Understanding the molecular determinants of specificity in proteinprotein interaction is an outstanding challenge of postgenome biology. The availability of large protein databases generated from sequences of hundreds of bacterial genomes enables various statistical approaches to this problem. In this context covariance-based methods have been used to identify correlation between amino acid positions in interacting proteins. However, these methods have an important shortcoming, in that they cannot distinguish between directly and indirectly correlated residues. We developed a method that combines covariance analysis with global inference analysis, adopted from use in statistical physics. Applied to a set of >2,500 representatives of the bacterial two-component signal transduction system, the combination of covariance with global inference successfully and robustly identified residue pairs that are proximal in space without resorting to ad hoc tuning parameters, both for heterointeractions between sensor kinase (SK) and response regulator (RR) proteins and for homointeractions between RR proteins. The spectacular success of this approach illustrates the effectiveness of the global inference approach in identifying direct interaction based on sequence information alone. We expect this method to be applicable soon to interaction surfaces between proteins present in only 1 copy per genome as the number of sequenced genomes continues to expand. Use of this method could significantly increase the potential targets for therapeutic intervention, shed light on the mechanism of protein-protein interaction, and establish the foundation for the accurate prediction of interacting protein partners.T he large majority of cellular functions are executed and controlled by interacting proteins. With up to several thousand types of proteins expressed in a typical bacterial cell at a given time, their concerted specific interactions regulate the interplay of biochemical processes that are the essence of life. Many protein interactions are transient, allowing proteins to mate with several partners or travel in cellular space to perform their functions. Understanding these transient interactions is one of the outstanding challenges of systems biology (reviewed in ref. 1). The characterization of the molecular details of the interface formed between known interacting proteins is a requirement for understanding the molecular determinants of protein-protein interaction, the knowledge of which may be important for a variety of applications including synthetic biology, e.g., designing new specific interaction between proteins (reviewed in ref.2), and pharmaceutics, e.g., protein interaction surfaces as drug targets (reviewed in ref.3).Experimental approaches to identify surfaces of interaction between proteins such as surface-scanning mutagenesis and cocrystal structure generation are arduous and/or serendipitous. Cocrystal structures provide the best molecular resolution but are particularly challenging to obtain for transient interactio...

Systematic annotation of gene regulatory elements is a major challenge in genome science. Direct mapping of chromatin modification marks and transcriptional factor binding sites genome-wide 1,2 has successfully identified specific subtypes of regulatory elements 3. In Drosophila several pioneering studies have provided genome-wide identification of Polycomb-Response Elements 4, chromatin states 5, transcription factor binding sites (TFBS) 6–9, PolII regulation 8, and insulator elements 10; however, comprehensive annotation of the regulatory genome remains a significant challenge. Here we describe results from the modENCODE cis-regulatory annotation project. We produced a map of the Drosophila melanogaster regulatory genome based on more than 300 chromatin immuno-precipitation (ChIP) datasets for eight chromatin features, five histone deacetylases (HDACs) and thirty-eight site-specific transcription factors (TFs) at different stages of development. Using these data we inferred more than 20,000 candidate regulatory elements and we validated a subset of predictions for promoters, enhancers, and insulators in vivo. We also identified nearly 2,000 genomic regions of dense TF binding associated with chromatin activity and accessibility. We discovered hundreds of new TF co-binding relationships and defined a TF network with over 800 potential regulatory relationships.

Insulators are DNA sequences that control the interactions among genomic regulatory elements and act as chromatin boundaries. A thorough understanding of their location and function is necessary to address the complexities of metazoan gene regulation. We studied by ChIP–chip the genome-wide binding sites of 6 insulator-associated proteins—dCTCF, CP190, BEAF-32, Su(Hw), Mod(mdg4), and GAF—to obtain the first comprehensive map of insulator elements in Drosophila embryos. We identify over 14,000 putative insulators, including all classically defined insulators. We find two major classes of insulators defined by dCTCF/CP190/BEAF-32 and Su(Hw), respectively. Distributional analyses of insulators revealed that particular sub-classes of insulator elements are excluded between cis-regulatory elements and their target promoters; divide differentially expressed, alternative, and divergent promoters; act as chromatin boundaries; are associated with chromosomal breakpoints among species; and are embedded within active chromatin domains. Together, these results provide a map demarcating the boundaries of gene regulatory units and a framework for understanding insulator function during the development and evolution of Drosophila.

We have isolated a cDNA encoding a novel human intracytoplasmic tyrosine kinase, termed RAFTK (for a related adhesion focal tyrosine kinase). In addition, we have cloned and characterized the murine homolog of the human RAFTK cDNA. Comparison of the deduced amino acid sequences of human RAFTK and murine Raftk cDNAs revealed 95% homology, indicating that RAFTK is highly conserved between these species. The RAFTK cDNA clone, encoding a polypeptide of 1009 amino acids, has closest homology (48% identity, 65% similarity) to the focal adhesion kinase (pp125FAK). Comparison of the deduced amino acid sequences also indicates that RAFTK, like pp125FAK, lacks a transmembrane region, myristylation sites, and SH2 and SH3 domains. In addition, like pp125FAK, RAFTK contains a kinase domain flanked by large N-terminal (426 residues) and C-terminal (331 residues) domains, and the C-terminal region contains a predicted proline-rich stretch of residues. In fetal tissues, RAFTK expression was abundant in brain, and low levels were observed in lung and liver. In adult tissues, it was less restricted, indicating that RAFTK expression is developmentally up-regulated. Expression of RAFTK was also observed in human CD34+ marrow cells, primary bone marrow megakaryocytes, platelets, and various areas of brain. The human RAFTK gene was assigned to human chromosome 8 using genomic DNAs from human/rodent somatic cell hybrid lines. The mouse Raftk gene was mapped to chromosome 14, closely linked to gonadotropin-releasing hormone. Using specific antibodies for RAFTK, a approximately 123-kDa protein from the human megakaryocytic CMK cell line was immunoprecipitated. Treatment of the megakaryocytic CMK cells with thrombin caused a rapid induction of tyrosine phosphorylation of RAFTK protein. The structural features of RAFTK suggest that it is a member of the focal adhesion kinase gene family and may participate in signal transduction in human megakaryocytes and brain as well as in other cell types.