CAREER: Mapping Biological Networks

Johns Hopkins University, Baltimore MD

Investigators

Abstract

Obtaining the genome sequence of an organism provides a blueprint, but not one that we yet know how to read. The instructions encoded by regulatory DNA remain particularly obscure. This CAREER project will advance the mapping of biological networks. Specific interactions between protein transcription factors and DNA regulatory elements will be predicted purely from genome sequence and inferred protein structure using all-atom, explicit solvent simulations of transcription factors bound to DNA. Advances in molecular force-fields and simulation algorithms, increases in computer speed, and homologous binding modes within transcription factor families make this a feasible goal. New algorithms will be developed for protein-DNA simulations and binding site predictions. Binding sites for members of selected gene families will be determined, with the vision of enabling a prediction for every family member within a genome. In a complementary effort, the human protein-protein interaction network will be analyzed at the domain level and the topological organization of protein subunits within protein complexes will be predicted. This project will have broader impact through dissemination of algorithms and data sets generated by the research plan, including public databases of protein-DNA and protein-protein interactions. Scientific outgrowths of this project include improved priors for Bayesian prediction of transcriptional regulatory networks, synergy with experimental methods for binding site analysis, anticipated advances in organism-specific research, and release of a large-scale human protein interaction network. Undergraduate, graduate and postdoctoral researchers will be mentored and trained; new course material will be developed at the undergraduate and graduate levels, essential for the rapidly evolving area of computational biology and bioinformatics; and outreach programs will provide science enrichment and mentoring to public high school students and professional development opportunities for their teachers. All results will be disseminated through appropriate channels, including peer-reviewed publications, conferences, workshops, freely available software and databases, and on-line course material.