The concept of strong and weak virtual reality

We approach the virtual reality phenomenon by studying its relationship to set theory, and we investigate the case where this is done using the wellfoundedness property of sets. Our hypothesis is that non-wellfounded sets (hypersets) give rise to a different quality of virtual reality than do familiar wellfounded sets. We initially provide an alternative approach to virtual reality based on Sommerhoff's idea of first and second order self-awareness; both categories of self-awareness are considered as necessary conditions for consciousness in terms of higher cognitive functions. We then introduce a representation of first and second order self-awareness through sets, and assume that these sets, which we call events, originally form a collection of wellfounded sets. Strong virtual reality characterizes virtual reality environments which have the limited capacity to create only events associated with wellfounded sets. In contrast, the more general concept of weak virtual reality characterizes collections of virtual reality mediated events altogether forming an entirety larger than any collection of wellfounded sets. By giving reference to Aczel's hyperset theory we indicate that this definition is not empty, because hypersets encompass wellfounded sets already. Moreover, we argue that weak virtual reality could be realized in human history through continued progress in computer technology. Finally, we reformulate our characterization into a more general framework, and use Baltag's Structural Theory of Sets (STS) to show that within this general hyperset theory Sommerhoff's first and second order self-awareness as well as both concepts of virtual reality admit a consistent mathematical representation.Comment: 17 pages; several edits in v

Rapid detection of similarity in protein structure and function through contact metric distances

The characterization of biological function among newly determined protein structures is a central challenge in structural genomics. One class of computational solutions to this problem is based on the similarity of protein structure. Here, we implement a simple yet efficient measure of protein structure similarity, the contact metric. Even though its computation avoids structural alignments and is therefore nearly instantaneous, we find that small values correlate with geometrical root mean square deviations obtained from structural alignments. To test whether the contact metric detects functional similarity, as defined by Gene Ontology (GO) terms, it was compared in large-scale computational experiments to four other measures of structural similarity, including alignment algorithms as well as alignment independent approaches. The contact metric was the fastest method and its sensitivity, at any given specificity level, was a close second only to Fast Alignment and Search Tool—a structural alignment method that is slower by three orders of magnitude. Critically, nearly 40% of correct functional inferences by the contact metric were not identified by any other approach, which shows that the contact metric is complementary and computationally efficient in detecting functional relationships between proteins. A public ‘Contact Metric Internet Server’ is provided

Random Amino Acid Mutations and Protein Misfolding Lead to Shannon Limit in Sequence-Structure Communication

The transmission of genomic information from coding sequence to protein structure during protein synthesis is subject to stochastic errors. To analyze transmission limits in the presence of spurious errors, Shannon's noisy channel theorem is applied to a communication channel between amino acid sequences and their structures established from a large-scale statistical analysis of protein atomic coordinates. While Shannon's theorem confirms that in close to native conformations information is transmitted with limited error probability, additional random errors in sequence (amino acid substitutions) and in structure (structural defects) trigger a decrease in communication capacity toward a Shannon limit at 0.010 bits per amino acid symbol at which communication breaks down. In several controls, simulated error rates above a critical threshold and models of unfolded structures always produce capacities below this limiting value. Thus an essential biological system can be realistically modeled as a digital communication channel that is (a) sensitive to random errors and (b) restricted by a Shannon error limit. This forms a novel basis for predictions consistent with observed rates of defective ribosomal products during protein synthesis, and with the estimated excess of mutual information in protein contact potentials

Accurate Protein Structure Annotation through Competitive Diffusion of Enzymatic Functions over a Network of Local Evolutionary Similarities

High-throughput Structural Genomics yields many new protein structures without known molecular function. This study aims to uncover these missing annotations by globally comparing select functional residues across the structural proteome. First, Evolutionary Trace Annotation, or ETA, identifies which proteins have local evolutionary and structural features in common; next, these proteins are linked together into a proteomic network of ETA similarities; then, starting from proteins with known functions, competing functional labels diffuse link-by-link over the entire network. Every node is thus assigned a likelihood z-score for every function, and the most significant one at each node wins and defines its annotation. In high-throughput controls, this competitive diffusion process recovered enzyme activity annotations with 99% and 97% accuracy at half-coverage for the third and fourth Enzyme Commission (EC) levels, respectively. This corresponds to false positive rates 4-fold lower than nearest-neighbor and 5-fold lower than sequence-based annotations. In practice, experimental validation of the predicted carboxylesterase activity in a protein from Staphylococcus aureus illustrated the effectiveness of this approach in the context of an increasingly drug-resistant microbe. This study further links molecular function to a small number of evolutionarily important residues recognizable by Evolutionary Tracing and it points to the specificity and sensitivity of functional annotation by competitive global network diffusion. A web server is at http://mammoth.bcm.tmc.edu/networks

Can the Internet cope with stress?

When will the Internet wake up and become aware of itself? In this note the problem is approached by asking an alternative question: Can the Internet cope with stress? By extrapolating the psychological difference between coping and defense mechanisms, a distributed software experiment is outlined which could reject the hypothesis that the Internet is not a conscious entity

Global risk minimization in financial markets

Recurring international financial crises have adverse socioeconomic effects and demand novel regulatory instruments or strategies for risk management and market stabilization. However, the complex web of market interactions often impedes rational decisions that would absolutely minimize the risk. Here we show that, for any given expected return, investors can overcome this complexity and globally minimize their financial risk in portfolio selection models, which is mathematically equivalent to computing the ground state of spin glass models in physics, provided the margin requirement remains below a critical, empirically measurable value. For markets with centrally regulated margin requirements, this result suggests a potentially stabilizing intervention strategy.

Plasmodium spp. membrane glutathione S-transferases: detoxification units and drug targets

Membrane glutathione S-transferases from the class of membrane-associated proteins in eicosanoid and glutathione metabolism (MAPEG) form a superfamily of detoxification enzymes that catalyze the conjugation of reduced glutathione (GSH) to a broad spectrum of xenobiotics and hydrophobic electrophiles. Evolutionarily unrelated to the cytosolic glutathione S-transferases, they are found across bacterial and eukaryotic domains, for example in mammals, plants, fungi and bacteria in which significant levels of glutathione are maintained. Species of genus Plasmodium, the unicellular protozoa that are commonly known as malaria parasites, do actively support glutathione homeostasis and maintain its metabolism throughout their complex parasitic life cycle. In humans and in other mammals, the asexual intraerythrocytic stage of malaria, when the parasite feeds on hemoglobin, grows and eventually asexually replicates inside infected red blood cells (RBCs), is directly associated with host disease symptoms and during this critical stage GSH protects the host RBC and the parasite against oxidative stress from parasite-induced hemoglobin catabolism. In line with these observations, several GSH-dependent Plasmodium enzymes have been characterized including glutathione reductases, thioredoxins, glyoxalases, glutaredoxins and glutathione S-transferases (GSTs); furthermore, GSH itself have been found to associate spontaneously and to degrade free heme and its hydroxide, hematin, which are the main cytotoxic byproducts of hemoglobin catabolism. However, despite the apparent importance of glutathione metabolism for the parasite, no membrane associated glutathione S-transferases of genus Plasmodium have been previously described. We recently reported the first examples of MAPEG members among Plasmodium spp