Synthetic biology
Assuming proteins are assembled in a modular fashion, it follows that one can apply principles from modular systems engineering. Thus, by redesigning or reverse engineering of known modular proteins, new synthetic, modular and functional polypeptides could be constructed. By attempting this we can fully explore whether modules have served as building blocks in the evolution of protein function, something that has been suggested from bioinformatics and experimental analysis, but remains to be substantiated for reverse engineered proteins. Such experiments will address the extent to which biological systems actually conform to this paradigm of modularity.


A system with logical, dynamical and programmable behaviour could be assembled from well-defined components/parts (e.g. domains and linear motifs). This approach is different from the classical molecular biology method of creating chimeric proteins by changing an existing system.

 

 The biological potential of modularity in signaling proteins might be explored by designing new proteins in a modular manner (i.e. not at an atomic level). In other words, modules could be joined in an in silico predicted sequence background . This is in contrast with more traditional protein engineering approaches such as “rational design”, “de novo” and “molecular evolution”

 

 

 An integrated approach of in silico and in vivo design, coupled with directed evolution, might allow us to determine fundamental building blocks of selected interaction networks. Engineered proteins can be expressed and tested for predicted functions, refer to Figure 3, such as activation of specific signalling pathways using phospho-specific antibodies (for example to MAP kinases and STAT proteins). This could be performed at the single cell level using flow cytometry with phospho-specific antibodies. Another Approach would be to look at markers of DNA synthesis/apoptosis. These synthetic proteins could function as control units (gates and switches) that allow for switching and gating in cellular or in vitro systems, thus allowing us to rewire or probe signaling pathways.

 

  Emergence in Protein Function
We have previously discussed the possibility that the juxtaposition of interaction domains and motifs in novel combinations may contribute to the evolution of new biological functions. The addition or removal of interaction modules can also be achieved in real time through alternative splicing, which together with post-translational modifications can greatly increase the numbers of protein isoforms in any cell with different binding properties, and potentially with different effects on regulatory networks. It remains unclear how the addition/elimination of domains or motifs might modify the overall complexity and function of a biological system, or might this might give rise to emergence in a cellular system. Informatics studies have shown that a general functional classification of a protein sequence can be performed by looking at its set of “features”, which includes post-translational modifications and other derived parameters [47].
Complexity appears to arise partly as a result of emergent properties of a system, but it is not clear whether our current inventory of modules is sufficiently well defined to describe this in quantitative terms. In this context, building new synthetic systems with chimeric proteins, using the currently known set of signalling components and interaction modules, will allow us to monitor their ability to perturb complexity. Standard network parameters can be measured experimentally, for instance connectivity and average cluster size.

Specificity and Cross-talk in Signalling Pathways
Transient interactions between proteins play an important role in preventing aberrant interactions between pathways in normal cells, and in stimulating cross-talk when this is physiologically desirable. Since these interactions frequently involve the recognition of peptide motifs by modular interaction domains, it is critical to understand how short linear peptides can confer specificity towards their cognate domain partners, especially in cases where their binding affinity is modest. In any one cell, many different members of a particular domain family are likely expressed (yeast for example have 28 SH3 domains), which might then compete for related ligands. Several mechanisms likely act in combination to build specificity. One is expression and subcellular localization – only when two proteins are co-expressed and co-localized will an interaction take place. This allows for combinatorial effects, since one domain may localize a protein, for example to a specific membrane site, thereby directing a second domain to specifically recognize a binding partner. Second, selectivity is driven by both permissive and inhibitory forces, and a steric restriction on binding non-physiological binding partners may therefore be just as important as an ability to engage the appropriate target. Thus, a linear proline-rich motif in the yeast Pbs2 protein, a MAP kinase scaffold, engages the SH3 domain of the Sho1 osmosensor, but does not undergo aberrant crosstalk with other yeast SH3 domains . However the Pbs2 motif does interact promiscuously with SH3 domains from non-yeast species [48]. This has led to the suggestion that an interaction motif need only discriminate between a set of domains that it meets in the context of the cell in which it is expressed, or the subcellular compartment in which it is localized [48].
Although some interaction domains show a very specific interaction with a single target, this usually applies only to proteins with highly specialized functions in one or a few cell types. In a biological setting, most interaction domains likely have numerous partners, which may differ according to the cell type, or within a single cell depending on the environmental conditions. Thus, it may be dangerous to assign an interaction domain to a unique function in a cellular network, when its connectivity is likely undergoing constant flux.

 

 

 

Last Updated ( Saturday, 09 September 2006 )