The actinin family of actin crosslinking proteins: natural functions and potential applications in synthetic biology

Actinin and spectrin proteins are members of the Spectrin Family of Actin Crosslinking Proteins. The importance of these proteins in the cytoskeleton is demonstrated by the fact that they are common targets for disease causing mutations. In their most prominent roles, actinin and spectrin are responsible for stabilising and maintaining the muscle architecture during contraction, and providing shape and elasticity to the red blood cell in circulation, respectively. To carry out such roles, actinin and spectrin must possess important mechanical and physical properties. These attributes are desirable when choosing a building block for protein-based nanoconstruction. In this study, I assess the contribution of several disease-associated mutations in the actinin-1 actin binding domain that have recently been linked to a rare platelet disorder, congenital macrothrombocytopenia. I investigate the suitability of both actinin and spectrin proteins as potential building blocks for nanoscale structures, and I evaluate a fusion-based assembly strategy to bring about self-assembly of protein nanostructures. I report that the actinin-1 mutant proteins display increased actin binding compared to WT actinin-1 proteins. I find that both actinin and spectrin proteins exhibit enormous potential as nano-building blocks in terms of their stability and ability to self-assemble, and I successfully design and create homodimeric and heterodimeric bivalent building blocks using the fusion-based assembly strategy. Overall, this study has gathered helpful information that will contribute to furthering the advancement of actinin and spectrin knowledge in terms of their natural functions, and potential unnatural functions in protein nanotechnology.

Preference inference based on Pareto models

In this paper, we consider Preference Inference based on a generalised form of Pareto order. Preference Inference aims at reasoning over an incomplete specification of user preferences. We focus on two problems. The Preference Deduction Problem (PDP) asks if another preference statement can be deduced (with certainty) from a set of given preference statements. The Preference Consistency Problem (PCP) asks if a set of given preference statements is consistent, i.e., the statements are not contradicting each other. Here, preference statements are direct comparisons between alternatives (strict and non-strict). It is assumed that a set of evaluation functions is known by which all alternatives can be rated. We consider Pareto models which induce order relations on the set of alternatives in a Pareto manner, i.e., one alternative is preferred to another only if it is preferred on every component of the model. We describe characterisations for deduction and consistency based on an analysis of the set of evaluation functions, and present algorithmic solutions and complexity results for PDP and PCP, based on Pareto models in general and for a special case. Furthermore, a comparison shows that the inference based on Pareto models is less cautious than some other types of well-known preference model.