Extracting insight from noisy cellular networks.

Network biologists attempt to extract meaningful relationships among genes or their products from very noisy data. We argue that what we categorize as noisy data may sometimes reflect noisy biology and therefore may shield a hidden meaning about how networks evolve and how matter is organized in the cell. We present practical solutions, based on existing evolutionary and biophysical concepts, through which our understanding of cell biology can be enormously enriched.

Massive sequence perturbation of the Raf ras binding domain reveals relationships between sequence conservation, secondary structure propensity, hydrophobic core organization and stability.

The contributions of specific residues to the delicate balance between function, stability and folding rates could be determined, in part by [corrected] comparing the sequences of structures having identical folds, but insignificant sequence homology. Recently, we have devised an experimental strategy to thoroughly explore residue substitutions consistent with a specific class of structure. Using this approach, the amino acids tolerated at virtually all residues of the c-Raf/Raf1 ras binding domain (Raf RBD), an exemplar of the common beta-grasp ubiquitin-like topology, were obtained and used to define the sequence determinants of this fold. Herein, we present analyses suggesting that more subtle sequence selection pressure, including propensity for secondary structure, the hydrophobic core organization and charge distribution are imposed on the Raf RBD sequence. Secondly, using the Gibbs free energies (DeltaG(F-U)) obtained for 51 mutants of Raf RBD, we demonstrate a strong correlation between amino acid conservation and the destabilization induced by truncating mutants. In addition, four mutants are shown to significantly stabilize Raf RBD native structure. Two of these mutations, including the well-studied R89L, are known to severely compromise binding affinity for ras. Another stabilized mutant consisted of a deletion of amino acid residues E104-K106. This deletion naturally occurs in the homologues a-Raf and b-Raf and could indicate functional divergence. Finally, the combination of mutations affecting five of 78 residues of Raf RBD results in stabilization of the structure by approximately 12 kJ mol(-1) (DeltaG(F-U) is -22 and -34 kJ mol(-1) for wt and mutant, respectively). The sequence perturbation approach combined with sequence/structure analysis of the ubiquitin-like fold provide a basis for the identification of sequence-specific requirements for function, stability and folding rate of the Raf RBD and structural analogues, highlighting the utility of conservation profiles as predictive tools of structural organization.

An in vivo map of the yeast protein interactome.

Protein interactions regulate the systems-level behavior of cells; thus, deciphering the structure and dynamics of protein interaction networks in their cellular context is a central goal in biology. We have performed a genome-wide in vivo screen for protein-protein interactions in Saccharomyces cerevisiae by means of a protein-fragment complementation assay (PCA). We identified 2770 interactions among 1124 endogenously expressed proteins. Comparison with previous studies confirmed known interactions, but most were not known, revealing a previously unexplored subspace of the yeast protein interactome. The PCA detected structural and topological relationships between proteins, providing an 8-nanometer-resolution map of dynamically interacting complexes in vivo and extended networks that provide insights into fundamental cellular processes, including cell polarization and autophagy, pathways that are evolutionarily conserved and central to both development and human health.

iVici: Interrelational Visualization and Correlation Interface.

We have developed an application, iVici, to analyze cellular networks represented as addressable symmetric or asymmetric two-dimensional matrices. iVici was designed to permit simultaneous visualization and correlation of multiple datasets, representing any relationship between a set of genes, mRNAs, or proteins. Visual overlay of datasets and addressable access to gene annotations permits comparison of networks of different types (for example protein-protein interactions and genetic networks) or investigation of the dynamic reorganization of a particular network.