Finding the "dark matter" in human and yeast protein network prediction and modelling

Singular manifolds of proteomic drivers to model the evolution of inflammatory bowel disease status

The conditions used to describe the presence of an immune disease are often represented by interaction graphs. These informative, but intricate structures are susceptible to perturbations at different levels. The mode in which that perturbation occurs is still of utmost importance in areas such as cell reprogramming and therapeutics models. In this sense, module identification can be useful to well characterise the global graph architecture. To help us with this identification, we perform topological overlap-related measures. Thanks to these measures, the location of highly disease-specific module regulators is possible. Such regulators can perturb other nodes, potentially causing the entire system to change behaviour or collapse. We provide a geometric framework explaining such situations in the context of inflammatory bowel diseases (IBD). IBD are severe chronic disorders of the gastrointestinal tract whose incidence is dramatically increasing worldwide. Our approach models different IBD status as Riemannian manifolds defined by the graph Laplacian of two high throughput proteome screenings. It also identifies module regulators as singularities within the manifolds (the so-called singular manifolds). Furthermore, it reinterprets the characteristic nonlinear dynamics of IBD as compensatory responses to perturbations on those singularities. Then, particular reconfigurations of the immune system could make the disease status move towards an innocuous target state.

In silico prediction of targets for anti-angiogenesis and their in vitro evaluation confirm the involvement of SOD3 in angiogenesis

Biocomputational network approaches are being successfully applied to predict and extract previously unknown information of novel molecular components of biological systems. In the present work, we have used this approach to predict new potential targets of anti-angiogenic therapies. For experimental validation of predictions, we made use of two in vitro assays related to two key steps of the angiogenic process, namely, endothelial cell migration and formation of "tubular-like" structures on Matrigel. From 7 predicted candidates, experimental tests clearly show that superoxide dismutase 3 silencing or blocking with specific antibodies inhibit both key steps of angiogenesis. This experimental validation was further confirmed with additional in vitro assays showing that superoxide dismutase 3 blocking produces inhibitory effects on the capacity of endothelial cells to form "tubular-like" structure within type I collagen matrix, to adhere to elastin-coated plates and to invade a Matrigel layer. Furthermore, angiogenesis was also inhibited in the en vivo aortic ring assay and in the in vivo mouse Matrigel plug assay. Therefore, superoxide dismutase 3 is confirmed as a putative target for anti-angiogenic therapy.

Understanding the interactability of chikungunya virus proteinsviamolecular recognition feature analysis

The chikungunya virus (CHIKV) is an alphavirus that has an enveloped icosahedral capsid and is transmitted byAedessp. mosquitos.

Structural and Functional View of Polypharmacology

Protein domains mediate drug-protein interactions and this principle can guide the design of multi-target drugs i.e. polypharmacology. In this study, we associate multi-target drugs with CATH functional families through the overrepresentation of targets of those drugs in CATH functional families. Thus, we identify CATH functional families that are currently enriched in drugs (druggable CATH functional families) and we use the network properties of these druggable protein families to analyse their association with drug side effects. Analysis of selected druggable CATH functional families, enriched in drug targets, show that relatives exhibit highly conserved drug binding sites. Furthermore, relatives within druggable CATH functional families occupy central positions in a human protein functional network, cluster together forming network neighbourhoods and are less likely to be within proteins associated with drug side effects. Our results demonstrate that CATH functional families can be used to identify drug-target interactions, opening a new research direction in target identification.

The study of severe cutaneous drug hypersensitivity reactions from a systems biology perspective

PURPOSE OF REVIEW

Stevens-Johnson syndrome and toxic epidermal necrolysis are severe hypersensitivity reactions, the majority of which are drug induced. The underlying mechanisms are not fully understood. Here, we review recent findings concerning both mechanistic and genetic factors related to these diseases and propose future approaches to unravel their complexity.

RECENT FINDINGS

Genome-wide association study studies have identified several variants in the human leukocyte antigen region associated with these reactions. These are highly dependent on the population studied and the triggering drug. The T-cell receptor repertoire of the patient is also key. Fas-Fas ligand interactions, perforin and granulysin have also been identified as important players. Furthermore, a high-throughput gene expression study has identified a number of genes that increase in expression in patients during the acute phase of these reactions.

SUMMARY

We review recent high-throughput studies on these diseases and suggest ways in which the data can be combined and reanalyzed using integrative systems biology techniques. We also suggest future lines of research using recent technology that could shed further light on their underlying mechanisms.

Systems biology for molecular life sciences and its impact in biomedicine

Modern systems biology is already contributing to a radical transformation of molecular life sciences and biomedicine, and it is expected to have a real impact in the clinical setting in the next years. In this review, the emergence of systems biology is contextualized with a historic overview, and its present state is depicted. The present and expected future contribution of systems biology to the development of molecular medicine is underscored. Concerning the present situation, this review includes a reflection on the "inflation" of biological data and the urgent need for tools and procedures to make hidden information emerge. Descriptions of the impact of networks and models and the available resources and tools for applying them in systems biology approaches to molecular medicine are provided as well. The actual current impact of systems biology in molecular medicine is illustrated, reviewing two cases, namely, those of systems pharmacology and cancer systems biology. Finally, some of the expected contributions of systems biology to the immediate future of molecular medicine are commented.

What is known on angiogenesis-related rare diseases? A systematic review of literature

Angiogenesis, the formation of new vessels from pre-existing ones, is essential during ontogenetic development and is related to many important physio-pathological processes in the adult. In fact, a persistent and deregulated angiogenesis is a required event for many diseases and pathological situations, including cancer progression and metastasis. Some rare diseases are also angiogenesis-related pathologies. However, there is a lack of an exhaustive review on the topic. The main purpose of this work is to carry out a systematic review of literature to determine what (and how much) scientific information concerning angiogenesis-related rare diseases can be extracted from available sources. After exhaustive searches in bibliographic databases, preselected data were filtered by selecting only those articles on rare diseases with an Orpha number hosted in the Orphanet web. The selected bibliographic references were further curated manually. With the 187 selected references, a critical reading and analysis was carried out allowing for an identification and classification of angiogenesis-related rare diseases, the involved genes and the drugs available for their treatment, all on the basis of the information available in Orphanet database.

Systems biology approaches to finding novel pain mediators

Chronic pain represents a major health burden; this maladaptive pain state occurs as a consequence of hypersensitivity within the peripheral and central components of the somatosensory system. High throughput technologies (genomics, transciptomics, lipidomics, and proteomics) are now being applied to tissue derived from pain patients as well as experimental pain models to discover novel pain mediators. The use of clustering, meta-analysis and other techniques can help refine potential candidates. Of particular importance are systems biology methods, such as co-expression network generating algorithms, which infer potential associations/interactions between molecules and build networks based on these interactions. Protein-protein interaction networks allow the lists of potential targets generated by these different platforms to be analyzed in their biological context. Outputs from these different methods must also be related to the clinical pain phenotype. The improved and standardized phenotyping of pain symptoms and sensory signs enables much better subject stratification. Our hope is that, in the future, the use of computational approaches to integrate datasets including sensory phenotype as well as the outputs of high throughput technologies will help define novel pain mediators and provide insights into the pathogenesis of chronic pain.

Alternative protein-protein interfaces are frequent exceptions

The intricate molecular details of protein-protein interactions (PPIs) are crucial for function. Therefore, measuring the same interacting protein pair again, we expect the same result. This work measured the similarity in the molecular details of interaction for the same and for homologous protein pairs between different experiments. All scores analyzed suggested that different experiments often find exceptions in the interfaces of similar PPIs: up to 22% of all comparisons revealed some differences even for sequence-identical pairs of proteins. The corresponding number for pairs of close homologs reached 68%. Conversely, the interfaces differed entirely for 12-29% of all comparisons. All these estimates were calculated after redundancy reduction. The magnitude of interface differences ranged from subtle to the extreme, as illustrated by a few examples. An extreme case was a change of the interacting domains between two observations of the same biological interaction. One reason for different interfaces was the number of copies of an interaction in the same complex: the probability of observing alternative binding modes increases with the number of copies. Even after removing the special cases with alternative hetero-interfaces to the same homomer, a substantial variability remained. Our results strongly support the surprising notion that there are many alternative solutions to make the intricate molecular details of PPIs crucial for function.

Uncovering the molecular machinery of the human spindle--an integration of wet and dry systems biology

The mitotic spindle is an essential molecular machine involved in cell division, whose composition has been studied extensively by detailed cellular biology, high-throughput proteomics, and RNA interference experiments. However, because of its dynamic organization and complex regulation it is difficult to obtain a complete description of its molecular composition. We have implemented an integrated computational approach to characterize novel human spindle components and have analysed in detail the individual candidates predicted to be spindle proteins, as well as the network of predicted relations connecting known and putative spindle proteins. The subsequent experimental validation of a number of predicted novel proteins confirmed not only their association with the spindle apparatus but also their role in mitosis. We found that 75% of our tested proteins are localizing to the spindle apparatus compared to a success rate of 35% when expert knowledge alone was used. We compare our results to the previously published MitoCheck study and see that our approach does validate some findings by this consortium. Further, we predict so-called "hidden spindle hub", proteins whose network of interactions is still poorly characterised by experimental means and which are thought to influence the functionality of the mitotic spindle on a large scale. Our analyses suggest that we are still far from knowing the complete repertoire of functionally important components of the human spindle network. Combining integrated bio-computational approaches and single gene experimental follow-ups could be key to exploring the still hidden regions of the human spindle system.

Regulatory cross-talk of mouse liver polyamine and methionine metabolic pathways: a systemic approach to its physiopathological consequences

Both polyamines and methionine derivatives are nitrogen compounds directly related to the regulation of gene expression. In silico predictions and experimental evidence suggest a cross-talk between polyamine and methionine metabolism in mammalian tissues. Since liver is the major organ that controls nitrogen metabolism of the whole organism, it is the best tissue to further test this hypothesis in vivo. In this work, we studied the effects of the chronic administration of a methionine-supplemented diet (0.5% Met in drinking water for 5 months) on the liver of mice (designated as MET-mice). Metabolic and proteomic approaches were performed and the data obtained were subjected to biocomputational analysis. Results showed that a supplemental methionine intake can indeed regulate biogenic amine metabolism in an in vivo model by multiple mechanisms including metabolic regulation and specific gene demethylation. Furthermore, putative systemic effects were investigated by molecular and cellular biology methods. Among other results, altered expression levels of multiple inflammation and cell proliferation/death balance markers were found and macrophage activation was observed. Overall, the results presented here will be of interest across a variety of biomedical disciplines, including nutrition, orphan diseases, immunology and oncology.

Systematic computational prediction of protein interaction networks

Determining the network of physical protein associations is an important first step in developing mechanistic evidence for elucidating biological pathways. Despite rapid advances in the field of high throughput experiments to determine protein interactions, the majority of associations remain unknown. Here we describe computational methods for significantly expanding protein association networks. We describe methods for integrating multiple independent sources of evidence to obtain higher quality predictions and we compare the major publicly available resources available for experimentalists to use.

Transient protein-protein interactions: structural, functional, and network properties

Transient interactions, which involve protein interactions that are formed and broken easily, are important in many aspects of cellular function. Here we describe structural and functional properties of transient interactions between globular domains and between globular domains, short peptides, and disordered regions. The importance of posttranslational modifications in transient interactions is also considered. We review techniques used in the detection of the different types of transient protein-protein interactions. We also look at the role of transient interactions within protein-protein interaction networks and consider their contribution to different aspects of these networks.