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Olivier Lichtarge
Baylor College of MedicineDepartment: Molecular and Human Genetics, and Biochemistry and Molecular BiologyAddress: One Baylor Plaza, T921 Houston, TX 77030 Phone: 713-798-5646 Fax: 713-798-1116 Email: lichtarge@bcm.tmc.edu Web: mammoth.bcm.tmc.edu/ |
Education
B.S. Math. & Physics, McGill University (1980)
Ph.D. Biophysics, Stanford (1987), M.D., Stanford (1990)
Post Doc. Molecular Pharmacology, UCSF (1997)
Internal Medicine, UCSF (1993); Endocrinology, UCSF (1996)
Honors
First Class Joint Honors in Mathematics and Physics (1980)
Dorothy Penrose Stout Fellowship Award, American Heart Association (1996)
Basil O�Connor Career Development Award, March of Dimes (2001)
Raymond and Beverley Sackler Fellowship, IHES, France (2005)
Research Topic
Annotation and Designed Perturbation of Protein Function and Pathways
Research Description
The primary goal of our bioinformatics laboratory is to understand how protein functional surfaces control critical events, such as binding, catalysis and active complex assembly. To address this problem typically requires exhaustive and expensive mutational analysis in the wetlab. Here instead, we analyze the mutational "experiments" already performed during evolution and recorded in sequence databases.
Specifically, we have developed a method of sequence analysis that identifies, among divergently related proteins, patterns of sequence variations that correlate with functional divergence. This evolutionary trace method (ET) ranks amino acids in a protein by their evolutionary (and presumably functional) importance. As a consequence of this ranking, it becomes possible to locate functional surfaces on a structure, probe the molecular details of active site function and specificity, and recognize cryptic functional commonalties in distantly related proteins.
We are using this new approach to probe G protein-mediated signaling, and transcriptional regulation by intracellular hormone receptors. Our focus in those systems is 1) to model and understand the mechanisms of G protein-coupled receptors; 2) to characterize interactions between these receptors and the G proteins; and 3) to decipher the origin of recognition specificity between transcriptional factors and their response elements. In turn, these systems are test beds for computational tools that can be used broadly to study helical transmembrane receptors, protein-protein interactions and protein-DNA interactions.
Most generally, we note that genome projects, growing protein structure databases and DNA chip technologies are now bringing to bear unprecedented amounts of data to fundamental problems in structural biology (protein structure prediction) and in genomics (gene function prediction). At the same time, these massive data overwhelm conventional means of analysis. For these reasons, our broad goal is to develop a new generation of bioinformatics methods, such as the evolutionary trace, that integrate sequence-structure-function data and turn them into new insights in gene expression and protein function.
Selected Publications
- Ribes-Zamora, A., I. Mihalek, O. Lichtarge, and A. A. Bertuch (2007) Distinct faces of the Ku heterodimer mediate DNA repair versus telomeric functions. Nature Struct and Mol. Bio. 14:301-7
- 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 22:2049-50.
- Kristensen, D.M., Chen, B., Fofanov,V., Ward, R.M., Lisewski, A.M., Kimmel, M., Kavraki, L., Lichtarge. O. (2006). Recurrent Use of Evolutionary Importance for Functional Annotation of Proteins Based on Local Structural Similarity. Protein Science 15:1530-6
- Raviscioni, M., Gu, P., Sattar, M., Cooney A.J., Lichtarge, O. (2005) Correlated evolutionary pressure at interacting transcription factors and DNA response elements can guide the rational engineering of DNA binding specificity. J. Mol. Biol, 350:402-15. COVER illustration
- Peili Gu*, P., Morgan, D.H.*, Sattar, M., Raviscioni, M., Lichtarge, O., Cooney, A.J. (2005). Evolutionary Trace Based Peptides Identify a Novel Asymmetric Interaction That Mediates Oligomerization in Nuclear Receptors. J. Biol. Chem. 280:31818-29.
- Madabushi, S., Gross, A., Philippi, A., Meng, E.C., Wensel, T.G., Lichtarge, O. (2004) Signaling Determinants Reveal Functional Subdomains in the Transmembrane Region of G Protein-Coupled Receptors. J. Biol. Chem. 279: 8126-8132.
- Mihalek, I., Res, I., Yao, H. and Lichtarge, O. (2003). Combining inference from evolution and geometric probability in protein structure evaluation. J. Mol. Biol. 331: 263-279.
- Yao, H., Kristensen, D.M., Mihalek, I., Sowa, M.E., Shaw, C., Kimmel, M., Kavraki, L. and Lichtarge, O. (2003). An accurate, scalable method to identify functional sites in protein structures. J. Mol. Biol. 326: 255-261.
- Madabushi, S., Yao, H., Marsh, M., Philippi, A., Kristensen, D., Sowa, M.E. andLichtarge, O*. (2002). Structural Clusters of Evolutionary Trace Residues are Statistically Significant and Widespread in Proteins. J. Mol. Biol. 316: 139-153. COVER.
- Lichtarge, O.* and Sowa, M.E. (2002). Evolutionary Predictions of Binding Surfaces and Interactions. Curr. Opin. Struct. Biol. 12: 21-27.
- Sowa, M.E., Wei H., Slep, K.C., Kercher, M.A., Lichtarge, O.* and Wensel, T.G. (2001). Prediction and Confirmation of an allosteric pathway for regulation of RGS domain activity. Nat. Struct. Biol. 8: 234-237. COVER.
- Sowa, M.E., He, W., Wensel, T.G. and Lichtarge, O*. (2000). Identification of a General RGS-Effector Interface. Proc. Natl. Acad. Sci. U.S.A. 97: 1483-1488.
- Lichtarge, O., Bourne, H.R. and Cohen, F.E. (1996). The Evolutionary Trace Method Defines the Binding Surfaces Common to a Protein Family. J. Mol. Biol. 257: 342-358. COVER.
Lab Members
Current Graduate Students
Former Grad Students
Current Post Docs
Former Post Docs
Lab Photos
Last edited on: September 21, 2009