Self-organization in prebiological systems: simulations of a model for the origin of genetic information

Protein folding - seeing is deceiving

This Perspective is intended to raise questions about the conventional interpretation of protein folding. According to the conventional interpretation, developed over many decades, a protein population can visit a vast number of conformations under unfolding conditions, but a single dominant native population emerges under folding conditions. Accordingly, folding comes with a substantial loss of conformational entropy. How is this price paid? The conventional answer is that favorable interactions between and among the side chains can compensate for entropy loss, and moreover, these interactions are responsible for the structural particulars of the native conformation. Challenging this interpretation, the Perspective introduces a proposal that high energy (i.e., unfavorable) excluding interactions winnow the accessible population substantially under physical-chemical conditions that favor folding. Both steric clash and unsatisfied hydrogen bond donors and acceptors are classified as excluding interactions, so called because conformers with such disfavored interactions will be largely excluded from the thermodynamic population. Both excluding interactions and solvent factors that induce compactness are somewhat nonspecific, yet together they promote substantial chain organization. Moreover, proteins are built on a backbone scaffold consisting of α-helices and strands of β-sheet, where the number of hydrogen bond donors and acceptors is exactly balanced. These repetitive secondary structural elements are the only two conformers that can be both completely hydrogen-bond satisfied and extended indefinitely without encountering a steric clash. Consequently, the number of fundamental folds is limited to no more than ~10,000 for a protein domain. Once excluding interactions are taken into account, the issue of "frustration" is largely eliminated and the Levinthal paradox is resolved. Putting the "bottom line" at the top: it is likely that hydrogen-bond satisfaction represents a largely under-appreciated parameter in protein folding models.

Identifying immunologically-vulnerable regions of the HCV E2 glycoprotein and broadly neutralizing antibodies that target them

Isolation of broadly neutralizing human monoclonal antibodies (HmAbs) targeting the E2 glycoprotein of Hepatitis C virus (HCV) has sparked hope for effective vaccine development. Nonetheless, escape mutations have been reported. Ideally, a potent vaccine should elicit HmAbs that target regions of E2 that are most difficult to escape. Here, aimed at addressing this challenge, we develop a predictive in-silico evolutionary model for E2 that identifies one such region, a specific antigenic domain, making it an attractive target for a robust antibody response. Specific broadly neutralizing HmAbs that appear difficult to escape from are also identified. By providing a framework for identifying vulnerable regions of E2 and for assessing the potency of specific antibodies, our results can aid the rational design of an effective prophylactic HCV vaccine.

A good vaccine should direct the immune response to virus regions that are most difficult to escape. Here, Quadeer et al. develop a predictive in-silico evolutionary model for HCV E2 which identifies one such antigenic region and identifies multiple broadly neutralizing human antibodies that appear difficult to escape from.

A fission-fusion origin for life

To develop a comprehensive 'cells-first' approach to the origin of life, we propose that protocells form spontaneously and that the fission and fusion of these protocells drives the dynamics of their evolution. The fitness criterion for this evolution is taken to be the the stability (conservation) of domains in the protocellular membrane as determined by non-covalent molecular associations between the amphiphiles of the membrane and a subset of the macromolecules in the protocell. In the presence of a source of free energy the macromolecular content of the protocell (co-)evolves as the result of (domain-dependent) membrane-catalysed polymerisation of the prebiotic constituents delivered to the protocell by fusion. The metabolism of the cell therefore (co-)evolves on a rugged fitness landscape. We indicate how domain evolution with the same fitness criterion can potentially give rise to coding. Membrane domains may therefore provide the link between protocells and the RNA/DNA-world.

Development of a spin-glass model of prebiotic evolution: environmental effects on ensembles of genetic polymers

We develop in two ways an existing spin-glass model of prebiotic polymer evolution. First, by choosing the environment J in a prescribed manner, similar to neural network presciptions, we may create an environment which favors a linearly independent set of evolutionary niches (Ea). That is, we may control which polymer "species" will evolve in our system. Computer simulations confirm this result. We obtain a quantitative value for the sharpness of a niche. Second, we extend the model by allowing a surviving polymer to act upon--to "remold"--its environment; the nature of the environmental action is governed by the "molding" matrix M. When the mold M is the identity matrix, the feedback algorithm reduces to a Hebb learning algorithm form, and a surviving polymer acts to enhance its own survival prospects. Molds having a structure analogous to (temporal) associative memories in neural networks can generate autocatalytic species or can exhibit symbiotic interspecies relationships.

Population dynamics in a spin-glass model of chemical evolution

We introduce a simple model describing the evolution of a population of information-carrying macromolecules. We discuss the asymptotic dependence of the variability of the population on different parameters, representing the severity or the fluctuations of the environment. We show the existence of a transition separating a neutralist evolutionary regime from a trapped one. We investigate the dependence of the evolutionary behavior of the population on the correlation properties of the fitness landscape.

A model of autocatalytic replication

The catalytic effects that existing polymer chains have on the formation of new chains are modeled using ideas from spin glasses and neural networks. Computer simulation shows that isolated groups of chains in this model are capable of accurately replicating a wide variety of complex structures without templating. Replication in the model arises spontaneously and rapidly, leading to an extremely simple realization of a system exhibiting Darwinian evolution.