S., Scholes, C.P. EPR-detected folding kinetics of externally located cysteine-directed spin-labeled mutants of iso-1-cytochrome cBiochemistry 2001 Dec 25;40(51):15846-15855.
    2. Di Gennaro, J.A., Siew, N., Hoffman, B.T., Zhang, L., Skolnick, J., Neilson, L.I., Fetrow, J.S. Enhanced functional annotation of protein sequences via the use of structural descriptors. J Struct Biol. 2001 May-Jun;134(2-3):232-245.
    3. Fetrow, J.S., Siew, N., Di Gennaro, J.A., Martinez-Yamout, M., Dyson, H.J., Skolnick, J. Genomic-scale comparison of sequence- and structure-based methods of function prediction: does structure provide additional insight? Protein Sci. 2001 May;10(5):1005-1014.


    1. Fetrow, J.S., Siew, N., and Skolnick, J. Structure-based functional motif identifies a potential disulfide oxidoreductase active site in the serine-threonine protein phosphatase-1 subfamily. FASEB J. 1999 Oct;13(13):1866-1874.
    2. Skolnick, J., Fetrow, J., Ortiz, A.R., and Kolinski, A. The role of computational biology in the genomics revolution Proceedings of the NRC Chemical Sciences Roundtable Workshop on the Impact of Advances in Computing and Communications Technologies on Chemical Sciences and Technology. 1999 44-61.
    3. Zhang, B., Rychlewski, L., Pawlowski, K., Fetrow, J. S., Skolnick, J., Godzik, A. From fold predictions to function predictions: Automation of functional site conservation analysis for functional genome predictions. Protein Sci. 1999 May;8(5):1104-1115.
    4. Fetrow, J.S. and Baxter, S.M. Assignment of 15N chemical shifts and 15N relaxation measurements for oxidized and reduced iso-1-cytochrome c. Biochemistry. 1999 Apr 6;38(14):4480-4492.
    5. Baxter, S.M. and Fetrow, J.S. Hydrogen exchange behavior of [ U- 15N]-labeled oxidized and reduced iso-1-cytochrome c.Biochemistry. 1999 Apr 6;38(14):4493-4503.
    6. Fetrow, J.S. and Berg, G. Using information theory to discover side chain rotamer classes: Analysis of the effects of local backbone structure. Proceedings of the Pacific Symposium on Biocomputing ’98, World Sci. Publ. Pac Symp Biocomput. 1999 278-289.


    1. Zhang, L., Godzik, A., Skolnick, J., Fetrow, J. Functional analysis of Escherichia coli proteins for members of the a / b hydrolase family. Fold Des. 1998 3(6):535-548.
    2. Fetrow, J., Godzik, A. and Skolnick, J. Functional analysis of the Escherichia coli genome using the sequence-to-structure-to-function paradigm: Identification of proteins exhibiting the glutaredoxin/thioredoxin disulfide oxidoreductase activity. J. Mol. Biol. 1998 Oct 2;282(4):703-711.
    3. Fetrow, J.S. and Skolnick, J. Method for prediction of protein function from sequence using the sequence-to-structure-to-function paradigm with application to glutaredoxins/thioredoxins and T1 ribonucleases. J. Mol. Biol. 1998 Sep 4;281(5):949-968.
    4. Fetrow, J.S. and Godzik, A. Function driven protein evolution: A possible proto-protein for the RNA-binding proteins.Proceedings of Pacific Symposium on Biocomputing (Ed. R.B. Altman, A.K. Dunker, L. Hunter T. Klein). 1998 485-496.
    5. Fetrow, J.S., Spitzer, J.S., Gilden, B.M., Mellender, S.J., Begley, T., Haas, B., and Boose, T.L. Structure, function, and temperature sensitivity analysis of directed, random mutants of proline 76 and glycine 77 in omega loop D of yeast iso-1-cytochrome cBiochemistry.1998;37(8):2477-2487.
    6. Fetrow, J.S., Schaak, D.L., Dreher, U., Wiland, D.J., and Boose, T.L. Mutagenesis of histidine 26 demonstrates the importance of loop-loop and loop-protein attachments for the function of iso-1-cytochrome cProtein Sci . 1998 27(4):994-1005.
    7. Baxter, S.M., Boose, T.L., and Fetrow, J.S. 15N isotopic labeling and amide hydrogen exchange rates of oxidized iso-1-cytochrome cJ. Am. Chem. Soc. 1998 119(41):9899 -9900.
    8. Qu, K. Vaughn, J.L., Sienkiewicz, A. Scholes, C.P., and Fetrow, J.S. Kinetics and motional dynamics of spin labeled yeast iso-1-cytochrome c: 1. Stopped-flow EPR as a probe for protein folding/unfolding of the C-terminal helix spin labeled at cysteine 102. Biochemistry. 1998 36(10):2884-2897.

Invited Articles and Reviews

  1. Fetrow, J.S. Active site profiling to identify protein functional sites in sequences and structures using the Deacon Active Site Profiler (DASP). Current Protocols in Bioinformatics 2006, Chapter 8:Unit 8 10.
  2. Creamer, T.P. and Fetrow, J.S. Rose is a Rose is a Rose. Especially if you're a George. A Perspectives article in Proteins Struct. Funct. Bioinformatics. 2006 May 1;63(2):268-72.
  3. Baxter, S., Knutson, S. and Fetrow, J.S. The importance of structure-based function annotation to drug discovery. Protein Structure Determination, Analysis and Modeling for Drug Discovery. D. I. Chasman, Ed., Dekker Publishing. 2003. p. 369-387.
  4. Fetrow, J., Giammona, D.A., Kolinski, A., Skolnick, J. The protein folding problem, a biophysical enigma. Curr Pharma Biotech. 2002;3(4):329-47.
  5. Betz, S., Baxter, S., Fetrow, J.S. Function first: a powerful approach to post-genomic drug discovery.
    Drug Discov Today. 2002;7(16):865-871.
  6. Baxter, S.M., Fetrow, J.S. Sequence- and structure-based protein function prediction from genomic information. Curr Opin Drug Discov Devel. 2001 May;4(3):291-295.
  7. Skolnick, J., Fetrow, J.S., Kolinski, A. Structural genomics and its importance for gene function analysis. Nature Biotechnology. 2000 Mar;18(3):283-287.
  8. Skolnick, J. and Fetrow, J.S. From genes to structure: novel applications of computational approaches in the genomic era. Trends in Biotech. 2000 Jan;18(1):34-39.
  9. Rudd, P.M., Wormald, M.R., Stanfield, R. Huang, M., Mattson, N., Speir, J.A., Di Gennaro, J.A., Fetrow, J.S., Dwek, R.A., and Wilson, I.A. Roles for glycosylation of cell surface receptors involved in cellular immune recognition. J. Mol. Biol. 1999 Oct 22;293(2):351-366.
  10. Fetrow, J.S. Omega Loops: Nonregular secondary structures significant in protein function and stability. FASEB J. 1995 Jun;9(9):708-717.
  11. Zhang, X., Fetrow, J.S., and Berg, G. Design of an Auto-associative Neural Network with Hidden Layer Activations that were used to Reclassify Local Protein Structures. (1994) Advances in Protein Chemistry V. J. Crabb, ed. p. 397-404.
  12. Fetrow, J. Molecular Modeling. In: Investigations in Modern Biology, 6th edition (A. Jacklet, ed.), Morton Publishing Co.; Englewood, Colorado. (Macromolecular modeling exercises for freshman biology laboratories) 1994:205-222.
  13. Fetrow, J.S. and Bryant, S.H. New programs for protein tertiary structure prediction. Biotechnology. 1993 Apr;11(4):479-484.
  14. Fetrow, J.S. and Mulligan, P. Properties of cytochrome c hybrid proteins expressed in Bakers yeast. NIH Conference, Research Opportunities in Biomolecular Engineering: The Interface between Chemical Engineering and Biology. Washington DC, December 7-8, 1992. Invited participant and poster presenter.
  15. Fetrow, J.S., Zehfus, M.H. and Rose, G.D. Protein folding—new twists. Bio/Technology. 1988;6:167-171.

Patents and Patent Applications

  1. Sulfenic Acid-Reactive Compounds And Their Methods Of Synthesis And Use In Detection Or Isolation Of Sulfenic Acid-Containing Chemicals Or Proteins. US Patent Application Serial No. 60/620,263. Inventors: Poole, L.B., King, S.B., and Fetrow, J.S. Provisional application submitted October 2004; application submitted October 2005.
  2. Methods and Systems for Predicting Protein Function. US99/11913. Inventors: Skolnick, J. and Fetrow, J.S. US Patent #6,631,332, issued 10/7/03.
  3. Functional Site Profiles for Proteins and Methods of Making and Using Same. US027/23166. Inventors: Fetrow, J.S., Baxter, S.M., Hoffman, B.T., and Cammer, S.A. Patent application submitted.


General Research Interests of the Group:

  • Structural and Computational Biophysics
    • Protein electrostatics
    • Allostery and long-range communication in proteins
    • Protein motion/dynamics
  • Understanding Biochemical Mechanisms
    • Protein structure and function relationships
    • Protein active site/functional site characterization and analysis
    • Classification of enzymes
    • Role of cysteine modifications
  • Systems Biology/Understanding Biological Systems and Processes
    • Cell signaling pathways involving protein modification
    • Computational algebra and Bayesian network modeling of time course data
    • Microarray analysis of gene expression data
    • Clustering microarray data
  • Bioinformatics
    • Development and implementation of novel computational methods to analyze biological data

The Fetrow Group research focuses on understanding how proteins work in the cell by studying the intricate relationships that exist between protein function and structure, involving communication networks both within the protein and between proteins. To achieve this the group is developing methods and tools to aid in the early stages of drug discovery using Bioinformatics, Computational Biophysics and Systems Biology approaches. Some of the research underway includes the characterization and classification of enzyme functional sites, which provides information on the functional relationships between proteins, and can thus aid in the design of specific enzyme inhibitors. The methods we are developing can be used to quickly classify structures or sequences based on mechanistic determinants, contributing to the efforts to more accurately characterize unannotated or misannotated proteins. Other major research projects focus on using computational algebra or Bayesian techniques to model biological networks from time course data, such as gene expression or protein phosphorylation data. These techniques provide a fast way to discover dependencies in interaction networks involving modification of the proteins involved, which aids in the discovery of potential drug targets. In addition to these projects we also participate in research focused on the identification of biomarkers for specific diseases and exploratory research aimed at gaining a better understanding of certain biological systems.

All of our research requires a seamless integration of computational and biological techniques; thus, interdisciplinary collaboration is a very important part of the research done by our group. On-going collaborations include the departments of Computer Science, Biology, Mathematics, Biochemistry, Physics, Microbiology and Immunology, Internal Medicine (Molecular Medicine), and others. We also value collaboration with other universities and research facilities and currently have relations with Wake Forest University Baptist Medical Center, Virginia Tech, University of Minnesota, SUNY Buffalo, University of North Carolina in Chapel Hill, and University of California in San Francisco.