Olivier Lichtarge, M.D., Ph.D.
Professor, Departments of Molecular & Human Genetics and Biochemistry & Molecular Biology
Ph.D., Stanford University
M.D., Stanford University
Resident in Internal Medicine, University of California at San Francisco
Fellow in Endocrinology, University of California at San Francisco
Postdoc, University of California at San Francisco
Rational re-design of protein function to control cellular pathways
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.
Examples that one may be able to use this approach in order to rationally modify proteins or design peptides that block, or re-wire, specific interactions in cellular pathways, one at a time. In the G protein signaling pathway, a G protein-coupled receptor was 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) (Gu et al. 2005). These examples thus suggest that ET offers a simple and effective strategy to dissect molecular networks.
Specific computational projects focus on the refinement and automation of the Evolutionary Trace, on the computational annotation of function, and on data integration on a proteomic scale. Our experimental focus is on the molecular mechanisms of G protein signaling, nuclear receptors, and kinases, through collaborations, and on interactions among essential gene products in bacteria, in our own wetlab. Since all these proteins are of pharmaceutical interest, we thus hope that computation and design can together lead to novel drug targets and to novel approaches for the development of therapeutics.
Ribes-Zamora A, Mihalek I, Lichtarge O, Bertuch AA (2007). Distinct faces of the Ku heterodimer mediate DNA repair and telomeric functions. Nat. Struct. Mol. Biol. 14: 301-307.
Raviscioni M, He Q, Salicru EM, Smyth CL, Lichtarge O (2006). Evolutionary identification of a subtype specific functional site in the ligand binding domain of steroid receptors. Proteins 64:1046-1057.
Shenoy SK, Drake MT, Nelson CD, Houtz DA, Xiao K, Madabushi S, Reiter E, Premont RT, Lichtarge O, Lefkowitz RJ (2006). Beta-arrestin-dependent, G protein-independent ERK1/2 activation by the beta2 adrenergic receptor. J. Biol. Chem. 281: 1261-1273.
Raviscioni M, Gu P, Sattar M, Cooney AJ, 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: 402-415.
Gu P, Morgan DH, Sattar M, Xu X, Wagner R, Ravisconi M, Lichtarge O, Cooney AJ (2005). Evolutionary trace-based peptides identify a novel asymmetric interaction that mediates oligomerization in nuclear receptors. J. Biol. Chem. 280: 31818-31829.
Madabushi S, Gross AK, Philippi A, Meng EC, Wensel TG, Lichtarge O (2004). Signaling Determinants Reveal Functional Subdomains in the Transmembrane Region of G Protein-Coupled Receptors. J. Biol. Chem. 279: 8126-8132.
Yao H*, Kristensen DM*, Mihalek I, Sowa ME, Shaw C, Kimmel M, Kavraki L, 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, Kristensen D, Philippi A, Sowa ME, Lichtarge O (2002). Structural Clusters of Evolutionary Trace Residues Are Statistically Significant and Common in Proteins. J. Mol. Biol. 316: 139-154.
Lichtarge O, Sowa ME (2002). Evolutionary Predictions of Binding Surfaces and Interactions. Curr. Opin. Struct. Biol. 12: 21-27.
Sowa ME, Wei He, Slep KC, Kercher MA, Lichtarge O, Wensel TG (2001). Prediction and confirmation of an allosteric pathway for regulation of RGS domain activity. Nat. Struct. Biol. 8: 234-237.
For more publications, see listing on PubMed.
Tel: (713) 798-5646
Fax: (713) 798-5386