Identification of organophosphorus simulants for the development of next-generation detection technologies.

Organophosphorus (OP) chemical warfare agents (CWAs) represent an ongoing threat but the understandable widespread prohibition of their use places limitations on the development of technologies to counter the effects of any OP CWA release. Herein, we describe new, accessible methods for the identification of appropriate molecular simulants to mimic the hydrogen bond accepting capacity of the P[double bond, length as m-dash]O moiety, common to every member of this class of CWAs. Using the predictive methodologies developed herein, we have identified OP CWA hydrogen bond acceptor simulants for soman and sarin.

Towards the Prediction of Antimicrobial Efficacy for Hydrogen Bonded, Self-Associating Amphiphiles.

Herein we report 50 structurally related supramolecular self-associating amphiphilic (SSA) salts and related compounds. These SSAs are shown to act as antimicrobial agents, active against model Gram-positive (methicillin-resistant Staphylococcus aureus) and/or Gram-negative (Escherichia coli) bacteria of clinical interest. Through a combination of solution-state, gas-phase, solid-state and in silico measurements, we determine 14 different physicochemical parameters for each of these 50 structurally related compounds.

In silico evolution of diauxic growth.

Background: The glucose effect is a well known phenomenon whereby cells, when presented with two different nutrients, show a diauxic growth pattern, i.e. an episode of exponential growth followed by a lag phase of reduced growth followed by a second phase of exponential growth.

Optimal parameter settings for information processing in gene regulatory networks.

Gene networks can often be interpreted as computational circuits. This article investigates the computational properties of gene regulatory networks defined in terms of the speed and the accuracy of the output of a gene network. It will be shown that there is no single optimal set of parameters, but instead, there is a trade-off between speed and accuracy.

Computational limits to binary genes.

We analyse the trade-off between the speed with which a gene can propagate information, the noise of its output and its metabolic cost. Our main finding is that for any given level of metabolic cost there is an optimal trade-off between noise and processing speed. Any system with a non-vanishing leak expression rate is suboptimal, i.