DNABINDPROT: fluctuation-based predictor of DNA-binding residues within a network of interacting residues

DNABINDPROT is designed to predict DNA-binding residues, based on the fluctuations of residues in high-frequency modes by the Gaussian network model. The residue pairs that display high mean-square distance fluctuations are analyzed with respect to DNA binding, which are then filtered with their evolutionary conservation profiles and ranked according to their DNA-binding propensities. If the analyses are based on the exact outcome of fluctuations in the highest mode, using a conservation threshold of 5, the results have a sensitivity, specificity, precision and accuracy of 9.3%, 90.5%, 18.1% and 78.6%, respectively, on a dataset of 36 unbound–bound protein structure pairs. These values increase up to 24.3%, 93.4%, 45.3% and 83.3% for the respective cases, when the neighboring two residues are considered. The relatively low sensitivity appears with the identified residues being selective and susceptible more for the binding core residues rather than all DNA-binding residues. The predicted residues that are not tagged as DNA-binding residues are those whose fluctuations are coupled with DNA-binding sites. They are in close proximity as well as plausible for other functional residues, such as ligand and protein–protein interaction sites. DNABINDPROT is free and open to all users without login requirement available at: http://www.prc.boun.edu.tr/appserv/prc/dnabindprot/

Community-Wide Assessment of Protein-Interface Modeling Suggests Improvements to Design Methodology

The CAPRI and CASP prediction experiments have demonstrated the power of community wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting there may be important physical chemistry missing in the energy calculations. 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the non-polar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were on average structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a non-binder

Integer Programming Based Heterogeneous CPU-GPU Cluster Scheduler for SLURM Resource Manager

We present an integer programming based heterogeneous CPU-GPU cluster scheduler for the widely used SLURM resource manager. Our scheduler algorithm takes windows of jobs and solves an allocation problem in which free CPU cores and GPU cards are allocated collectively to jobs so as to maximize some objective function. We perform realistic SLURM emulation tests using the Effective System Performance (ESP) workloads. The test results show that our scheduler produces better resource utilization and shorter average job waiting times. The SLURM scheduler plug-in that implements our algorithm is available at http://code.google.com/p/slurm-ipsched/

Generating Multibillion Element Unstructured Meshes on Distributed Memory Parallel Machines

We present a parallel mesh generator called PMSH that is developed as a wrapper code around the open source sequential Netgen mesh generator. Parallelization of the mesh generator is carried out in five stages: (i) generation of a coarse volume mesh; (ii) partitioning of the coarse mesh; (iii) refinement of coarse surface mesh to produce fine surface submeshes; (iv) remeshing of each fine surface submesh to get a final fine mesh; (v) matching of partition boundary vertices followed by global vertex numbering. A new integer based barycentric coordinate method is developed for matching distributed partition boundary vertices. This method does not have precision related problems of floating point coordinate based vertex matching. Test results obtained on an SGI Altix ICE X system with 8192 cores confirm that our approach does indeed enable us to generate multibillion element meshes in a scalable way

Effects of Digital Stories on the Development of EFL Learners’ Listening Skill

The purpose of this research was to investigate the effects of digital storytelling on listening skills of language learners and their attitudes towards the use of digital storytelling. 64 secondary school students whose degrees were 6th and 7th grade participated in the study. The study was conducted in Adana, Turkey during the fall semester of the academic year 2020-2021. Quasi-experimental design with pretest-posttest control group was employed for the research. Listening comprehension achievement test and learners’ attitude scale were the data collection tools of the research. The results of the study revealed that participants had statistically significant differences in their listening skills improvement and test group had higher competency in listening activities compared to the control group. The findings also provided additional information about learners’ attitudes towards digital storytelling listening activities, including their motivation level and thoughts. Students’ attitudes towards digital storytelling were positive and their motivation was significantly higher

Kırşehir il sınırları içerisinde Rüzgâr Enerjisi Santrali (RES) kurulumu için uygun sahaların mekânsal olarak belirlenmesi

Bu çalışmada; Kırşehir il sınırları içerisinde rüzgâr enerjisi santrali (RES) kurulumu için uygun sahaların mekânsal olarak belirlenmesi amaçlanmıştır. Bu amaç doğrultusunda, uygun sahaların tespit edilebilmesi için 15 kriter belirlenmiştir. Bu kriterler; rüzgâr hızı, güç yoğunluğu, yükseklik, eğim, pürüzlülük, arazi kullanımı, litoloji, enerji nakil hatlarına uzaklık, trafo merkezlerine uzaklık, yollara uzaklık, korunan alanlara uzaklık, kuş göç yolları, yerleşim alanlarına uzaklık ve akarsulara uzaklıktır. Belirlenen kriterlerin değerlendirilebilmesi için gerekli coğrafi veriler, ilgili kuruluşlardan temin edilmiştir. Bu kriterlerin birbirlerine göre önem derecelerini belirleyebilmek için Analitik Hiyerarşi Süreci (AHS) yönteminden yararlanılmıştır. Kriterlerin ağırlık değerleri belirlenirken literatür taraması yapılmış ve uzman görüşleri alınmıştır. Her kriter için mekansal raster katman oluşturulmuştur. Hesaplanan önem derecelerine göre 15 katman, ağırlıklı çakıştırma yapılarak Kırşehir ili için RES uygunluk haritası oluşturulmuştur. Son olarak Kırşehir il sınırları içerisinde kurulu olan bir adet RES’in (GEYCEK RES) de belirlenen uygun sahalarda olduğu tespit edilmiştir

Hot Spots in a Network of Functional Sites

<div><p>It is of significant interest to understand how proteins interact, which holds the key phenomenon in biological functions. Using dynamic fluctuations in high frequency modes, we show that the Gaussian Network Model (GNM) predicts hot spot residues with success rates ranging between S 8–58%, C 84–95%, P 5–19% and A 81–92% on unbound structures and S 8–51%, C 97–99%, P 14–50%, A 94–97% on complex structures for sensitivity, specificity, precision and accuracy, respectively. High specificity and accuracy rates with a single property on unbound protein structures suggest that hot spots are predefined in the dynamics of unbound structures and forming the binding core of interfaces, whereas the prediction of other functional residues with similar dynamic behavior explains the lower precision values. The latter is demonstrated with the case studies; ubiquitin, hen egg-white lysozyme and M2 proton channel. The dynamic fluctuations suggest a pseudo network of residues with high frequency fluctuations, which could be plausible for the mechanism of biological interactions and allosteric regulation.</p></div

The GNM performance values of the unbound dataset.

<p>Labels S, C, P and A refer to sensitivity, specificity, precision and accuracy, respectively. GNM modes 1–3 and 1–5 refer to the average three and five fastest modes, respectively. The reported values are percentages.</p

(A1 & A2) The GNM analysis performed on Ubiquitin (1 D3Z [104]).

<p>Experimentally determined hot spot residues (lines) and the long range interactions (sticks) are shown with the exact outcome of the fastest mode (blue) and the second fastest mode (red). Details are in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074320#pone.0074320.s010" target="_blank">Figure S10</a>. (A1) and (A2) display the same figure from two perspectives. (B) The residues fluctuating in the high frequency modes by GNM for the unbound (dark grey: 2<b> </b>LYM <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074320#pone.0074320-Kundrot1" target="_blank">[89]</a>) and bound (light grey: 2<b> </b>LYO <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074320#pone.0074320-Wang2" target="_blank">[83]</a>) hen egg-white lysozyme (HEWL) structures in orange and in cyan, respectively. Experimentally determined hot spot residues (sticks), ligand (yellow sphere), and catalytic residues (dots) are also shown. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074320#pone.0074320.s011" target="_blank">Figure S11</a>. (C1 &C2) The GNM analysis performed on Influenza virus M2 proton channel, 3<b> </b>BKD <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074320#pone.0074320-Stouffer1" target="_blank">[95]</a>: (C1) the amantadine bound structure 2<b> </b>KQT <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074320#pone.0074320-Cady1" target="_blank">[105]</a> and (C2) the rimantadine bound 2<b> </b>RLF <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074320#pone.0074320-Schnell1" target="_blank">[91]</a>. The exact outcome of the fluctuations in the average five fastest modes above the threshold is colored based on the strength of fluctuations in the decreasing order (red to green). Blue display the residues below the threshold. Rimantadine and amantadine are shown in magenta dots with the corresponding sites in lines and in sticks, respectively. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074320#pone.0074320.s012" target="_blank">Figure S12</a>.</p