The identification of similarities between biological networks: application to the metabolome and interactome

The increasing interest in systems biology has resulted in extensive experimental data describing networks of interactions (or associations) between molecules in metabolism, protein-protein interactions and gene regulation. Comparative analysis of these networks is central to understanding biological systems. We report a novel method (PHUNKEE: Pairing subgrapHs Using NetworK Environment Equivalence) by which similar subgraphs in a pair of networks can be identified. Like other methods, PHUNKEE explicitly considers the graphical form of the data and allows for gaps. However, it is novel in that it includes information about the context of the subgraph within the adjacent network. We also explore a new approach to quantifying the statistical significance of matching subgraphs. We report similar subgraphs in metabolic pathways and in protein-protein interaction networks. The most similar metabolic subgraphs were generally found to occur in processes central to all life, such as purine, pyrimidine and amino acid metabolism. The most similar pairs of subgraphs found in the protein-protein interaction networks of Drosophila melanogaster and Saccharomyces cerevisiae also include central processes such as cell division but, interestingly, also include protein sub-networks involved in pre-mRNA processing. The inclusion of network context information in the comparison of protein interaction networks increased the number of similar subgraphs found consisting of proteins involved in the same functional process. This could have implications for the prediction of protein function.     

Combining different 'omics' technologies to map and validate protein-protein interactions in humans.

The mapping of protein-protein interactions is key to understanding biological processes. Many technologies have been reported to map interactions and these have been systematically applied in yeast. To date, the number of reported yeast protein interactions that have been truly validated by at least one other approach is low. The mapping of human protein interaction networks is even more complicated. Thus, it is unreasonable to try to map the human interactome; instead, interaction mapping in human cell lines should be focused along the lines of diseases or changes that can be associated with specific cells. In this paper, an approach for combining different 'omics' technologies to achieve efficient mapping and validation of protein interactions in human cell lines is presented.     

An accurate,sensitive, and scalable method to identify functional sites in protein structures

Functional sites determine the activity and interactions of proteins and as such constitute the targets of most drugs. However, the exponential growth of sequence and structure data far exceeds the ability of experimental techniques to identify their locations and key amino acids. To fill this gap we developed a computational Evolutionary Trace method that ranks the evolutionary importance of amino acids in protein sequences. Studies show that the best-ranked residues form fewer and larger structural clusters than expected by chance and overlap with functional sites, but until now the significance of this overlap has remained qualitative. Here, we use 86 diverse protein structures, including 20 determined by the structural genomics initiative, to show that this overlap is a recurrent and statistically significant feature. An automated ET correctly identifies seven of ten functional sites by the least favorable statistical measure, and nine of ten by the most favorable one. These results quantitatively demonstrate that a large fraction of functional sites in the proteome may be accurately identified from sequence and structure. This should help focus structure-function studies, rational drug design, protein engineering, and functional annotation to the relevant regions of a protein.     

Chromosome rearrangements and the evolution of genome structuring and adaptability

Eukaryotes appear to evolve by micro and macro rearrangements. This is observed not only for long-term evolutionary adaptation, but also in short-term experimental evolution of yeast, Saccharomyces cerevisiae. Moreover, based on these and other experiments it has been postulated that repeat elements, retroposons for example, mediate such events. We study an evolutionary model in which genomes with retroposons and a breaking/repair mechanism are subjected to a changing environment. We show that retroposon-mediated rearrangements can be a beneficial mutational operator for short-term adaptations to a new environment. But simply having the ability of rearranging chromosomes does not imply an advantage over genomes in which only single-gene insertions and deletions occur. Instead, a structuring of the genome is needed: genes that need to be amplified (or deleted) in a new environment have to cluster. We show that genomes hosting retroposons, starting with a random order of genes, will in the long run become organized, which enables (fast) rearrangement-based adaptations to the environment. In other words, our model provides a "proof of principle" that genomes can structure themselves in order to increase the beneficial effect of chromosome rearrangements.     

Crystal structures of SnoaL2 and AclR: two putative hydroxylases in the biosynthesis of aromatic polyketide antibiotics

SnoaL2 and AclR are homologous enzymes in the biosynthesis of the aromatic polyketides nogalamycin in Streptomyces nogalater and cinerubin in Streptomyces galilaeus, respectively. Evidence obtained from gene transfer experiments suggested that SnoaL2 catalyzes the hydroxylation of the C-1 carbon atom of the polyketide chain. Here we show that AclR is also involved in the production of 1-hydroxylated anthracyclines in vivo. The three-dimensional structure of SnoaL2 has been determined by multi-wavelength anomalous diffraction to 2.5A resolution, and that of AclR to 1.8A resolution using molecular replacement. Both enzymes are dimers in solution and in the crystal. The fold of the enzyme subunits consists of an alpha+beta barrel. The dimer interface is formed by packing of the beta-sheets from the two subunits against each other. In the interior of the alpha+beta barrel a hydrophobic cavity is formed that most likely binds the substrate and harbors the active site. The subunit fold and the architecture of the active site in SnoaL2 and AclR are similar to that of the polyketide cyclases SnoaL and AknH; however, they show completely different quaternary structures. A comparison of the active site pockets of the putative hydroxylases AclR and SnoaL2 with those of bona fide polyketide cyclases reveals distinct differences in amino acids lining the cavity that might be responsible for the switch in chemistry. The moderate degree of sequence similarity and the preservation of the three-dimensional fold of the polypeptide chain suggest that these enzymes are evolutionary related. Members of this enzyme family appear to have evolved from a common protein scaffold by divergent evolution to catalyze reactions chemically as diverse as aldol condensation and hydroxylation.     

Free energy simulations for protein ligand binding and stability

Abstract

We summarize several computational techniques to determine relative free energies for condensed-phase systems. The focus is on practical considerations which are capable of making direct contact with experiments. Particular applications include the thermodynamic stability of apo- and holo-myoglobin, insulin dimerization free energy, ligand binding in lysozyme, and ligand diffusion in globular proteins. In addition to provide differential free energies between neighboring states, converged umbrella sampling simulations provide insight into migration barriers and ligand dissociation barriers and analysis of the trajectories yield additional insight into the structural dynamics of fundamental processes. Also, such simulations are useful tools to quantify relative stability changes for situations where experiments are difficult. This is illustrated for NO-bound myoglobin. For the dissociation of benzonitrile from lysozyme it is found that long umbrella sampling simulations are required to approximately converge the free energy profile. Then, however, the resulting differential free energy between the bound and unbound state is in good agreement with estimates from molecular mechanics with generalized Born surface area simulations. Furthermore, comparing the barrier height for ligand escape suggests that ligand dissociation contains a non-equilibrium component.     

Multimodal approach to explore the pathogenicity of BARD1, ARG 658 CYS,and ILE 738 VAL mutants

BARD1–BRCA1 complex plays an important role in DNA damage repair, apoptosis, chromatin remodeling, and other important processes required for cell survival. BRCA1 and BARD1 heterodimer possess E3 ligase activity and is involved in genome maintenance, by functioning in surveillance for DNA damage, thereby regulating multiple pathways including tumor suppression. BRCT domains are evolutionary conserved domains present in different proteins such as BRCA1, BARD1, XRCC, and MDC1 regulating damage response and cell-cycle control through protein–protein interactions. Nonetheless, the role of BARD1BRCT in the recruitment of DNA repair mechanism and structural integrity with BRCA1 complex is still implicit. To explicate the role of BARD1BRCT in the DNA repair mechanism, in silico, in vitro, and biophysical approach were applied to characterize BARD1 BRCT wild-type and Arg658Cys and Ile738Val mutants. However, no drastic secondary and tertiary structural changes in the mutant proteins were observed. Thermal and chemical denaturation studies revealed that mutants Arg658Cys and Ile738Val have a decrease in T_m and ?G than the wild type. In silico studies of BARD1 BRCT (568-777) and mutant protein indicate loss in structural compactness on the Ile738Val mutant. Comparative studies of wild-type and mutants will thus be helpful in understanding the basic role of BARD1BRCT in DNA damage repair.     

Are protein–protein interfaces more conserved in sequence than the rest of the protein surface?

Protein interfaces are thought to be distinguishable from the rest of the protein surface by their greater degree of residue conservation. We test the validity of this approach on an expanded set of 64 protein-protein interfaces using conservation scores derived from two multiple sequence alignment types, one of close homologs/orthologs and one of diverse homologs/paralogs. Overall, we find that the interface is slightly more conserved than the rest of the protein surface when using either alignment type, with alignments of diverse homologs showing marginally better discrimination. However, using a novel surface-patch definition, we find that the interface is rarely significantly more conserved than other surface patches when using either alignment type. When an interface is among the most conserved surface patches, it tends to be part of an enzyme active site. The most conserved surface patch overlaps with 39% (+/- 28%) and 36% (+/- 28%) of the actual interface for diverse and close homologs, respectively. Contrary to results obtained from smaller data sets, this work indicates that residue conservation is rarely sufficient for complete and accurate prediction of protein interfaces. Finally, we find that obligate interfaces differ from transient interfaces in that the former have significantly fewer alignment gaps at the interface than the rest of the protein surface, as well as having buried interface residues that are more conserved than partially buried interface residues.     

Molecular docking uncovers TSPY binds more efficiently with eEF1A2 compared to eEF1A1

Testis-specific protein, Y-encoded (TSPY) binds to eukaryotic translation elongation factor 1 alpha (eEF1A) at its SET/NAP domain that is essential for the elongation during protein synthesis implicated with normal spermatogenesis. The eEF1A exists in two forms, eEF1A1 (alpha 1) and eEF1A2 (alpha 2), encoded by separate loci. Despite critical interplay of the TSPY and eEF1A proteins, literature remained silent on the residues playing significant roles during such interactions. We deduced 3D structures of TSPY and eEF1A variants by comparative modeling (Modeller 9.13) and assessed protein–protein interactions employing HADDOCK docking. Pairwise alignment using EMBOSS Needle for eEF1A1 and eEF1A2 proteins revealed high degree (~92%) of homology. Efficient binding of TSPY with eEF1A2 as compared to eEF1A1 was observed, in spite of the occurrence of significant structural similarities between the two variants. We also detected strong interactions of domain III followed by domains II and I of both eEF1A variants with TSPY. In the process, seven interacting residues of TSPY’s NAP domain namely, Asp 175, Glu 176, Asp 179, Tyr 183, Asp 240, Glu 244, and Tyr 246 common to both eEF1A variants were detected. Additionally, six lysine residues observed in eEF1A2 suggest their possible role in TSPY–eEF1A2 complex formation essential for germ cell development and spermatogenesis. Thus, more efficient binding of TSPY with eEF1A2 as compared to that of eEF1A1 established autonomous functioning of these two variants. Studies on mutated protein following similar approach would uncover the causative obstruction, between the interacting partners leading to deeper understanding on the structure–function relationship.