Functional Sites Induce Long-Range Evolutionary Constraints in Enzymes

Functional residues in proteins tend to be highly conserved over evolutionary time. However, to what extent functional sites impose evolutionary constraints on nearby or even more distant residues is not known. Here, we report pervasive conservation gradients toward catalytic residues in a dataset of 524 distinct enzymes: evolutionary conservation decreases approximately linearly with increasing distance to the nearest catalytic residue in the protein structure. This trend encompasses, on average, 80% of the residues in any enzyme, and it is independent of known structural constraints on protein evolution such as residue packing or solvent accessibility. Further, the trend exists in both monomeric and multimeric enzymes and irrespective of enzyme size and/or location of the active site in the enzyme structure. By contrast, sites in protein–protein interfaces, unlike catalytic residues, are only weakly conserved and induce only minor rate gradients. In aggregate, these observations show that functional sites, and in particular catalytic residues, induce long-range evolutionary constraints in enzymes.Fil: Jack, Benjamin R.. University of Texas at Austin; Estados UnidosFil: Meyer, Austin G.. University of Texas at Austin; Estados UnidosFil: Echave, Julián. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Wilke, Claus O.. University of Texas at Austin; Estados Unido

Analyzing Machupo virus-receptor binding by molecular dynamics simulations

In many biological applications, we would like to be able to computationally predict mutational effects on affinity in protein-protein interactions. However, many commonly used methods to predict these effects perform poorly in important test cases. In particular, the effects of multiple mutations, non-alanine substitutions, and flexible loops are difficult to predict with available tools and protocols. We present here an existing method applied in a novel way to a new test case; we interrogate affinity differences resulting from mutations in a host-virus protein-protein interface. We use steered molecular dynamics (SMD) to computationally pull the machupo virus (MACV) spike glycoprotein (GP1) away from the human transferrin receptor (hTfR1). We then approximate affinity using the maximum applied force of separation and the area under the force-versus-distance curve. We find, even without the rigor and planning required for free energy calculations, that these quantities can provide novel biophysical insight into the GP1/hTfR1 interaction. First, with no prior knowledge of the system we can differentiate among wild type and mutant complexes. Moreover, we show that this simple SMD scheme correlates well with relative free energy differences computed via free energy perturbation. Second, although the static co-crystal structure shows two large hydrogen-bonding networks in the GP1/hTfR1 interface, our simulations indicate that one of them may not be important for tight binding. Third, one viral site known to be critical for infection may mark an important evolutionary suppressor site for infection-resistant hTfR1 mutants. Finally, our approach provides a framework to compare the effects of multiple mutations, individually and jointly, on protein-protein interactions.Comment: 33 pages, 8 figures, 5 table

Identifying Structural Variation in Haploid Microbial Genomes from Short-Read Resequencing Data Using Breseq

Mutations that alter chromosomal structure play critical roles in evolution and disease, including in the origin of new lifestyles and pathogenic traits in microbes. Large-scale rearrangements in genomes are often mediated by recombination events involving new or existing copies of mobile genetic elements, recently duplicated genes, or other repetitive sequences. Most current software programs for predicting structural variation from short-read DNA resequencing data are intended primarily for use on human genomes. They typically disregard information in reads mapping to repeat sequences, and significant post-processing and manual examination of their output is often required to rule out false-positive predictions and precisely describe mutational events. Results: We have implemented an algorithm for identifying structural variation from DNA resequencing data as part of the breseq computational pipeline for predicting mutations in haploid microbial genomes. Our method evaluates the support for new sequence junctions present in a clonal sample from split-read alignments to a reference genome, including matches to repeat sequences. Then, it uses a statistical model of read coverage evenness to accept or reject these predictions. Finally, breseq combines predictions of new junctions and deleted chromosomal regions to output biologically relevant descriptions of mutations and their effects on genes. We demonstrate the performance of breseq on simulated Escherichia coli genomes with deletions generating unique breakpoint sequences, new insertions of mobile genetic elements, and deletions mediated by mobile elements. Then, we reanalyze data from an E. coli K-12 mutation accumulation evolution experiment in which structural variation was not previously identified. Transposon insertions and large-scale chromosomal changes detected by breseq account for similar to 25% of spontaneous mutations in this strain. In all cases, we find that breseq is able to reliably predict structural variation with modest read-depth coverage of the reference genome (>40-fold). Conclusions: Using breseq to predict structural variation should be useful for studies of microbial epidemiology, experimental evolution, synthetic biology, and genetics when a reference genome for a closely related strain is available. In these cases, breseq can discover mutations that may be responsible for important or unintended changes in genomes that might otherwise go undetected.U.S. National Institutes of Health R00-GM087550U.S. National Science Foundation (NSF) DEB-0515729NSF BEACON Center for the Study of Evolution in Action DBI-0939454Cancer Prevention & Research Institute of Texas (CPRIT) RP130124University of Texas at Austin startup fundsUniversity of Texas at AustinCPRIT Cancer Research TraineeshipMolecular Bioscience

Solubility of nickel in slags equilibrated with Ni-S melt

To provide thermodynamic data for converting the nickel matte to liquid nickel, an experimental study was conducted in the phase equilibrium between the Ni-S melt and FeOX-SiO2, FeOX-CaO or CaO-Al2O3 based slag melted in a magnesia crucible at 1773 and 1873 K. pSO2 was controlled at 10.1 kPa while pO2 and pS2 ranged between those where NiO precipitated and Ni3S2 formed, respectively. The nickel content in the slag and the sulfur content in the metal at given pO2 and pS2 were smallest for the CaO-Al2O3 based slag. Both decreased with increasing temperature. At 1873 K, the content of nickel in the CaO-Al2O3 based slag at pO2 of 10 Pa (near the precipitation of NiO) was 4%, while the content of sulfur in alloy is 0.4 mass %. Thus, the CaO-Al2O3 base slag at 1873 K would be suitable for direct converting of Ni3S2 to metallic nickel. The distribution behavior of nickel between the slag and the Ni-S melt was discussed based on the concept of oxidic and sulfidic dissolution

My Road Ahead study protocol: a randomised controlled trial of an online psychological intervention for men following treatment for localised prostate cancer

BACKGROUND There is a need for psychosocial interventions for men with prostate cancer to promote adaptive coping with the challenges and distress associated with diagnosis, treatment and recovery. In addition, interventions are needed that help to overcome barriers to psychosocial treatment such as limited face-to-face psychosocial support services, a shortage of adequately trained professionals, geographical distance, perceived and personal stigma and a preference for consumer-centric and self-directed learning. My Road Ahead is an online cognitive behaviour therapy (CBT) intervention for prostate cancer. This protocol describes a randomised controlled trial (RCT) that will evaluate the efficacy of this online intervention alone, the intervention in combination with a moderated online forum, and the moderated online forum alone. METHODS/DESIGN This study utilises a RCT design with three groups receiving: 1) the 6-module My Road Ahead intervention alone; 2) the My Road Ahead intervention plus a moderated online forum; and 3) the moderated online forum alone. It is expected that 150 men with localised prostate cancer will be recruited into the RCT. Online measures will assess men's psychological distress as well as sexual and relationship adjustment at baseline, post-intervention, 3 month follow-up and 6 month follow-up. The study is being conducted in Australia and participants will be recruited from April 2012 to Feb 2014. The primary aim of this study is to evaluate the efficacy of My Road Ahead in reducing psychological distress. DISCUSSION To our knowledge, My Road Ahead is the first self-directed online psychological intervention developed for men who have been treated for localised prostate cancer. The RCT will assess the efficacy of this intervention in improving psychological well-being, sexual satisfaction, relationship satisfaction and overall quality of life. If successful, this intervention could provide much needed support to men receiving treatment for localised prostate cancer in a highly accessible manner. TRIAL REGISTRATION Australian New Zealand Clinical Trials Registry Identifier: ACTRN12611000278932.The authors would like to acknowledge the funding partners involved in this study; the Prostate Cancer Foundation of Australia (PCFA), beyondblue: the National Depression and Anxiety Initiative with funding support from Movember Foundation

White Matter Deterioration May Foreshadow Impairment of Emotional Valence Determination in Early-Stage Dementia of the Alzheimer Type

In Alzheimer Disease (AD), non-verbal skills often remain intact for far longer than verbally mediated processes. Four (1 female, 3 males) participants with early-stage Clinically Diagnosed Dementia of the Alzheimer Type (CDDAT) and eight neurotypicals (NTs; 4 females, 4 males) completed the emotional valence determination test (EVDT) while undergoing BOLD functional magnetic resonance imaging (fMRI). We expected CDDAT participants to perform just as well as NTs on the EVDT, and to display increased activity within the bilateral amygdala and right anterior cingulate cortex (r-ACC). We hypothesized that such activity would reflect an increased reliance on these structures to compensate for on-going neuronal loss in frontoparietal regions due to the disease. We used diffusion tensor imaging (DTI) to determine if white matter (WM) damage had occurred in frontoparietal regions as well. CDDAT participants had similar behavioral performance and no differences were observed in brain activity or connectivity patterns within the amygdalae or r-ACC. Decreased fractional anisotropy (FA) values were noted, however, for the bilateral superior longitudinal fasciculi and posterior cingulate cortex (PCC). We interpret these findings to suggest that emotional valence determination and non-verbal skill sets are largely intact at this stage of the disease, but signs foreshadowing future decline were revealed by possible WM deterioration. Understanding how non-verbal skill sets are altered, while remaining largely intact, offers new insights into how non-verbal communication may be more successfully implemented in the care of AD patients and highlights the potential role of DTI as a presymptomatic biomarker

Automated Potentiometric Titrations in KCl/Water-Saturated Octanol: Method for Quantifying Factors Influencing Ion-Pair Partitioning

The knowledge base of factors influencing ion pair partitioning is very sparse, primarily because of the difficulty in determining accurate log PI values of desirable low molecular weight (MW) reference compounds. We have developed a potentiometric titration procedure in KCl/water-saturated octanol that provides a link to log PI through the thermodynamic cycle of ionization and partitioning. These titrations have the advantage of being independent of the magnitude of log P, while maintaining a reproducibility of a few hundredths of a log P in the calculated difference between log P neutral and log P ion pair (diff (log PN − I)). Simple model compounds can be used. The titration procedure is described in detail, along with a program for calculating pKa′′ values incorporating the ionization of water in octanol. Hydrogen bonding and steric factors have a greater influence on ion pairs than they do on neutral species, yet these factors are missing from current programs used to calculate log PI and log D. In contrast to the common assumption that diff (log PN − I) is the same for all amines, they can actually vary more than 3 log units, as in our examples. A major factor affecting log PI is the ability of water and the counterion to approach the charge center. Bulky substituents near the charge center have a negative influence on log PI. On the other hand, hydrogen bonding groups near the charge center have the opposite effect by lowering the free energy of the ion pair. The use of this titration method to determine substituent ion pair stabilization values (IPS) should bring about more accurate log D calculations and encourage species-specific QSAR involving log DN and log DI. This work also brings attention to the fascinating world of nature’s highly stabilized ion pairs

Maximum Allowed Solvent Accessibilites of Residues in Proteins

Matthew Z. Tien, Department of Biochemistry and Molecular Biology, The University of Chicago, Chicago, Illinois, United States of AmericaAustin G. Meyer, School of Medicine, Texas Tech University Health Sciences Center, Lubbock, Texas, United States of AmericaAustin G. Meyer, Dariya K. Sydykova, Stephanie J. Spielman, Claus O. Wilke, Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of AmericaDariya K. Sydykova, Stephanie J. Spielman, Claus O. Wilke, Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, United States of AmericaDariya K. Sydykova, Stephanie J. Spielman, Claus O. Wilke, Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of AmericaThe relative solvent accessibility (RSA) of a residue in a protein measures the extent of burial or exposure of that residue in the 3D structure. RSA is frequently used to describe a protein's biophysical or evolutionary properties. To calculate RSA, a residue's solvent accessibility (ASA) needs to be normalized by a suitable reference value for the given amino acid; several normalization scales have previously been proposed. However, these scales do not provide tight upper bounds on ASA values frequently observed in empirical crystal structures. Instead, they underestimate the largest allowed ASA values, by up to 20%. As a result, many empirical crystal structures contain residues that seem to have RSA values in excess of one. Here, we derive a new normalization scale that does provide a tight upper bound on observed ASA values. We pursue two complementary strategies, one based on extensive analysis of empirical structures and one based on systematic enumeration of biophysically allowed tripeptides. Both approaches yield congruent results that consistently exceed published values. We conclude that previously published ASA normalization values were too small, primarily because the conformations that maximize ASA had not been correctly identified. As an application of our results, we show that empirically derived hydrophobicity scales are sensitive to accurate RSA calculation, and we derive new hydrophobicity scales that show increased correlation with experimentally measured scales.This work was supported by National Institutes of Health (http://nih.gov/) grant R01 GM088344 to COW. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Center for Computational Biology and BioinformaticsIntegrative BiologyEmail: [email protected]