Olivier Lichtarge, M.D., Ph.D.
Professor, Molecular & Human Genetics,
Biochemistry & Molecular Biology;
Programs in Developmental Biology, Cell & Molecular Biology, and Structural & Computational Biology, and Molecular Biophysics
Director, Center of Computational and Integrative Biomedical Research
Education and Awards
- B.S., McGill University, Canada, 1980
- Ph.D., Stanford University, 1987
- M.D., Stanford University, 1990
- Resident in Internal Medicine, University of California at San Francisco, 1996
- Fellow in Endocrinology, University of California at San Francisco, 1996
- Postdoc, University of California at San Francisco, 1997
Our lab marries computation with experiments to study three areas of protein structure-function: the molecular basis of protein catalysis and interaction, the design of peptides and proteins, and the annotation of protein sequence and structure. In each case, our long-term goals are to engineer proteins or peptides to probe and then rationally disrupt protein pathways.
To guide experiments, we rely on an integrated computational analysis of the evolution of protein sequences, structures, and functions. This phylogenomic strategy is called the Evolutionary Trace (ET) and, most simply, it assigns to each sequence residue a relative score of “functional importance”. From this we can formulate hypotheses on the molecular determinants of activity and specificity, and rationally target experiments to the most relevant sites of a protein.
In the G protein signaling pathway, one example of this approach is a G protein-coupled receptor engineered to signal through the ERK/MAPK pathway but not through the typical G protein mechanism (Shenoy et al., 2006). Another example is an RGS7 mutant designed to shut off G protein signaling as if it were and RGS9 (Sowa et al., 2001). Likewise in nuclear hormone receptors and bHLH transcription factors, targeted mutations enabled us to swap DNA binding (Raviscioni et al., 2005) and in vivo proneural development (Quan et al., 2004), respectively. Finally, Evolutionary Trace-based peptides let us mimic a protein-protein interaction surface and disrupt normal binding in Germ Cell Nuclear Transcription Factor (GCNF4).
Thus while our computational aims are to improve the general annotation of function on a proteomic scale, our experimental projects aim to characterize molecular mechanisms in protein families of intense pharmaceutical interest. The hope is that computation and design, together, can lead to novel drug targets and to novel approaches for the development of therapeutics.
- ETAscape: analyzing protein networks to predict enzymatic function and substrates in Cytoscape. Bachman BJ, Venner E, Lua RC, Erdin S, Lichtarge O. Bioinformatics. 2012 Jun 11. [Epub ahead of print]
- The use of evolutionary patterns in protein annotation. Wilkins AD, Bachman BJ, Erdin S, Lichtarge O. Curr Opin Struct Biol. 2012 Jun;22(3):316-25.
- Evolutionary trace for prediction and redesign of protein functional sites. Wilkins A, Erdin S, Lua R, Lichtarge O. Methods Mol Biol. 2012;819:29-42.
- Separation of recombination and SOS response in Escherichia coli RecA suggests LexA interaction sites. Adikesavan AK, Katsonis P, Marciano DC, Lua R, Herman C, Lichtarge O. PLoS Genet. 2011 Sep;7(9):e1002244.
- Desmosterolosis-phenotypic and molecular characterization of a third case and review of the literature. Schaaf CP, Koster J, Katsonis P, Kratz L, Shchelochkov OA, Scaglia F, Kelley RI, Lichtarge O, Waterham HR, Shinawi M. Am J Med Genet A. 2011 Jul;155A(7):1597-604. Review.
- Protein function prediction: towards integration of similarity metrics. Erdin S, Lisewski AM, Lichtarge O. Curr Opin Struct Biol. 2011 Apr;21(2):180-8.
- Accurate protein structure annotation through competitive diffusion of enzymatic functions over a network of local evolutionary similarities. Venner E, Lisewski AM, Erdin S, Ward RM, Amin SR, Lichtarge O. PLoS One. 2010 Dec 13;5(12):e14286.
- PyETV: a PyMOL evolutionary trace viewer to analyze functional site predictions in protein complexes. Lua RC, Lichtarge O. Bioinformatics. 2010 Dec 1;26(23):2981-2.
- Sequence and structure continuity of evolutionary importance improves protein functional site discovery and annotation. Wilkins AD, Lua R, Erdin S, Ward RM, Lichtarge O. Protein Sci. 2010 Jul;19(7):1296-311.
- Evolution: a guide to perturb protein function and networks. Lichtarge O, Wilkins A. Curr Opin Struct Biol. 2010 Jun;20(3):351-9. Review.