High‐order combination effects and biological robustness
Open Access
- 1 January 2008
- journal article
- Published by Springer Nature in Molecular Systems Biology
- Vol. 4 (1) , 215
- https://doi.org/10.1038/msb.2008.51
Abstract
Biological systems are robust, in that they can maintain stable phenotypes under varying conditions or attacks. Biological systems are also complex, being organized into many functional modules that communicate through interlocking pathways and feedback mechanisms. In these systems, robustness and complexity are linked because both qualities arise from the same underlying mechanisms. When perturbed by multiple attacks, such complex systems become fragile in both theoretical and experimental studies, and this fragility depends on the number of agents applied. We explore how this relationship can be used to study the functional robustness of a biological system using systematic high‐order combination experiments. This presents a promising approach toward many biomedical and bioengineering challenges. For example, high‐order experiments could determine the point of fragility for pathogenic bacteria and might help identify optimal treatments against multi‐drug resistance. Such studies would also reinforce the growing appreciation that biological systems are best manipulated not by targeting a single protein, but by modulating the set of many nodes that can selectively control a system's functional state.Keywords
This publication has 55 references indexed in Scilit:
- Combinatorial RNAi for quantitative protein network analysisProceedings of the National Academy of Sciences, 2007
- A robustness-based approach to systems-oriented drug designNature Reviews Drug Discovery, 2007
- Systematic pathway analysis using high-resolution fitness profiling of combinatorial gene deletionsNature Genetics, 2007
- Computational analysis of the synergy among multiple interacting genesMolecular Systems Biology, 2007
- Chemical combination effects predict connectivity in biological systemsMolecular Systems Biology, 2007
- Functional classification of drugs by properties of their pairwise interactionsNature Genetics, 2006
- Multicomponent therapeutics for networked systemsNature Reviews Drug Discovery, 2005
- Biological robustnessNature Reviews Genetics, 2004
- Integration of chemical-genetic and genetic interaction data links bioactive compounds to cellular target pathwaysNature Biotechnology, 2003
- Functional organization of the yeast proteome by systematic analysis of protein complexesNature, 2002