Systems biology of the heart

Noble, Denis

doi:10.1002/047001153x.g308211

Cited by 9 publications

(11 citation statements)

References 52 publications

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“…Because adaptation may involve various aspects of regulation, target validation ideally should integrate not only metabolic, but also signalling and gene‐expression networks (Alberghina and Westerhoff, 2005). So far, however, of the few successful network‐based drug design studies that exist (Noble, 2006), none addresses the potential adaptation of the network.…”

Section: Introductionmentioning

confidence: 99%

A domino effect in drug action: from metabolic assault towards parasite differentiation

Haanstra

Kerkhoven

Tuijl

et al. 2010

Molecular Microbiology

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SummaryAwareness is growing that drug target validation should involve systems analysis of cellular networks. There is less appreciation, though, that the composition of networks may change in response to drugs. If the response is homeostatic (e.g. through upregulation of the target protein), this may neutralize the inhibitory effect. In this scenario the effect on cell growth and survival would be less than anticipated based on affinity of the drug for its target. Glycolysis is the sole free-energy source for the deadly parasite Trypanosoma brucei and is therefore a possible target pathway for anti-trypanosomal drugs. Plasmamembrane glucose transport exerts high control over trypanosome glycolysis and hence the transporter is a promising drug target. Here we show that at high inhibitor concentrations, inhibition of trypanosome glucose transport causes cell death. Most interestingly, sublethal concentrations initiate a domino effect in which network adaptations enhance inhibition. This happens via (i) metabolic control exerted by the target protein, (ii) decreases in mRNAs encoding the target protein and other proteins in the same pathway, and (iii) partial differentiation of the cells leading to (low) expression of immunogenic insect-stage coat proteins. We discuss how these 'anti-homeostatic' responses together may facilitate killing of parasites at an acceptable drug dosage.

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Section: Introductionmentioning

confidence: 99%

A domino effect in drug action: from metabolic assault towards parasite differentiation

Haanstra

Kerkhoven

Tuijl

et al. 2010

Molecular Microbiology

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“…Despite the significant progress that has been made in the development of computational atrial cardiomyocyte models and their application to study AF mechanisms, numerous challenges remain. The present modelling approach reflects a ‘middle‐out approach’ (Noble, ), in which most models have an intermediate level of complexity (i.e. deterministic common‐pool models to simulate APs and whole‐cell Ca 2+ transients), corresponding to the amount of available experimental data (Fig.…”

Section: Introductionmentioning

confidence: 99%

“…To create the hierarchical, multiscale understanding of AF that is needed to optimally develop novel antiarrhythmic therapies, models will also have to be extended from this cellular level in both subcellular and multicellular directions (Noble, ), and will have to cover a larger range of time scales (Fig. B ).…”

Section: Introductionmentioning

confidence: 99%

Computational models of atrial cellular electrophysiology and calcium handling, and their role in atrial fibrillation

Heijman

Abdoust

Voigt

et al. 2015

The Journal of Physiology

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The complexity of the heart makes an intuitive understanding of the relative contribution of ion channels, transporters and signalling pathways to cardiac electrophysiology challenging. Computational modelling of cardiac cellular electrophysiology has proven useful to integrate experimental findings, extrapolate results obtained in expression systems or animal models to other systems, test quantitatively ideas based on experimental data and provide novel hypotheses that are experimentally testable. While the bulk of computational modelling has traditionally been directed towards ventricular bioelectricity, increasing recognition of the clinical importance of atrial arrhythmias, particularly atrial fibrillation, has led to widespread efforts to apply computational approaches to understanding atrial electrical function. The increasing availability of detailed, atrial‐specific experimental data has stimulated the development of novel computational models of atrial‐cellular electrophysiology and Ca2+ handling. To date, more than 300 studies have employed mathematical simulations to enhance our understanding of atrial electrophysiology, arrhythmogenesis and therapeutic responses. Future modelling studies are likely to move beyond current whole‐cell models by incorporating new data on subcellular architecture, macromolecular protein complexes, and localized ion‐channel regulation by signalling pathways. At the same time, more integrative multicellular models that take into account regional electrophysiological and Ca2+ handling properties, mechano‐electrical feedback and/or autonomic regulation will be needed to investigate the mechanisms governing atrial arrhythmias. A combined experimental and computational approach is expected to provide the more comprehensive understanding of atrial arrhythmogenesis that is required to develop improved diagnostic and therapeutic options. Here, we review this rapidly expanding area, with a particular focus on Ca2+ handling, and provide ideas about potential future directions.

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“…For the actual construction of a model, three major directions of discovery have been formulated: bottom‐up, top‐down and middle‐out (term credited to Sydney Brenner, in Noble76). For dynamic models, the bottom‐up approach is still prevalent, thanks to the complexity of the systems and to the fact that even the behaviour of individual pathways is rarely understood.…”

Section: Introductionmentioning

confidence: 99%

Modelling dynamic processes in yeast

Klipp

2007

Yeast

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Yeast molecular and cell biology has accumulated large amounts of qualitative and quantitative data of diverse cellular processes. The results are often summarized as verbal or graphical descriptions. Moreover, a series of mathematical models has been developed that should help to interpret such data, to integrate them into a coherent picture and to allow for an understanding of the underlying processes. Dynamic modelling of regulatory processes in yeast focuses on central carbon metabolism, on a number of selected signalling pathways and on cell cycle regulation. These models can explain questions of general relevance, such as whether the dynamics of a network can be understood from the combination of in vitro kinetics of its individual reactions. They help to elucidate complicated dynamic features, such as glycolytic oscillations, effects of feedback regulation or the optimal regulation of gene expression. The availability of comprehensive qualitative information, such as protein interactions or pathway composition, and sets of quantitative data make yeast a perfect model organism. Therefore, yeast-related data are often used to develop and examine computational approaches and modelling methods.

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Systems biology of the heart

Cited by 9 publications

References 52 publications

A domino effect in drug action: from metabolic assault towards parasite differentiation

A domino effect in drug action: from metabolic assault towards parasite differentiation

Computational models of atrial cellular electrophysiology and calcium handling, and their role in atrial fibrillation

Modelling dynamic processes in yeast

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