Understanding biological functions through molecular networks

The completion of genome sequences and subsequent high-throughput mapping of molecular networks have allowed us to study biology from the network perspective. Experimental, statistical and mathematical modeling approaches have been employed to study the structure, function and dynamics of molecular networks, and begin to reveal important links of various network properties to the functions of the biological systems. In agreement with these functional links, evolutionary selection of a network is apparently based on the function, rather than directly on the structure of the network. Dynamic modularity is one of the prominent features of molecular networks. Taking advantage of such a feature may simplify network-based biological studies through construction of process-specific modular networks and provide functional and mechanistic insights linking genotypic variations to complex traits or diseases, which is likely to be a key approach in the next wave of understanding complex human diseases. With the development of ready-to-use network analysis and modeling tools the networks approaches will be infused into everyday biological research in the near future.     

Annotating proteins by mining protein interaction networks

MOTIVATION: In general, most accurate gene/protein annotations are provided by curators. Despite having lesser evidence strengths, it is inevitable to use computational methods for fast and a priori discovery of protein function annotations. This paper considers the problem of assigning Gene Ontology (GO) annotations to partially annotated or newly discovered proteins. RESULTS: We present a data mining technique that computes the probabilistic relationships between GO annotations of proteins on protein-protein interaction data, and assigns highly correlated GO terms of annotated proteins to non-annotated proteins in the target set. In comparison with other techniques, probabilistic suffix tree and correlation mining techniques produce the highest prediction accuracy of 81% precision with the recall at 45%. AVAILABILITY: Code is available upon request. Results and used materials are available online at http://kirac.case.edu/PROTAN.     

Signalling through cerebral cavernous malformation protein networks

Cerebral cavernous malformations (CCMs) are neurovascular abnormalities characterized by thin, leaky blood vessels resulting in lesions that predispose to haemorrhages, stroke, epilepsy and focal neurological deficits. CCMs arise due to loss-of-function mutations in genes encoding one of three CCM complex proteins, KRIT1, CCM2 or CCM3. These widely expressed, multi-functional adaptor proteins can assemble into a CCM protein complex and (either alone or in complex) modulate signalling pathways that influence cell adhesion, cell contractility, cytoskeletal reorganization and gene expression. Recent advances, including analysis of the structures and interactions of CCM proteins, have allowed substantial progress towards understanding the molecular bases for CCM protein function and how their disruption leads to disease. Here, we review current knowledge of CCM protein signalling with a focus on three pathways which have generated the most interest—the RhoA–ROCK, MEKK3–MEK5–ERK5–KLF2/4 and cell junctional signalling pathways—but also consider ICAP1-β1 integrin and cdc42 signalling. We discuss emerging links between these pathways and the processes that drive disease pathology and highlight important open questions—key among them is the role of subcellular localization in the control of CCM protein activity.     

Evolving protein interaction networks through gene duplication

The topology of the proteome map revealed by recent large-scale hybridization methods has shown that the distribution of protein-protein interactions is highly heterogeneous, with many proteins having few edges while a few of them are heavily connected. This particular topology is shared by other cellular networks, such as metabolic pathways, and it has been suggested to be responsible for the high mutational homeostasis displayed by the genome of some organisms. In this paper we explore a recent model of proteome evolution that has been shown to reproduce many of the features displayed by its real counterparts. The model is based on gene duplication plus re-wiring of the newly created genes. The statistical features displayed by the proteome of well-known organisms are reproduced and suggest that the overall topology of the protein maps naturally emerges from the two leading mechanisms considered by the model.     

Dirigent proteins: molecular characteristics and potential biotechnological applications

Dirigent proteins (DIRs) are thought to play important roles in plant secondary metabolism. They lack catalytic activity but direct the outcome of bimolecular coupling reactions toward regio- and stereospecific product formation. Functionally described DIRs confer specificity to the oxidative coupling of coniferyl alcohol resulting in the preferred production of either (+)- or (?)-pinoresinol, which are the first intermediates in the enantiocomplementary pathways for lignan biosynthesis. DIRs are extracellular glycoproteins with high β-strand content and have been found in all land plants investigated so far. Their ability to capture and orientate radicals represents a unique naturally evolved concept for the control of radical dimerization reactions. Although oxidative coupling is commonly used in biological systems, its wider application in chemical synthesis is often limited by insufficient selectivity. This minireview gives an overview of functionally described DIRs and their molecular characteristics and wants to inspire further research for their use in biotechnological applications.     

Structure-based analyses of gut microbiome-related proteins by neural networks and molecular dynamics simulations

An imbalance in the gut microbiome is linked to immune disorders, such as autoimmune, allergic, and chronic inflammatory disorders. Elucidation of disease mechanisms is a matter of urgency. It requires precise elucidation of the structure-based mechanisms of protein interactions involved in disease onset. In addition, an understanding of the protein dynamics is vital because these fluctuations affect the function and interaction of disease-associated proteins. Experimental evaluation of not only protein interactions, functions, and structures but also the dynamics are time-consuming; therefore, computational predictions are necessary to elucidate disease mechanisms. Here, we introduce recent studies on structure-based analyses of proteins using computational approaches, particularly artificial intelligence (AI) and molecular dynamics (MD) simulations.     

BLNK: molecular scaffolding through 'cis'-mediated organization of signaling proteins

Assembly of intracellular macromolecular complexes is thought to provide an important mechanism to coordinate the generation of second messengers upon receptor activation. We have previously identified a B cell linker protein, termed BLNK, which serves such a scaffolding function in B cells. We demonstrate here that phosphorylation of five tyrosine residues within human BLNK nucleates distinct signaling effectors following B cell antigen receptor activation. The phosphorylation of multiple tyrosine residues not only amplifies PLCgamma-mediated signaling but also supports 'cis'-mediated interaction between distinct signaling effectors within a large molecular complex. These data demonstrate the importance of coordinate phosphorylation of molecular scaffolds, and provide insights into how assembly of macromolecular complexes is required for normal receptor function.     

Exploring mechanisms of diet-colon cancer associations through candidate molecular interaction networks

Background

Epidemiological studies in the recent years have investigated the relationship between dietary habits and disease risk demonstrating that diet has a direct effect on public health. Especially plant-based diets -fruits, vegetables and herbs- are known as a source of molecules with pharmacological properties for treatment of several malignancies. Unquestionably, for developing specific intervention strategies to reduce cancer risk there is a need for a more extensive and holistic examination of the dietary components for exploring the mechanisms of action and understanding the nutrient-nutrient interactions. Here, we used colon cancer as a proof-of-concept for understanding key regulatory sites of diet on the disease pathway.

Results

We started from a unique vantage point by having a database of 158 plants positively associated to colon cancer reduction and their molecular composition (~3,500 unique compounds). We generated a comprehensive picture of the interaction profile of these edible and non-edible plants with a predefined candidate colon cancer target space consisting of ~1,900 proteins. This knowledge allowed us to study systematically the key components in colon cancer that are targeted synergistically by phytochemicals and identify statistically significant and highly correlated protein networks that could be perturbed by dietary habits.

Conclusion

We propose here a framework for interrogating the critical targets in colon cancer processes and identifying plant-based dietary interventions as important modifiers using a systems chemical biology approach. Our methodology for better delineating prevention of colon cancer by nutritional interventions relies heavily on the availability of information about the small molecule constituents of our diet and it can be expanded to any other disease class that previous evidence has linked to lifestyle.     

Identification of additional proteins in differential proteomics using protein interaction networks

In this study, we developed a novel computational approach based on protein–protein interaction networks to identify a list of proteins that might have remained undetected in differential proteomic profiling experiments. We tested our computational approach on two sets of human smooth muscle cell protein extracts that were affected differently by DNase I treatment. Differential proteomic analysis by saturation DIGE resulted in the identification of 41 human proteins. The application of our approach to these 41 input proteins consisted of four steps: (i) Compilation of a human protein–protein interaction network from public databases; (ii) calculation of interaction scores based on functional similarity; (iii) determination of a set of candidate proteins that are needed to efficiently and confidently connect the 41 input proteins; and (iv) ranking of the resulting 25 candidate proteins. Two of the three highest‐ranked proteins, beta‐arrestin 1, and beta‐arrestin 2, were experimentally tested, revealing that their abundance levels in human smooth muscle cell samples were indeed affected by DNase I treatment. These proteins had not been detected during the experimental proteomic analysis. Our study suggests that our computational approach may represent a simple, universal, and cost‐effective means to identify additional proteins that remain elusive for current 2D gel‐based proteomic profiling techniques.     

Heat shock proteins: molecular chaperones of protein biogenesis.

Heat shock proteins (Hsps) were first identified as proteins whose synthesis was enhanced by stresses such as an increase in temperature. Recently, several of the major Hsps have been shown to be intimately involved in protein biogenesis through a direct interaction with a wide variety of proteins. As a reflection of this role, these Hsps have been referred to as molecular chaperones. Hsp70s interact with incompletely folded proteins, such as nascent chains on ribosomes and proteins in the process of translocation from the cytosol into mitochondria and the endoplasmic reticulum. Hsp60 also binds to unfolded proteins, preventing aggregation and facilitating protein folding. Although less well defined, other Hsps such as Hsp90 also play important roles in modulating the activity of a number of proteins. The function of the proteolytic system is intertwined with that of molecular chaperones. Several components of this system, encoded by heat-inducible genes, are responsible for the degradation of abnormal or misfolded proteins. The budding yeast Saccharomyces cerevisiae has proven very useful in the analysis of the role of molecular chaperones in protein maturation, translocation, and degradation. In this review, results of experiments are discussed within the context of experiments with other organisms in an attempt to describe the current state of understanding of these ubiquitous and important proteins.     

Langmuir monolayer approaches to protein recognition through molecular imprinting

Surface plasmon resonance (SPR) spectroscopy and atomic force microscopy (AFM) have been employed to investigate ferritin adsorption to binary surfactant monolayers of cationic dioctadecyldimethylammonium bromide (DOMA) and non-ionic methyl stearate (SME). Surfactant molar ratios, miscibility, and lateral mobility were controlled to define the number, size, and distribution of "binding sites" for ferritin, which under the low ionic strength conditions investigated, adsorbed to the monolayers predominantly through electrostatic interactions. Successive adsorption/desorption cycles revealed that fluid monolayers, capable of laterally restructuring during the initial protein adsorption event, bound up to 60% more ferritin (dependent on SME:DOMA ratios) as compared to monolayers that were immobilized on a hydrophobic support during this first adsorption step. The enhanced binding of ferritin to fluid monolayers was accentuated in films having non-ionic SME as the principal component. These findings support the premise that the surfactants reorganize to form favorable interactions with an adsorbing protein, leading to protein specific charge patterns, or templates, in the films. Template assessment, however, was complicated by the presence of an irreversibly bound protein fraction, which AFM revealed to be locally ordered protein clusters.     

Combined morphological and molecular analysis of individual nematodes through short‐term preservation in formalin

Small metazoans such as marine nematodes are increasingly identified using both molecular and morphological techniques. Formalin is the preferred fixative for morphological analysis but specimens become unsuitable for molecular study due to formalin‐induced modification of DNA. Nematodes fixed in ethanol work well for molecular studies but become unsuitable for taxonomy due to shrinkage. Here we show for the first time that formalin can be used as a short‐term fixative (≤ 7 days) for marine nematodes, allowing both morphological and molecular work to be conducted on the same individual. No sequence ambiguities were detected in polymerase chain reaction (PCR) amplifications of 18S ribosomal DNA (rDNA) following short‐term formalin preservation.