Sequence-specific interactions between proteins and DMA are critical for the expression and maintenance of genomic information. Although genome-wide sequencing projects yield a parts list for protein-DNA interactions, directly in the form of potential binding sites and indirectly in the form of inferred protein sequences, these data do not directly speak to the interactions between these parts. Our long-term goal is to develop a quantitative model for assessing the sequence-specific binding preferences and affinities of DMA-binding proteins. The specific hypothesis behind this research is that accurate modeling and engineering of protein-DNA interactions requires treatment of both DMA and protein flexibility, and physically realistic scoring functions. This is based on several observations. First, purely sequence-based models are only partially successful in predicting binding preferences. Second, structural data indicate that a single amino acid at a well-defined position in a protein-DNA interface can participate in context-dependent interactions due to conformational freedom. Thus, a side chain's ability to move contradicts the common assumption made by sequence-based methods that an amino acid at a given position has a single mode of action. Finally, examination of crystal structures of homologous protein-DNA ^complexes reveals that changes in protein and DNA sequences are accompanied by modest but significant structural rearrangements.
The specific aims i n this proposal are designed to generate a physical model for protein- DNA interactions and to test experimentally the predictions made by this model: 1. To construct a physical model for describing the basis for specificity in protein-DNA interfaces. 2. To generate a model, using physical chemical and statistical mechanical considerations, for the prediction of binding sites for the winged helix family of transcription factors found in two-component signaling pathways. 3. To redesign the DNA binding and cleavage preference of the lAnil homing endonuclease to target genes in Anopheles gambiae, the primary vector for malaria.
| Lyskov, Sergey; Chou, Fang-Chieh; Conchúir, Shane Ó et al. (2013) Serverification of molecular modeling applications: the Rosetta Online Server that Includes Everyone (ROSIE). PLoS One 8:e63906 |
| Borgo, Benjamin; Havranek, James J (2012) Automated selection of stabilizing mutations in designed and natural proteins. Proc Natl Acad Sci U S A 109:1494-9 |
| Leaver-Fay, Andrew; Tyka, Michael; Lewis, Steven M et al. (2011) ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules. Methods Enzymol 487:545-74 |
| Fleishman, Sarel J; Corn, Jacob E; Strauch, Eva M et al. (2010) Rosetta in CAPRI rounds 13-19. Proteins 78:3212-8 |
| Ashworth, Justin; Taylor, Gregory K; Havranek, James J et al. (2010) Computational reprogramming of homing endonuclease specificity at multiple adjacent base pairs. Nucleic Acids Res 38:5601-8 |
| Havranek, James J (2010) Specificity in computational protein design. J Biol Chem 285:31095-9 |
| Thyme, Summer B; Jarjour, Jordan; Takeuchi, Ryo et al. (2009) Exploitation of binding energy for catalysis and design. Nature 461:1300-4 |
| Muratore, Kathryn E; Seeliger, Markus A; Wang, Zhihong et al. (2009) Comparative analysis of mutant tyrosine kinase chemical rescue. Biochemistry 48:3378-86 |
| Havranek, James J; Baker, David (2009) Motif-directed flexible backbone design of functional interactions. Protein Sci 18:1293-305 |
