H2r: Identification of evolutionary important residues by means of an entropy based analysis of multiple sequence alignments

BACKGROUND: A multiple sequence alignment (MSA) generated for a protein can be used to characterise residues by means of a statistical analysis of single columns. In addition to the examination of individual positions, the investigation of co-variation of amino acid frequencies offers insights into function and evolution of the protein and residues. RESULTS: We introduce conn(k), a novel parameter for the characterisation of individual residues. For each residue k, conn(k) is the number of most extreme signals of co-evolution. These signals were deduced from a normalised mutual information (MI) value U(k, l) computed for all pairs of residues k, l. We demonstrate that conn(k) is a more robust indicator than an individual MI-value for the prediction of residues most plausibly important for the evolution of a protein. This proposition was inferred by means of statistical methods. It was further confirmed by the analysis of several proteins. A server, which computes conn(k)-values is available at http://www-bioinf.uni-regensburg.de. CONCLUSION: The algorithms H2r, which analyses MSAs and computes conn(k)-values, characterises a specific class of residues. In contrast to strictly conserved ones, these residues possess some flexibility in the composition of side chains. However, their allocation is sensibly balanced with several other positions, as indicated by conn(k)

Integrated Analysis of Residue Coevolution and Protein Structure in ABC Transporters

Intraprotein side chain contacts can couple the evolutionary process of amino acid substitution at one position to that at another. This coupling, known as residue coevolution, may vary in strength. Conserved contacts thus not only define 3-dimensional protein structure, but also indicate which residue-residue interactions are crucial to a protein’s function. Therefore, prediction of strongly coevolving residue-pairs helps clarify molecular mechanisms underlying function. Previously, various coevolution detectors have been employed separately to predict these pairs purely from multiple sequence alignments, while disregarding available structural information. This study introduces an integrative framework that improves the accuracy of such predictions, relative to previous approaches, by combining multiple coevolution detectors and incorporating structural contact information. This framework is applied to the ABC-B and ABC-C transporter families, which include the drug exporter P-glycoprotein involved in multidrug resistance of cancer cells, as well as the CFTR chloride channel linked to cystic fibrosis disease. The predicted coevolving pairs are further analyzed based on conformational changes inferred from outward- and inward-facing transporter structures. The analysis suggests that some pairs coevolved to directly regulate conformational changes of the alternating-access transport mechanism, while others to stabilize rigid-body-like components of the protein structure. Moreover, some identified pairs correspond to residues previously implicated in cystic fibrosis

Review of Coronal Oscillations - An Observer's View

Recent observations show a variety of oscillation modes in the corona. Early non-imaging observations in radio wavelengths showed a number of fast-period oscillations in the order of seconds, which have been interpreted as fast sausage mode oscillations. TRACE observations from 1998 have for the first time revealed the lateral displacements of fast kink mode oscillations, with periods of ~3-5 minutes, apparently triggered by nearby flares and destabilizing filaments. Recently, SUMER discovered with Doppler shift measurements loop oscillations with longer periods (10-30 minutes) and relatively short damping times in hot (7 MK) loops, which seem to correspond to longitudinal slow magnetoacoustic waves. In addition, propagating longitudinal waves have also been detected with EIT and TRACE in the lowest density scale height of loops near sunspots. All these new observations seem to confirm the theoretically predicted oscillation modes and can now be used as a powerful tool for ``coronal seismology'' diagnostic.Comment: 5 Figure

Computing Highly Correlated Positions Using Mutual Information and Graph Theory for G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are a superfamily of seven transmembrane-spanning proteins involved in a wide array of physiological functions and are the most common targets of pharmaceuticals. This study aims to identify a cohort or clique of positions that share high mutual information. Using a multiple sequence alignment of the transmembrane (TM) domains, we calculated the mutual information between all inter-TM pairs of aligned positions and ranked the pairs by mutual information. A mutual information graph was constructed with vertices that corresponded to TM positions and edges between vertices were drawn if the mutual information exceeded a threshold of statistical significance. Positions with high degree (i.e. had significant mutual information with a large number of other positions) were found to line a well defined inter-TM ligand binding cavity for class A as well as class C GPCRs. Although the natural ligands of class C receptors bind to their extracellular N-terminal domains, the possibility of modulating their activity through ligands that bind to their helical bundle has been reported. Such positions were not found for class B GPCRs, in agreement with the observation that there are not known ligands that bind within their TM helical bundle. All identified key positions formed a clique within the MI graph of interest. For a subset of class A receptors we also considered the alignment of a portion of the second extracellular loop, and found that the two positions adjacent to the conserved Cys that bridges the loop with the TM3 qualified as key positions. Our algorithm may be useful for localizing topologically conserved regions in other protein families

Visual Predators Select for Crypticity and Polymorphism in Virtual Prey

Cryptically colored animals commonly occur in several distinct pattern variants. Such phenotypic diversity may be promoted by frequency-dependent predation, in which more abundant variants are attacked disproportionately often, but the hypothesis has never been explicitly tested. Here we report the first controlled experiment on the effects of visual predators on prey crypticity and phenotypic variance, in which blue jays (Cyanocitta cristata) searched for digital moths on computer monitors. Moth phenotypes evolved via a genetic algorithm in which individuals detected by the jays were much less likely to reproduce. Jays often failed to detect atypical cryptic moths, confirming frequency- dependent selection and suggesting the use of searching images, which enhance the detection of common prey. Over successive generations, the moths evolved to become significantly harder to detect, and they showed significantly greater phenotypic variance than non-selected or frequency-independent selected controls