101 research outputs found
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Evaluating the effects of turf-replacement programs in Los Angeles
Water utilities incentivize turf replacement to promote water conservation, but the effects of such programs have received limited evaluations. In 2014, the Metropolitan Water District of Southern California (MWD) undertook an unprecedented investment to incentive turf replacement throughout Southern California in response to a serious Statewide drought. MWD devoted $350 million to the program, resulting in more than 46,000 rebate payments (25,000 in Los Angeles County) to remove 15.3 million square meters of turf. The program implementation provided a unique opportunity to address research gaps on turf replacement implementation. We analyzed socioeconomic and spatial trends of program participants and assessed landscape changes from turf replacement using a random sample of properties (4% of LA County participants in 2014–16). Specifically, we used a novel and cost-effective approach Google Earth Street View to characterize landscapes in front yards and created a typology of land cover types. Results showed: post-replacement landscapes had a diversity of land cover types – diverse yards with several land cover types, as well as more homogenous yards with a single land cover such as woodchips, bare soil, gravel, and artificial turf. Analysis also indicated some evidence of “neighborhood adoption” effects. We describe the need for longitudinal studies to understand long-term effects of turf replacement and associated water use, and suggest that water utilities should also evaluate results in backyards, which requires site visits. This study provides a novel contribution that can be replicated over space and time to further knowledge of turf replacement program implementations and evaluation
Multidimensional replica-exchange method for free-energy calculations
We have developed a new simulation algorithm for free-energy calculations.
The method is a multidimensional extension of the replica-exchange method.
While pairs of replicas with different temperatures are exchanged during the
simulation in the original replica-exchange method, pairs of replicas with
different temperatures and/or different parameters of the potential energy are
exchanged in the new algorithm. This greatly enhances the sampling of the
conformational space and allows accurate calculations of free energy in a wide
temperature range from a single simulation run, using the weighted histogram
analysis method.Comment: 13 pages, (ReVTeX), 9 figures. J. Chem. Phys. 113 (2000), in pres
Highly Charged Ion Production Using an Electrode in Biased and Floating Modes
One of the most popular ways to obtain higher beam intensities in ECR ion sources is to install an electrode (usually disc) into the plasma chamber. Examined this method in detail we found that majority of the groups observed the beam intensity improvement by supplying a suitable biased voltage to the electrode and an electron current was injected into the plasma. A few groups observed the enhancement, however, when the electrode operated at floating potential - without being an electron donor. Only a few (and sometimes contradictionary) information was found on the optimised properties of the electrodes, i.e. position, dimension, shape, material. In spite of the great success of the "biased-disc" method, the mechanism is still not completely clear. In this contribution, as one step of understanding, we examine what condition we observed the above mentioned two modes. The experiments were performed at the 18 GHz RIKEN and at the 14.5 GHz ATOMKI ECR ion sources. It was found that effect of the electrode is strongly depends on the local plasma parameters and on the position of the electrode. At certain mirror ratios and electrode positions we needed to negatively bias the electrode and inject electrons into the plasma. The electrode operated as an electron source (Electron Donor ED mode). At higher mirror ratios and other axial positions the electrode works by directly changing the plasma potential dip (Potential Tuner PT mode). These two modes were checked and successfully found both in continuos and in pulsed mode operation. In both (ED and PT) modes we generated higher highly charged ion currents in the RIKEN-ECRIS than without the electrode
Amino acid "little Big Bang": Representing amino acid substitution matrices as dot products of Euclidian vectors
<p>Abstract</p> <p>Background</p> <p>Sequence comparisons make use of a one-letter representation for amino acids, the necessary quantitative information being supplied by the substitution matrices. This paper deals with the problem of finding a representation that provides a comprehensive description of amino acid intrinsic properties consistent with the substitution matrices.</p> <p>Results</p> <p>We present a Euclidian vector representation of the amino acids, obtained by the singular value decomposition of the substitution matrices. The substitution matrix entries correspond to the dot product of amino acid vectors. We apply this vector encoding to the study of the relative importance of various amino acid physicochemical properties upon the substitution matrices. We also characterize and compare the PAM and BLOSUM series substitution matrices.</p> <p>Conclusions</p> <p>This vector encoding introduces a Euclidian metric in the amino acid space, consistent with substitution matrices. Such a numerical description of the amino acid is useful when intrinsic properties of amino acids are necessary, for instance, building sequence profiles or finding consensus sequences, using machine learning algorithms such as Support Vector Machine and Neural Networks algorithms.</p
Prediction of binding hot spot residues by using structural and evolutionary parameters
In this work, we present a method for predicting hot spot residues by using a set of structural and evolutionary parameters. Unlike previous studies, we use a set of parameters which do not depend on the structure of the protein in complex, so that the predictor can also be used when the interface region is unknown. Despite the fact that no information concerning proteins in complex is used for prediction, the application of the method to a compiled dataset described in the literature achieved a performance of 60.4%, as measured by F-Measure, corresponding to a recall of 78.1% and a precision of 49.5%. This result is higher than those reported by previous studies using the same data set
Minimum Free Energy Path of Ligand-Induced Transition in Adenylate Kinase
Large-scale conformational changes in proteins involve barrier-crossing transitions on the complex free energy surfaces of high-dimensional space. Such rare events cannot be efficiently captured by conventional molecular dynamics simulations. Here we show that, by combining the on-the-fly string method and the multi-state Bennett acceptance ratio (MBAR) method, the free energy profile of a conformational transition pathway in Escherichia coli adenylate kinase can be characterized in a high-dimensional space. The minimum free energy paths of the conformational transitions in adenylate kinase were explored by the on-the-fly string method in 20-dimensional space spanned by the 20 largest-amplitude principal modes, and the free energy and various kinds of average physical quantities along the pathways were successfully evaluated by the MBAR method. The influence of ligand binding on the pathways was characterized in terms of rigid-body motions of the lid-shaped ATP-binding domain (LID) and the AMP-binding (AMPbd) domains. It was found that the LID domain was able to partially close without the ligand, while the closure of the AMPbd domain required the ligand binding. The transition state ensemble of the ligand bound form was identified as those structures characterized by highly specific binding of the ligand to the AMPbd domain, and was validated by unrestrained MD simulations. It was also found that complete closure of the LID domain required the dehydration of solvents around the P-loop. These findings suggest that the interplay of the two different types of domain motion is an essential feature in the conformational transition of the enzyme
Nature of protein family signatures: Insights from singular value analysis of position-specific scoring matrices
Position-specific scoring matrices (PSSMs) are useful for detecting weak
homology in protein sequence analysis, and they are thought to contain some
essential signatures of the protein families. In order to elucidate what kind
of ingredients constitute such family-specific signatures, we apply singular
value decomposition to a set of PSSMs and examine the properties of dominant
right and left singular vectors. The first right singular vectors were
correlated with various amino acid indices including relative mutability, amino
acid composition in protein interior, hydropathy, or turn propensity, depending
on proteins. A significant correlation between the first left singular vector
and a measure of site conservation was observed. It is shown that the
contribution of the first singular component to the PSSMs act to disfavor
potentially but falsely functionally important residues at conserved sites. The
second right singular vectors were highly correlated with hydrophobicity
scales, and the corresponding left singular vectors with contact numbers of
protein structures. It is suggested that sequence alignment with a PSSM is
essentially equivalent to threading supplemented with functional information.
The presented method may be used to separate functionally important sites from
structurally important ones, and thus it may be a useful tool for predicting
protein functions.Comment: 22 pages, 7 figures, 4 table
Enhanced and effective conformational sampling of protein molecular systems for their free energy landscapes
Protein folding and protein–ligand docking have long persisted as important subjects in biophysics. Using multicanonical molecular dynamics (McMD) simulations with realistic expressions, i.e., all-atom protein models and an explicit solvent, free-energy landscapes have been computed for several systems, such as the folding of peptides/proteins composed of a few amino acids up to nearly 60 amino-acid residues, protein–ligand interactions, and coupled folding and binding of intrinsically disordered proteins. Recent progress in conformational sampling and its applications to biophysical systems are reviewed in this report, including descriptions of several outstanding studies. In addition, an algorithm and detailed procedures used for multicanonical sampling are presented along with the methodology of adaptive umbrella sampling. Both methods control the simulation so that low-probability regions along a reaction coordinate are sampled frequently. The reaction coordinate is the potential energy for multicanonical sampling and is a structural identifier for adaptive umbrella sampling. One might imagine that this probability control invariably enhances conformational transitions among distinct stable states, but this study examines the enhanced conformational sampling of a simple system and shows that reasonably well-controlled sampling slows the transitions. This slowing is induced by a rapid change of entropy along the reaction coordinate. We then provide a recipe to speed up the sampling by loosening the rapid change of entropy. Finally, we report all-atom McMD simulation results of various biophysical systems in an explicit solvent
SNOSite: Exploiting Maximal Dependence Decomposition to Identify Cysteine S-Nitrosylation with Substrate Site Specificity
S-nitrosylation, the covalent attachment of a nitric oxide to (NO) the sulfur atom of cysteine, is a selective and reversible protein post-translational modification (PTM) that regulates protein activity, localization, and stability. Despite its implication in the regulation of protein functions and cell signaling, the substrate specificity of cysteine S-nitrosylation remains unknown. Based on a total of 586 experimentally identified S-nitrosylation sites from SNAP/L-cysteine-stimulated mouse endothelial cells, this work presents an informatics investigation on S-nitrosylation sites including structural factors such as the flanking amino acids composition, the accessible surface area (ASA) and physicochemical properties, i.e. positive charge and side chain interaction parameter. Due to the difficulty to obtain the conserved motifs by conventional motif analysis, maximal dependence decomposition (MDD) has been applied to obtain statistically significant conserved motifs. Support vector machine (SVM) is applied to generate predictive model for each MDD-clustered motif. According to five-fold cross-validation, the MDD-clustered SVMs could achieve an accuracy of 0.902, and provides a promising performance in an independent test set. The effectiveness of the model was demonstrated on the correct identification of previously reported S-nitrosylation sites of Bos taurus dimethylarginine dimethylaminohydrolase 1 (DDAH1) and human hemoglobin subunit beta (HBB). Finally, the MDD-clustered model was adopted to construct an effective web-based tool, named SNOSite (http://csb.cse.yzu.edu.tw/SNOSite/), for identifying S-nitrosylation sites on the uncharacterized protein sequences
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