Generic Properties of Dynamical Models of Protocells

Models are of great importance for protocell research, not only for the usual reasons why models matter, but also because real protocells are not yet available in the lab. There are indeed some cases where one or a few duplications have been achieved (Hanczyc and Szostak 2004; Luisi et al. 2004; Luisi 2006; Stano et al. 2006; Schrum et al. 2010; Stano and Luisi 2010a) but so far, to the best of our knowledge, a sustained growth of a population of protocells has never been observed. We will be particularly interested in models that allow us to explore the generic properties of protocells and of protocell populations. Of course, it is perfectly legitimate to concentrate on a particular hypothesis and to develop specific models well-suited to study its properties. But at the present stage of our knowledge we believe it can be even more important to be able to grasp the generic properties of these systems. Protocells lie somewhere in between chemistry and biology: their ingredients are chemicals, as well as those of living beings. And their wished-for properties are indeed typical of life. That’s why we find it appropriate to discuss here some features of models of biological systems aimed at describing some of their generic properties—a field of research that has been properly referred to as “complex systems biology” (Kaneko 2006). Although it is widely agreed that “biological systems are complex”, there are several important features of the science of complex systems that have not yet deeply affected the study of biological organisms and processes. Indeed, biology has been largely dominated by a gene-centric view in the last decades, and the one gene—one trait approach, which has sometimes proved to be effective, has been extended to cover even complex traits. This simplifying view has been appropriately criticized, and the movement called systems biology (Noble 2006) has taken off. Systems biology emphasizes the presence of several feedback loops in biological systems, which severely limit the range of validity of explanations based