Sloppiness, robustness, and evolvability in systems biology

TL;DR

This paper explores how biochemical networks exhibit robustness and evolvability through the concepts of sloppiness and neutral spaces, offering insights into their structural properties and implications for biological function.

Contribution

It introduces the idea that sloppiness in multiparameter models explains robustness and evolvability without requiring adaptive evolution, expanding understanding of system behavior.

Findings

Biochemical networks are often 'sloppy' with many insensitive parameters.

Robustness can arise from inherent sloppiness, not just adaptive evolution.

Sloppiness and neutral spaces are key to understanding biological system stability.

Abstract

The functioning of many biochemical networks is often robust -- remarkably stable under changes in external conditions and internal reaction parameters. Much recent work on robustness and evolvability has focused on the structure of neutral spaces, in which system behavior remains invariant to mutations. Recently we have shown that the collective behavior of multiparameter models is most often 'sloppy': insensitive to changes except along a few 'stiff' combinations of parameters, with an enormous sloppy neutral subspace. Robustness is often assumed to be an emergent evolved property, but the sloppiness natural to biochemical networks offers an alternative non-adaptive explanation. Conversely, ideas developed to study evolvability in robust systems can be usefully extended to characterize sloppy systems.