Molecular Interaction Map Research Articles

Plant Behaviour Special Issue

Terrestrial plants are sessile. However, their life is not still, but an exercise of continuous exploration. Plants explore their environment seeking favourable microsites for light capture and nutrient absorption, and avoiding places where resources are highly contested. Animals do this by movement; plants by growing and discarding organs, or by changing the shape of these organs. If good conditions are not found, plants often adjust their form and physiology to tolerate adversity. In long-lived plants, like the pines illustrated in the cover photographs and described in the associated legend, this foraging behaviour literally leaves its mark in the trunks. Plant behaviours require an exquisite ability to assess the external conditions and use acquired information to make adaptive decisions. In the last few years, plant biologists have made major advances in understanding how plants read their environment and how they activate internal signalling mechanisms that lead to the expression of effective responses. We are now beginning to piece together the first maps of molecular interactions that control the development of plant architecture, the physiology of shoots and roots, and the expression of plant defences against natural enemies in response to informational signals gathered by a variety of sensory mechanisms. This Special Issue of Plant Cell & Environment presents a collection of papers on plant behaviour that will challenge all plant biologists. The following papers consider the definition and use of the term behaviour as applied to plants, the use of informational language to incorporate concepts such as learning and intelligence in the description of plant behaviour, the mechanisms that allow the plant to forage for resources and modify their body shape and function to cope with multiple environmental and biotic stresses, and the ecological consequences of behavioural responses. For far too long plant behaviour has languished in the shade of its more easily investigated animal counterpart. This issue highlights the growing realisation that plant behaviour has not only come of age but that fully understanding its complexity will become the primary task for plant biologists for the rest of this century.

Cataloging and organizing p73 interactions in cell cycle arrest and apoptosis

We have compiled the p73-mediated cell cycle arrest and apoptosis pathways. p73 is a member of the p53 family, consisting of p53, p63 and p73. p73 exists in several isoforms, presenting different domain structures. p73 functions not only as a tumor suppressor in apoptosis but also as differentiator in embryo development. p53 mutations are responsible for half of the human cancers; p73 can partially substitute mutant p53 as tumor suppressor. The pathways we assembled create a p73-centered network consisting of 53 proteins and 176 interactions. We clustered our network into five functional categories: Upregulation, Activation, Suppression, Transcriptional Activity and Degradation. Our literature searches led to discovering proteins (c-Jun and pRb) with apparent opposing functional effects; these indicate either currently missing proteins and interactions or experimental misidentification or functional annotation. For convenience, here we present the p73 network using the molecular interaction map (MIM) notation. The p73 MIM is unique amongst MIMs, since it further implements detailed domain features. We highlight shared pathways between p53 and p73. We expect that the compiled and organized network would be useful to p53 family-based studies.

A comprehensive modular map of molecular interactions in RB/E2F pathway

We present, here, a detailed and curated map of molecular interactions taking place in the regulation of the cell cycle by the retinoblastoma protein (RB/RB1). Deregulations and/or mutations in this pathway are observed in most human cancers. The map was created using Systems Biology Graphical Notation language with the help of CellDesigner 3.5 software and converted into BioPAX 2.0 pathway description format. In the current state the map contains 78 proteins, 176 genes, 99 protein complexes, 208 distinct chemical species and 165 chemical reactions. Overall, the map recapitulates biological facts from approximately 350 publications annotated in the diagram. The network contains more details about RB/E2F interaction network than existing large-scale pathway databases. Structural analysis of the interaction network revealed a modular organization of the network, which was used to elaborate a more summarized, higher-level representation of RB/E2F network. The simplification of complex networks opens the road for creating realistic computational models of this regulatory pathway.

Chromatin Challenges during DNA Replication: A Systems Representation

In a recent review, A. Groth and coworkers presented a comprehensive account of nucleosome disassembly in front of a DNA replication fork, assembly behind the replication fork, and the copying of epigenetic information onto the replicated chromatin. Understanding those processes however would be enhanced by a comprehensive graphical depiction analogous to a circuit diagram. Accordingly, we have constructed a molecular interaction map (MIM) that preserves in essentially complete detail the processes described by Groth et al. The MIM organizes and elucidates the information presented by Groth et al. on the complexities of chromatin replication, thereby providing a tool for system-level comprehension of the effects of genetic mutations, altered gene expression, and pharmacologic intervention.

Interfering with Protein-Protein Contact: Molecular Interaction Maps and Peptide Modulators

Protein-protein interactions (PPIs) can be useful targets for different pathologies. In fact controlling a function or attempting to repair an anomaly often means interfering with the cross-talk among different proteins. In order to have a general view of these cross-talks, Molecular Interaction Maps (MIMs) are used, organizing the enormous available information that is added every day and trying to understand the most suitable and accurate targets for any specific cell alteration. In this paper the c-Myc protein is taken as an example to explain the use of a map. The discovery of a peptidomimetic antagonist of c-Myc, active against proliferation of cancer cell lines, is reported and a possible mechanism of action is explained. To interfere with a specific protein-protein contact, a good starting point can be to consider a protein entity. Because the interaction between two proteins is normally characterized by a wide zone of contact, relative large inhibitors could be more convenient in the first approaches. Therefore, peptides mimicking the interacting zone can be considered as potential leads in the rational design of effective molecules. Here different examples of peptides as protein-protein interaction inhibitors are reported.

Chk2 Molecular Interaction Map and Rationale for Chk2 Inhibitors

To organize the rapidly accumulating information on bioregulatory networks related to the histone gamma-H2AX-ATM-Chk2-p53-Mdm2 pathways in concise and unambiguous diagrams, we used the molecular interaction map notation (http://discover.nci.nih.gov/min). Molecular interaction maps are particularly useful for networks that include protein-protein binding and posttranslational modifications (e.g., phosphorylation). Both are important for nearly all of the proteins involved in DNA double-strand break signaling. Visualizing the regulatory circuits underlying cellular signaling may help identify key regulatory reactions and defects that can serve as targets for anticancer drugs.

Depicting combinatorial complexity with the molecular interaction map notation

To help us understand how bioregulatory networks operate, we need a standard notation for diagrams analogous to electronic circuit diagrams. Such diagrams must surmount the difficulties posed by complex patterns of protein modifications and multiprotein complexes. To meet that challenge, we have designed the molecular interaction map (MIM) notation (http://discover.nci.nih.gov/mim/). Here we show the advantages of the MIM notation for three important types of diagrams: (1) explicit diagrams that define specific pathway models for computer simulation; (2) heuristic maps that organize the available information about molecular interactions and encompass the possible processes or pathways; and (3) diagrams of combinatorially complex models. We focus on signaling from the epidermal growth factor receptor family (EGFR, ErbB), a network that reflects the major challenges of representing in a compact manner the combinatorial complexity of multimolecular complexes. By comparing MIMs with other diagrams of this network that have recently been published, we show the utility of the MIM notation. These comparisons may help cell and systems biologists adopt a graphical language that is unambiguous and generally understood.

Modularity and Dynamics of Cellular Networks

Understanding how the phenotypes and behaviors of cells are controlled is one of the major challenges in biological research. Traditionally, focus has been given to the characterization of individual genes/proteins or individual interactions during cellular events. However, many phenotypes and behaviors cannot be attributed to isolated components. Rather, they arise from characteristics of cellular networks, which represent connections between molecules in cells. We review the recent progress on analyzing the architecture and dynamics of cellular networks. We also summarize how computational modeling yields insight about cell signaling pathways. The responses of cells to genetic perturbations or environmental cues are controlled by complex networks, including interconnected signaling pathways and cascades of transcriptional programs. The advance of genome technologies has made it possible to analyze cellular events on a global scale. A number of high-throughput techniques, such as DNA microarrays, chromatin immunoprecipitations, and yeast two-hybrid and mass-spectrometry analyses have been applied to cellular systems [1–10]. These experiments have provided first-draft catalogs of essential components, transcriptional regulatory diagrams, and molecular interaction maps for a number of organisms. In addition to providing a candidate list of biomolecules involved in biological processes, the high-throughput technologies offer unprecedented opportunities to derive underlying principles of how complex cellular networks are built and how network architectures contribute to phenotypes. A series of important questions in this area have been addressed recently (Figure 1). For example, what are the characteristics of cellular network structures that distinguish them from randomly generated networks? Are the network structures relevant for biological functions? If so, are they evolutionarily conserved and how do they evolve? Are some topological patterns preferred at certain times or conditions? These questions are analogous to those asked in the field of genome sequence analysis, such as identifying biologically relevant sequence motifs and domains, investigating the evolutionary conservation between sequences from different species, and understanding temporal or spatial specificities of regulatory sites. In this paper, we survey recent progress on addressing these questions and use mammalian cell signaling as case studies to discuss how computational analyses of networks shed light on specific biological processes. Figure 1 An Overview of Biological Network Analyses Based on “Omic” Data

Molecular Interaction Maps of Bioregulatory Networks: A General Rubric for Systems Biology

A standard for bioregulatory network diagrams is urgently needed in the same way that circuit diagrams are needed in electronics. Several graphical notations have been proposed, but none has become standard. We have prepared many detailed bioregulatory network diagrams using the molecular interaction map (MIM) notation, and we now feel confident that it is suitable as a standard. Here, we describe the MIM notation formally and discuss its merits relative to alternative proposals. We show by simple examples how to denote all of the molecular interactions commonly found in bioregulatory networks. There are two forms of MIM diagrams. "Heuristic" MIMs present the repertoire of interactions possible for molecules that are colocalized in time and place. "Explicit" MIMs define particular models (derived from heuristic MIMs) for computer simulation. We show also how pathways or processes can be highlighted on a canonical heuristic MIM. Drawing a MIM diagram, adhering to the rules of notation, imposes a logical discipline that sharpens one's understanding of the structure and function of a network.

Targeting Chk2 Kinase: Molecular Interaction Maps and Therapeutic Rationale

Most anticancer drugs presently used clinically target genomic DNA. The selectivity of these anticancer drugs for tumor tissues is probably due to tumor-specific defects suppressing cell cycle checkpoints and DNA repair, and enhancing apoptotic response in the tumor. We will review the molecular interactions within the ATM-Chk2 pathway implicating the DNA damage sensor kinases (ATM, ATR and DNA-PK), the adaptor BRCT proteins (Nbs1, Brca1, 53BP1, MDC1) and the effector kinases (Chk2, Chk1, Plk3, JNK, p38). The molecular interaction map convention (MIM) will be used for presenting this molecular network (http://discover.nci.nih.gov/mim/). A characteristic of the ATM-Chk2 pathway is its redundancy. First, ATM and Chk2 phosphorylate common substrates including p53, E2F1, BRCA1, and Chk2 itself, which suggests that Chk2 (also known as CHECK2, Cds1 in fission yeast, and Dmchk2 or Dmnk or Loki in the fruit fly) acts as a relay for ATM and/or as a salvage pathway when ATM is inactivated. Secondly, redundancy is apparent for the substrates, which can be phosphorylated/activated at similar residues by Chk2, Chk1, and the polo kinases (Plk's). Functionally, Chk2 can activate both apoptosis (via p53, E2F1 and PML) and cell cycle checkpoint (via Cdc25A and Cdc25C, p53, and BRCA1). We will review the short list of published Chk2 inhibitors. We will also propose a novel paradigm for screening interfacial inhibitors of Chk2. Chk2 inhibitors might be used to enhance the tumor selectivity of DNA targeted agents in p53-deficient tumors, and for the treatment of tumors whose growth depends on enhanced Chk2 activity.

Selective Induction of Apoptosis in Melanoma Cells by Tyrosinase Promoter-Controlled CD95 Ligand Overexpression

Induction of apoptosis has been demonstrated previously by overexpression of CD95 ligand (CD95L) in cultured human melanoma cells. For in vivo approaches based on CD95L, however, targeted expression is a prerequisite and tyrosinase promoters have been considered for selection. Luciferase reporter gene assays performed for a representative panel of melanoma cell lines characterized by strong (SK-Mel-19), moderate (SK-Mel-13, MeWo), weak (A-375), and missing expression (M-5) of endogenous tyrosinase revealed high tyrosinase promoter activities in SK-Mel-19, SK-Mel-13, and MeWo, but only weak activities in A-375 and M-5 as well as in non-melanoma cell lines. After transfection of a CMV promoter CD95L expression construct, melanoma cells were found highly sensitive, as compared with non-melanoma cells. By applying a tyrosinase promoter CD95L construct, apoptosis was selectively induced in SK-Mel-19, SK-Mel-13, MeWo as well as in A-375, which was characterized by high CD95 surface expression and high sensitivity to agonistic CD95 activation. M5 and non-melanoma cell lines remained uninfluenced. Also, resistance to agonistic CD95 activation seen in MeWo characterized by weak CD95 surface expression was overcome by overexpression of CD95L. Our investigations provide evidence that tyrosinase promoter CD95L constructs may be of value for selective induction of apoptosis in therapeutic strategies for melanoma.

A comprehensive pathway map of epidermal growth factor receptor signaling

The epidermal growth factor receptor (EGFR) signaling pathway is one of the most important pathways that regulate growth, survival, proliferation, and differentiation in mammalian cells. Reflecting this importance, it is one of the best-investigated signaling systems, both experimentally and computationally, and several computational models have been developed for dynamic analysis. A map of molecular interactions of the EGFR signaling system is a valuable resource for research in this area. In this paper, we present a comprehensive pathway map of EGFR signaling and other related pathways. The map reveals that the overall architecture of the pathway is a bow-tie (or hourglass) structure with several feedback loops. The map is created using CellDesigner software that enables us to graphically represent interactions using a well-defined and consistent graphical notation, and to store it in Systems Biology Markup Language (SBML).

Systems Biology

Systems Biology

Metabolic Syndrome and Robustness Tradeoffs

The metabolic syndrome is a highly complex breakdown of normal physiology characterized by obesity, insulin resistance, hyperlipidemia, and hypertension. Type 2 diabetes is a major manifestation of this syndrome, although increased risk for cardiovascular disease (CVD) often precedes the onset of frank clinical diabetes. Prevention and cure for this disease constellation is of major importance to world health. Because the metabolic syndrome affects multiple interacting organ systems (i.e., it is a systemic disease), a systems-level analysis of disease evolution is essential for both complete elucidation of its pathophysiology and improved approaches to therapy. The goal of this review is to provide a perspective on systems-level approaches to metabolic syndrome, with particular emphasis on type 2 diabetes. We consider that metabolic syndromes take over inherent dynamics of our body that ensure robustness against unstable food supply and pathogenic infections, and lead to chronic inflammation that ultimately results in CVD. This exemplifies how trade-offs between robustness against common perturbations (unstable food and infections) and fragility against unusual perturbations (high-energy content foods and low-energy utilization lifestyle) is exploited to form chronic diseases. Possible therapeutic approaches that target fragility of emergent robustness of the disease state have been discussed. A detailed molecular interaction map for adipocyte, hepatocyte, skeletal muscle cell, and pancreatic beta-cell cross-talk in the metabolic syndrome can be viewed at http://www.systems-biology.org/001/003.html.

417 The ATM-Chk2 kinase pathway: molecular interaction maps and therapeutic rationale

The antiproliferative effect of Tempol, a stable nitroxide free radical, was investigated on the p53-negative human leukemia cell line HL60. A concentration- and time-dependent inhibition of cell growth was observed that appears to be due to induction of apoptosis. Involvement of oxidative stress is indicated by a concentration-dependent increase in intracellular peroxides and a parallel decrease in total cellular glutathione; in addition, increased survival rates were observed in cells simultaneously treated with Tempol and the antioxidant N-acetylcysteine. Tempol did not affect the relative levels of Bax and Bcl2, whereas p21WAF1/CIP1 was enhanced in a concentration- and time-dependent fashion; this effect was partially inhibited by N-acetylcysteine, was maintained for up to 8 h after Tempol removal, and seemed to depend on continuing protein synthesis. The increase in p21WAF1/CIP1 was accompanied by a parallel accumulation of cells in the G1 phase of the cycle and by a decrease in the 110 kDa form of pRb. Our results suggest that p53-independent induction of p21WAF1/CIP1 mediates the antiproliferative effect of Tempol; on the basis of this observation, the nitroxide could be proposed as an useful adjunct to the treatment of p53-deficient tumors, which are often refractory to standard chemotherapy.

Properties of switch-like bioregulatory networks studied by simulation of the hypoxia response control system.

A complex bioregulatory network could be more easily comprehended if its essential function could be described by a small "core" subsystem, and if its response characteristics were switch-like. We tested this proposition by simulation studies of the hypoxia response control network. We hypothesized that a small subsystem governs the basics of the cellular response to hypoxia and that this response has a sharp oxygen-dependent transition. A molecular interaction map of the network was prepared, and an evolutionarily conserved core subsystem was extracted that could control the activity of hypoxia response promoter elements on the basis of oxygen concentration. The core subsystem included the hypoxia-inducible transcription factor (HIFalpha:ARNT heterodimer), proline hydroxylase, and the von Hippel-Lindau protein. Simulation studies showed that the same core subsystem can exhibit switch-like responses both to oxygen level and to HIFalpha synthesis rate, thus suggesting a mechanism for hypoxia response promoter element-dependent responses common to both hypoxia and growth factor signaling. The studies disclosed the mechanism responsible for the sharp transitions. We show how parameter sets giving switch-like behavior can be found and how this type of behavior provides a foundation for quantitative studies in cells.

Apoptosis defects and chemotherapy resistance: molecular interaction maps and networks.

Intrinsic (innate) and acquired (adaptive) resistance to chemotherapy critically limits the outcome of cancer treatments. For many years, it was assumed that the interaction of a drug with its molecular target would yield a lethal lesion, and that determinants of intrinsic drug resistance should therefore be sought either at the target level (quantitative changes or/and mutations) or upstream of this interaction, in drug metabolism or drug transport mechanisms. It is now apparent that independent of the factors above, cellular responses to a molecular lesion can determine the outcome of therapy. This review will focus on programmed cell death (apoptosis) and on survival pathways (Bcl-2, Apaf-1, AKT, NF-kappaB) involved in multidrug resistance. We will present our molecular interaction mapping conventions to summarize the AKT and IkappaB/NF-kappaB networks. They complement the p53, Chk2 and c-Abl maps published recently. We will also introduce the 'permissive apoptosis-resistance' model for the selection of multidrug-resistant cells.

Molecular interaction maps--a diagrammatic graphical language for bioregulatory networks.

Molecular interaction maps (MIMs) use a clear, accurate, and versatile graphical language to depict complex biological processes. Here, we discuss the main features of the MIM language and its potential uses. MIMs can be used as database resources and simulation guides, and can serve to generate new hypotheses regarding the roles of specific molecules in the bioregulatory networks that control progression through the cell cycle, differentiation, and cell death.

Integration of Postgenomic Data for GMA to Simulate a Metabolic Circuit

In order to understand cell metabolism as a system, it is important to formulize its molecular interaction network and to analyze it in the system level. In the postgenomic era, various experimental data such as transcriptome, proteome, and metabolome have accumulated rapidly. Such information is greatly available for constructing a molecular interaction map and simulating its dynamic features. We aim at developing the strategy that integrates such postgenomic data efficiently for simulating a metabolic system. General Mass Action (GMA) is a powerful candidate that integrates the postgenomic data [1], because GMA readily employs the profile of metabolite concentrations, fluxes, and enzyme concentrations. Then, a problem is that it is difficult to measure the kinetic parameters in vivo based on the above technologies. Generally, the measurement of a kinetic parameter requires the extensive and laborious experiments based on the kinetic theory. Therefore, we present a novel strategy that connects the postgenomic data to the GMA simulation.

Molecular interaction maps as information organizers and simulation guides.

A graphical method for mapping bioregulatory networks is presented that is suited for the representation of multimolecular complexes, protein modifications, as well as actions at cell membranes and between protein domains. The symbol conventions defined for these molecular interaction maps are designed to accommodate multiprotein assemblies and protein modifications that can generate combinatorially large numbers of molecular species. Diagrams can either be "heuristic," meaning that detailed knowledge of all possible reaction paths is not required, or "explicit," meaning that the diagrams are totally unambiguous and suitable for simulation. Interaction maps are linked to annotation lists and indexes that provide ready access to pertinent data and references, and that allow any molecular species to be easily located. Illustrative interaction maps are included on the domain interactions of Src, transcription control of E2F-regulated genes, and signaling from receptor tyrosine kinase through phosphoinositides to Akt/PKB. A simple method of going from an explicit interaction diagram to an input file for a simulation program is outlined, in which the differential equations need not be written out. The role of interaction maps in selecting and defining systems for modeling is discussed. (c) 2001 American Institute of Physics.