Biomedical subjects

Jose B Pereira-Leal

Publications and source records attributed to Jose B Pereira-Leal.

6 recordsLinked to original sources

PubMed2006

3D complex: a structural classification of protein complexes.

Most of the proteins in a cell assemble into complexes to carry out their function. It is therefore crucial to understand the physicochemical properties as well as the evolution of interactions between proteins. The Protein Data Bank represents an important source of information for such studies, because more than half of the structures are homo- or heteromeric protein complexes. Here we propose the first hierarchical classification of whole protein complexes of known 3-D structure, based on representing their fundamental structural features as a graph. This classification provides the first overview of all the complexes in the Protein Data Bank and allows nonredundant sets to be derived at different levels of detail. This reveals that between one-half and two-thirds of known structures are multimeric, depending on the level of redundancy accepted. We also analyse the structures in terms of the topological arrangement of their subunits and find that they form a small number of arrangements compared with all theoretically possible ones. This is because most complexes contain four subunits or less, and the large majority are homomeric. In addition, there is a strong tendency for symmetry in complexes, even for heteromeric complexes. Finally, through comparison of Biological Units in the Protein Data Bank with the Protein Quaternary Structure database, we identified many possible errors in quaternary structure assignments. Our classification, available as a database and Web server at http://www.3Dcomplex.org, will be a starting point for future work aimed at understanding the structure and evolution of protein complexes.

Amino Acid Sequence↗

PubMed2006

The origins and evolution of functional modules: lessons from protein complexes.

Modularity is an attribute of a system that can be decomposed into a set of cohesive entities that are loosely coupled. Many cellular networks can be decomposed into functional modules-each functionally separable from the other modules. The protein complexes in physical protein interaction networks are a good example of this, and here we focus on their origins and evolution. We investigate the emergence of protein complexes and physical interactions between proteins by duplication, and review other mechanisms. We dissect the dataset of protein complexes of known three-dimensional structure, and show that roughly 90% of these complexes contain contacts between identical proteins within the same complex. Proteins that are shared across different complexes occur frequently, and they tend to be essential genes more often than members of a single protein complex. We also provide a perspective on the evolutionary mechanisms driving the growth of other modular cellular networks such as transcriptional regulatory and metabolic networks.

Evolution, Molecular↗

PubMed2005

The vertebrate Hef ortholog is a component of the Fanconi anemia tumor-suppressor pathway.

The helicase-associated endonuclease for fork-structured DNA (Hef) is an archaeabacterial protein that processes blocked replication forks. Here we have isolated the vertebrate Hef ortholog and investigated its molecular function. Disruption of this gene in chicken DT40 cells results in genomic instability and sensitivity to DNA cross-links. The similarity of this phenotype to that of cells lacking the Fanconi anemia-related (FA) tumor-suppressor genes led us to investigate whether Hef functions in this pathway. Indeed, we found a genetic interaction between the FANCC and Hef genes. In addition, Hef is a component of the FA nuclear protein complex that facilitates its DNA damage-inducible chromatin localization and the monoubiquitination of the FA protein FANCD2. Notably, Hef interacts directly with DNA structures that are intermediates in DNA replication. This discovery sheds light on the origins, regulation and molecular function of the FA tumor-suppressor pathway in the maintenance of genome stability.

Adenosine Triphosphatases↗

PubMed2005

Comparative genomics of trypanosomatid parasitic protozoa.

A comparison of gene content and genome architecture of Trypanosoma brucei, Trypanosoma cruzi, and Leishmania major, three related pathogens with different life cycles and disease pathology, revealed a conserved core proteome of about 6200 genes in large syntenic polycistronic gene clusters. Many species-specific genes, especially large surface antigen families, occur at nonsyntenic chromosome-internal and subtelomeric regions. Retroelements, structural RNAs, and gene family expansion are often associated with syntenic discontinuities that-along with gene divergence, acquisition and loss, and rearrangement within the syntenic regions-have shaped the genomes of each parasite. Contrary to recent reports, our analyses reveal no evidence that these species are descended from an ancestor that contained a photosynthetic endosymbiont.

Animals↗

PubMed2004

Detection of functional modules from protein interaction networks.

Complex cellular processes are modular and are accomplished by the concerted action of functional modules (Ravasz et al., Science 2002;297:1551-1555; Hartwell et al., Nature 1999;402:C47-52). These modules encompass groups of genes or proteins involved in common elementary biological functions. One important and largely unsolved goal of functional genomics is the identification of functional modules from genomewide information, such as transcription profiles or protein interactions. To cope with the ever-increasing volume and complexity of protein interaction data (Bader et al., Nucleic Acids Res 2001;29:242-245; Xenarios et al., Nucleic Acids Res 2002;30:303-305), new automated approaches for pattern discovery in these densely connected interaction networks are required (Ravasz et al., Science 2002;297:1551-1555; Bader and Hogue, Nat Biotechnol 2002;20:991-997; Snel et al., Proc Natl Acad Sci USA 2002;99:5890-5895). In this study, we successfully isolate 1046 functional modules from the known protein interaction network of Saccharomyces cerevisiae involving 8046 individual pair-wise interactions by using an entirely automated and unsupervised graph clustering algorithm. This systems biology approach is able to detect many well-known protein complexes or biological processes, without reference to any additional information. We use an extensive statistical validation procedure to establish the biological significance of the detected modules and explore this complex, hierarchical network of modular interactions from which pathways can be inferred.

Algorithms↗

PubMed2003

Genome evolution reveals biochemical networks and functional modules.

The analysis of completely sequenced genomes uncovers an astonishing variability between species in terms of gene content and order. During genome history, the genes are frequently rear-ranged, duplicated, lost, or transferred horizontally between genomes. These events appear to be stochastic, yet they are under selective constraints resulting from the functional interactions between genes. These genomic constraints form the basis for a variety of techniques that employ systematic genome comparisons to predict functional associations among genes. The most powerful techniques to date are based on conserved gene neighborhood, gene fusion events, and common phylogenetic distributions of gene families. Here we show that these techniques, if integrated quantitatively and applied to a sufficiently large number of genomes, have reached a resolution which allows the characterization of function at a higher level than that of the individual gene: global modularity becomes detectable in a functional protein network. In Escherichia coli, the predicted modules can be bench-marked by comparison to known metabolic pathways. We found as many as 74% of the known metabolic enzymes clustering together in modules, with an average pathway specificity of at least 84%. The modules extend beyond metabolism, and have led to hundreds of reliable functional predictions both at the protein and pathway level. The results indicate that modularity in protein networks is intrinsically encoded in present-day genomes.

Amino Acids↗