In Situ Deprotection and Incorporation of Unnatural Amino Acids during Cell‐Free Protein Synthesis

The S30 extract from E. coli BL21 Star (DE3) used for cell‐free protein synthesis removes a wide range of α‐amino acid protecting groups by cleaving α‐carboxyl hydrazides; methyl, benzyl, tert‐butyl, and adamantyl esters; tert‐butyl and adamantyl carboxamides; α‐amino form‐, acet‐, trifluoroacet‐, and benzamides; and side‐chain hydrazides and esters. The free amino acids are produced and incorporated into a protein under standard conditions. This approach allows the deprotection of amino acids to be carried out in situ to avoid separate processing steps. The advantages of this approach are demonstrated by the efficient incorporation of the chemically intractable (S)‐4‐fluoroleucine, (S)‐4,5‐dehydroleucine, and (2S,3R)‐4‐chlorovaline into a protein through the direct use of their respective precursors, namely, (S)‐4‐fluoroleucine hydrazide, (S)‐4,5‐dehydroleucine hydrazide, and (2S,3R)‐4‐chlorovaline methyl ester. These results also show that the fluoro‐ and dehydroleucine and the chlorovaline are incorporated into a protein by the normal biosynthetic machinery as substitutes for leucine and isoleucine, respectively.     

Ion beam engineered nano silver silicon substrates for surface enhanced Raman spectroscopy

We demonstrate a method for engineering substrates for surface enhanced Raman spectroscopy (SERS) by Ag⁻ ion implantation in Si. The implantation dose and beam current density are chosen such that the Ag concentration in Si exceeds the solid solubility limit, causes aggregation of Ag and nucleates Ag nano particles. The embedded nano particles are then partially exposed by a wet etch process. Our measurements show that the so fabricated nano‐composite substrates are very effective as stable and reproducible SERS substrates. Copyright © 2013 John Wiley & Sons, Ltd.     

Influence of topology in the evolution of coordination in complex networks under information diffusion constraints

In this paper, we study the influence of the topological structure of social systems on the evolution of coordination in them. We simulate a coordination game (“Stag-hunt”) on four well-known classes of complex networks commonly used to model social systems, namely scale-free, small-world, random and hierarchical-modular, as well as on the well-mixed model. Our particular focus is on understanding the impact of information diffusion on coordination, and how this impact varies according to the topology of the social system. We demonstrate that while time-lags and noise in the information about relative payoffs affect the emergence of coordination in all social systems, some topologies are markedly more resilient than others to these effects. We also show that, while non-coordination may be a better strategy in a society where people do not have information about the payoffs of others, coordination will quickly emerge as the better strategy when people get this information about others, even with noise and time lags. Societies with the so-called small-world structure are most conducive to the emergence of coordination, despite limitations in information propagation, while societies with scale-free topologies are most sensitive to noise and time-lags in information diffusion. Surprisingly, in all topologies, it is not the highest connected people (hubs), but the slightly less connected people (provincial hubs) who first adopt coordination. Our findings confirm that the evolution of coordination in social systems depends heavily on the underlying social network structure.     

Modeling networked systems using the topologically distributed bounded rationality framework

In networked systems research, game theory is increasingly used to model a number of scenarios where distributed decision making takes place in a competitive environment. These scenarios include peer‐to‐peer network formation and routing, computer security level allocation, and TCP congestion control. It has been shown, however, that such modeling has met with limited success in capturing the real‐world behavior of computing systems. One of the main reasons for this drawback is that, whereas classical game theory assumes perfect rationality of players, real world entities in such settings have limited information, and cognitive ability which hinders their decision making. Meanwhile, new bounded rationality models have been proposed in networked game theory which take into account the topology of the network. In this article, we demonstrate that game‐theoretic modeling of computing systems would be much more accurate if a topologically distributed bounded rationality model is used. In particular, we consider (a) link formation on peer‐to‐peer overlay networks (b) assigning security levels to computers in computer networks (c) routing in peer‐to‐peer overlay networks, and show that in each of these scenarios, the accuracy of the modeling improves very significantly when topological models of bounded rationality are applied in the modeling process. Our results indicate that it is possible to use game theory to model competitive scenarios in networked systems in a way that closely reflects real world behavior, topology, and dynamics of such systems. © 2016 Wiley Periodicals, Inc. Complexity 21: 123–137, 2016