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David Kristensen Baylor College of Medicine Department: Bioinformatics Address: Stowers Institute for Medical Research 1000 E. 50th St. • Kansas City, MO 64110 Phone: 713-798-7677 Fax: Email: dk131363@gmail.com Web:

Education

B.S. (Honors) Biology, Univerisity of Missouri - Kansas City (2000)
Ph.D. Structural & Computational Biology and Molecular Biophysics, Baylor College of Medicine (2007)
Postdoctoral Research Associate, Stowers Institute for Medical Research (current)

Honors

2004 Graduate Student Symposium SCBMB speaker
2002 Best SCBMB Poster – 2002 CMB & SCBMB Research Conference
2001-2004 WM Keck Center for Computational Biology Pre-doctoral fellow
1997-2000 National Dean's List (top 0.5% of nation)
1996-2000 Curator's Scholarship, University of Missouri - Kansas City,
1996-2000 Missouri Higher Education Academic Scholarship Award
1994 Eagle Scout w/ silver palm and other honors, Boy Scouts of America

Research Topic

Large Scale Discovery and Annotation of Functional Sites in Protein Structures

Research Description

The PDB now contains several thousand protein structures, with several more on the way. However, generally these structures are only useful if their biological function is known. In fact, the structures are most useful when the function can be mapped to certain key residues in the active site of the protein. For instance, rational drug design, whereby a small molecule is designed to fit into and interact with the active site, requires knowledge of the functionally important residues on the surface of the protein. The Evolutionary Trace method, invented by Dr. Lichtarge, was designed to determine such information for a single protein. This project seeks to expand the scope of that procedure to include all the proteins in the PDB in order to create a web-accessible database of functionally important residues on protein surfaces. Doing so will require the creation of several major new computational tools to automate the Evolutionary Trace and quality control procedures. In addition, measures will be taken to insure that the database can grow alongside the mass of structural and sequence information. The database will then be used as a springboard to further understand the structure/function relationship in proteins. For example, active site templates will be extracted from the database and, with the addition of 3D geometrical matching algorithms, will be developed to search for molecular mimicry in new protein structures. However, even without extensions, the database of active sites, once created, will be immediately useful in the study of structure/function relationships and in other fields. For instance, the database will provide researchers with the ability to target experiments directly at the residues of highest functional significance in a protein.

Selected Publications

• D.M. Kristensen, R.M. Ward, A.M. Lisewski, B.Y. Chen, V.Y. Fofanov, M. Kimmel, L.E. Kavraki, and O. Lichtarge. (in preparation). Enzyme Function Prediction with 3D-Templates of Evolutionarily Important Amino Acids.
• D.M. Kristensen and O. Lichtarge. (in preparation). A Proteomic-Scale Survey of Functional Residues in Protein Structures Using a Database of Functional Sites.
• Morgan, D.H., D.M. Kristensen, D. Mittleman, and O. Lichtarge. (2006). ET Viewer: An Application for Predicting and Visualizing Functional Sites in Protein Structures. Bioinformatics. Aug 15;22(16):2049-50.
• Chen, B.Y., D.H. Bryant, V. Y. Fofanov, D.M. Kristensen, A.E. Cruess, M. Kimmel, O. Lichtarge, and L.E. Kavraki. (2006). Cavity-Aware Motifs Reduce False Positives in Protein Function Prediction. Proceedings of the 2006 IEEE Computational Systems Bioinformatics Conference (CSB 2006), pp. 311-23. Palo Alto, CA, August 2006.
• Kristensen, D.M., B.Y. Chen, V.Y. Fofanov, R.M. Ward, A.M. Lisewski, M. Kimmel, L.E. Kavraki, and O. Lichtarge. (2006). Recurrent Use of Evolutionary Importance for Functional Annotation of Proteins Based on Local Structural Similarity. Protein Science special section on Automated Function Prediction. 15:1530–1536.
• Chen, B.Y., V.Y. Fofanov, D.H. Bryant, B.D. Dodson, D.M. Kristensen, A.M. Lisewski, M. Kimmel, O. Lichtarge, and L.E. Kavraki. (2006). Geometric Sieving: Automated Distributed Optimization of 3D-Motifs for Protein Function Prediction. Proceedings of The Tenth Annual International Conference on Computational Molecular Biology (RECOMB 2006). Venice, Italy, April 2006.
• Chen, B.Y., V.Y. Fofanov, D.M. Kristensen, M. Kimmel, O. Lichtarge, L.E. Kavraki. (2005). Algorithms for Structural Comparison and Statistical Analysis of 3-D Protein Motifs. Proceedings of The Pacific Symposium on Biocomputing (PSB 2005), pp. 334-345, World Scientific. Big Island, HI, January 2005.
• Trakhanov, S., N.K. Vyas, D.M. Kristensen, J. Ma, and F.A. Quiocho. (2005). Ligand-free and Bound Structures of the Binding Protein (LivJ) of the E. coli ABC Leu/Ile/Val Transport System: Trajectory and Dynamics of the Interdomain Rotation and Ligand Specificity. Biochemistry. J Biol Chem. 44(17):6597-608.
• Overman, S.A., D.M. Kristensen, P. Bondre, B. Hewitt, and G.J. Thomas, Jr. (2004) Effects of Virion and Salt Concentrations on the Raman Signatures of Filamentous Phages fd, Pf1, Pf3, and PH75. Biochemistry. 43(41):13129-13136.
• Lichtarge, O., H. Yao, D.M. Kristensen, S. Madabushi and I. Mihalek. (2003). Accurate and scalable identification of functional sites by evolutionary tracing. J. Struct. Func. Gen. 4(2-3):159-166.
• *Yao, H., *D.M. Kristensen, I. Mihalek, M.E. Sowa, C. Shaw, M. Kimmel, L. Kavraki and O. Lichtarge. (2003) An Accurate, Sensitive, and Scalable Method to Identify Functional Sites in Protein Structures. J Mol Biol. Feb 7;326(1):255-61. (* These authors contributed equally to this work).
• Madabushi, S., H. Yao, M. Marsh, D.M. Kristensen, A. Philippi, M.E. Sowa and O. Lichtarge. (2002) Structural clusters of evolutionary trace residues are statistically significant and common in proteins. J Mol Biol. Feb 8;316(1):139-54.

Last edited on: November 15, 2007