Confidence from uncertainty - A multi-target drug screening method from robust control theory

Background Robustness is a recognized feature of biological systems that evolved as a defence to environmental variability. Complex diseases such as diabetes, cancer, bacterial and viral infections, exploit the same mechanisms that allow for robust behaviour in healthy conditions to ensure their own...

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Vydáno v:	BMC systems biology Ročník 4; číslo 1; s. 161
Hlavní autoři:	Luni, Camilla, Shoemaker, Jason E, Sanft, Kevin R, Petzold, Linda R, Doyle, Francis J
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London BioMed Central 24.11.2010 BioMed Central Ltd
Témata:	Algorithms Antibiotics Behavior Bioinformatics Biomedical and Life Sciences Cellular and Medical Topics Computational Biology/Bioinformatics Computer science Confidence Diabetes Drug Evaluation, Preclinical - methods Drug therapy Feedback, Physiological Genes Health aspects Life Sciences Mandatory drug testing Methodology Methodology Article Methods Models, Biological Ordinary differential equations Physiological Physiological aspects Signal transduction Simulation and Modeling Studies Systems Biology Systems Biology - methods Uncertainty United States Stochastic Simulation Algorithm Robust Performance System Biology Markup Language Nominal Performance Local Sensitivity Analysis
ISSN:	1752-0509, 1752-0509
On-line přístup:	Získat plný text
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Popis
Shrnutí:	Background Robustness is a recognized feature of biological systems that evolved as a defence to environmental variability. Complex diseases such as diabetes, cancer, bacterial and viral infections, exploit the same mechanisms that allow for robust behaviour in healthy conditions to ensure their own continuance. Single drug therapies, while generally potent regulators of their specific protein/gene targets, often fail to counter the robustness of the disease in question. Multi-drug therapies offer a powerful means to restore disrupted biological networks, by targeting the subsystem of interest while preventing the diseased network from reconciling through available, redundant mechanisms. Modelling techniques are needed to manage the high number of combinatorial possibilities arising in multi-drug therapeutic design, and identify synergistic targets that are robust to system uncertainty. Results We present the application of a method from robust control theory, Structured Singular Value or μ- analysis, to identify highly effective multi-drug therapies by using robustness in the face of uncertainty as a new means of target discrimination. We illustrate the method by means of a case study of a negative feedback network motif subject to parametric uncertainty. Conclusions The paper contributes to the development of effective methods for drug screening in the context of network modelling affected by parametric uncertainty. The results have wide applicability for the analysis of different sources of uncertainty like noise experienced in the data, neglected dynamics, or intrinsic biological variability.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ISSN:	1752-0509 1752-0509
DOI:	10.1186/1752-0509-4-161