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Computational modeling of the EGFR network elucidates control mechanisms regulating signal dynamics.

ABSTRACT: BACKGROUND: The epidermal growth factor receptor (EGFR) signaling pathway plays a key role in regulation of cellular growth and development. While highly studied, it is still not fully understood how the signal is orchestrated. One of the reasons for the complexity of this pathway is the extensive network of inter-connected components involved in the signaling. In the aim of identifying critical mechanisms controlling signal transduction we have performed extensive analysis of an executable model of the EGFR pathway using the stochastic pi-calculus as a modeling language. RESULTS: Our analysis, done through simulation of various perturbations, suggests that the EGFR pathway contains regions of functional redundancy in the upstream parts; in the event of low EGF stimulus or partial system failure, this redundancy helps to maintain functional robustness. Downstream parts, like the parts controlling Ras and ERK, have fewer redundancies, and more than 50% inhibition of specific reactions in those parts greatly attenuates signal response. In addition, we suggest an abstract model that captures the main control mechanisms in the pathway. Simulation of this abstract model suggests that without redundancies in the upstream modules, signal transduction through the entire pathway could be attenuated. In terms of specific control mechanisms, we have identified positive feedback loops whose role is to prolong the active state of key components (e.g., MEK-PP, Ras-GTP), and negative feedback loops that help promote signal adaptation and stabilization. CONCLUSIONS: The insights gained from simulating this executable model facilitate the formulation of specific hypotheses regarding the control mechanisms of the EGFR signaling, and further substantiate the benefit to construct abstract executable models of large complex biological networks.

SUBMITTER: Wang DY

PROVIDER: S-EPMC2807436 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

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Computational modeling of the EGFR network elucidates control mechanisms regulating signal dynamics.

Wang Dennis Y Q DY Cardelli Luca L Phillips Andrew A Piterman Nir N Fisher Jasmin J

BMC systems biology 20091222

<h4>Background</h4>The epidermal growth factor receptor (EGFR) signaling pathway plays a key role in regulation of cellular growth and development. While highly studied, it is still not fully understood how the signal is orchestrated. One of the reasons for the complexity of this pathway is the extensive network of inter-connected components involved in the signaling. In the aim of identifying critical mechanisms controlling signal transduction we have performed extensive analysis of an executab ...[more]

PMID: 20028552

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Project description:Hsp90 is a molecular chaperone essential for protein folding and activation in normal homeostasis and stress response. ATP binding and hydrolysis facilitate Hsp90 conformational changes required for client activation. Hsp90 plays an important role in disease states, particularly in cancer, where chaperoning of the mutated and overexpressed oncoproteins is important for function. Recent studies have illuminated mechanisms related to the chaperone function. However, an atomic resolution view of Hsp90 conformational dynamics, determined by the presence of different binding partners, is critical to define communication pathways between remote residues in different domains intimately affecting the chaperone cycle. Here, we present a computational analysis of signal propagation and long-range communication pathways in Hsp90. We carried out molecular dynamics simulations of the full-length Hsp90 dimer, combined with essential dynamics, correlation analysis, and a signal propagation model. All-atom MD simulations with timescales of 70 ns have been performed for complexes with the natural substrates ATP and ADP and for the unliganded dimer. We elucidate the mechanisms of signal propagation and determine "hot spots" involved in interdomain communication pathways from the nucleotide-binding site to the C-terminal domain interface. A comprehensive computational analysis of the Hsp90 communication pathways and dynamics at atomic resolution has revealed the role of the nucleotide in effecting conformational changes, elucidating the mechanisms of signal propagation. Functionally important residues and secondary structure elements emerge as effective mediators of communication between the nucleotide-binding site and the C-terminal interface. Furthermore, we show that specific interdomain signal propagation pathways may be activated as a function of the ligand. Our results support a "conformational selection model" of the Hsp90 mechanism, whereby the protein may exist in a dynamic equilibrium between different conformational states available on the energy landscape and binding of a specific partner can bias the equilibrium toward functionally relevant complexes.

Project description:BackgroundColorectal cancer is one of the most prevalent causes of cancer death. It has been studied extensively for a long time, and numerous genetic and epigenetic events have been associated with the disease. However, its molecular mechanisms are still unclear. High-throughput metabolomics data, combined with customized computational systems modeling, can assist our understanding of some of these mechanisms by revealing connections between alterations in enzymatic activities and their consequences for a person's metabolic profile. Of particular importance in this context is purine metabolism, as it provides the nucleotides needed for cell proliferation.Methods and findingsWe employ a computational systems approach to infer molecular mechanisms associated with purine metabolism in colorectal carcinoma. The approach uses a dynamic model of purine metabolism as the simulation system and metabolomics data as input. The execution of large-scale Monte Carlo simulations and optimization with the model permits a step-wise reduction in possibly affected enzyme mechanisms, from which likely targets emerge.ConclusionsAccording to our results, some enzymes in the purine pathway system are very unlikely the targets of colorectal carcinoma. In fact, only three enzymatic steps emerge with statistical confidence as most likely being affected, namely: amidophosphoribosyltransferase (ATASE), 5'-nucleotidase (5NUC), and the xanthine oxidase/dehydrogenase (XD) reactions. The first of these enzymes catalyzes the first committed step of de novo purine biosynthesis, while the other two enzymes are associated with critical purine salvage pathways. The identification of these enzymes is statistically significant and robust. In addition, the results suggest potential secondary targets. The computational method cannot discern whether the inferred mechanisms constitute symptoms of colorectal carcinoma, or whether they might be causative and critical components of the uncontrolled cellular growth in cancer. The inferred molecular mechanisms present testable hypotheses that suggest targeted experiments for future studies of colorectal carcinoma and might eventually lead to improved diagnosis and treatment.

Dataset Information

Computational modeling of the EGFR network elucidates control mechanisms regulating signal dynamics.

Publications

Computational modeling of the EGFR network elucidates control mechanisms regulating signal dynamics.

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