Predicting and improving the protein sequence alignment quality by support vector regression

Abstract Background For successful protein structure prediction by comparative modeling, in addition to identifying a good template protein with known structure, obtaining an accurate sequence alignment between a query protein and a template protein is critical. It has been known that the alignment accuracy can vary significantly depending on our choice of various alignment parameters such as gap opening penalty and gap extension penalty. Because the accuracy of sequence alignment is typically measured by comparing it with its corresponding structure alignment, there is no good way of evaluating alignment accuracy without knowing the structure of a query protein, which is obviously not available at the time of structure prediction. Moreover, there is no universal alignment parameter option that would always yield the optimal alignment. Results In this work, we develop a method to predict the quality of the alignment between a query and a template. We train the support vector regression (SVR) models to predict the MaxSub scores as a measure of alignment quality. The alignment between a query protein and a template of length n is transformed into a (n + 1)-dimensional feature vector, then it is used as an input to predict the alignment quality by the trained SVR model. Performance of our work is evaluated by various measures including Pearson correlation coefficient between the observed and predicted MaxSub scores. Result shows high correlation coefficient of 0.945. For a pair of query and template, 48 alignments are generated by changing alignment options. Trained SVR models are then applied to predict the MaxSub scores of those and to select the best alignment option which is chosen specifically to the query-template pair. This adaptive selection procedure results in 7.4% improvement of MaxSub scores, compared to those when the single best parameter option is used for all query-template pairs. Conclusion The present work demonstrates that the alignment quality can be predicted with reasonable accuracy. Our method is useful not only for selecting the optimal alignment parameters for a chosen template based on predicted alignment quality, but also for filtering out problematic templates that are not suitable for structure prediction due to poor alignment accuracy. This is implemented as a part in FORECAST, the server for fold-recognition and is freely available on the web at http://pbil.kaist.ac.kr/forecast</p

Down-regulation of phosphoglucomutase 3 mediates sulforaphane-induced cell death in LNCaP prostate cancer cells

<p>Abstract</p> <p>Background</p> <p>Sulforaphane (SFN) is an isothiocyanate found in cruciferous vegetables that exerts anti-oxidant, anti-inflammatory, anti-cancer and radio-sensitizing activities. Nonetheless, the mechanism responsible for SFN-induced cell death is not fully understood. In the present study, anti-cancer mechanism of SFN was elucidated in LNCaP prostate cancer cells.</p> <p>Results</p> <p>SFN exerted cytotoxicity and increased TUNEL positive cells in a concentration-dependent manner in LNCaP cells. Proteomics study revealed that levels of nine proteins including tubulin β-2, phosphoglucomutase-3 (PGM3), melanoma-derived leucine zipper containing extra-nuclear factor, activin A type I receptor precursor, smoothelin-A, KIA0073, hypothetical protein LOC57691 and two unnamed proteins were changed over 8 folds in SFN treated LNCaP cells compared to untreated control. We have further confirmed that SFN reduced PGM3 expression with western blotting and showed that PGM3 siRNA enhanced cytotoxicity demonstrated by cell morphology and TUNEL assays in LNCaP cells.</p> <p>Conclusion</p> <p>Taken together, these findings suggest that PGM3 plays a role in mediating SFN-induced cell death in LNCaP cells, and is a potential molecular therapeutic target for prostate cancer.</p

Geomagnetic field influences probabilistic abstract decision-making in humans

To resolve disputes or determine the order of things, people commonly use binary choices such as tossing a coin, even though it is obscure whether the empirical probability equals to the theoretical probability. The geomagnetic field (GMF) is broadly applied as a sensory cue for various movements in many organisms including humans, although our understanding is limited. Here we reveal a GMF-modulated probabilistic abstract decision-making in humans and the underlying mechanism, exploiting the zero-sum binary stone choice of Go game as a proof-of-principle. The large-scale data analyses of professional Go matches and in situ stone choice games showed that the empirical probabilities of the stone selections were remarkably different from the theoretical probability. In laboratory experiments, experimental probability in the decision-making was significantly influenced by GMF conditions and specific magnetic resonance frequency. Time series and stepwise systematic analyses pinpointed the intentionally uncontrollable decision-making as a primary modulating target. Notably, the continuum of GMF lines and anisotropic magnetic interplay between players were crucial to influence the magnetic field resonance-mediated abstract decision-making. Our findings provide unique insights into the impact of sensing GMF in decision-makings at tipping points and the quantum mechanical mechanism for manifesting the gap between theoretical and empirical probability in 3-dimensional living space.Comment: 32 pages, 5 figures, 4 supplementary figures, 2 supplementary tables, and separate 15 ancillary file

Tunable electron scattering mechanism in plasmonic SrMoO3_3 thin films

4d transition metal perovskite oxides serve as suitable testbeds for the study of strongly correlated metallic properties. Among these, $SrMoO_{3}$ (SMO) exhibits remarkable electrical conductivity at room temperature. The temperature-dependent resistivity $(\rho(T))$ exhibits a Fermi-liquid behavior below the transition temperature $T^{*}$, reflecting the dominant electron-electron interaction. Above $T^{*}$, electron-phonon interaction becomes more appreciable. In this study, we employed the power-law scaling of $\rho(T)$ to rigorously determine the $T^{*}$. We further demonstrate that the $T^{*}$ can be modified substantially by ~40 K in epitaxial thin films. It turns out that the structural quality determines $T^{*}$. Whereas the plasma frequency could be tuned by the change in the electron-electron interaction via the effective mass enhancement, we show that the plasmonic properties are more directly governed by the electron-impurity scattering. The facile control of the electron scattering mechanism through structural quality modulation can be useful for plasmonic sensing applications in the visible region

Effect of the Phosphorus Gettering on Si Heterojunction Solar Cells

To improve the efficiency of crystalline silicon solar cells, should be collected the excess carrier as much as possible. Therefore, minimizing the recombination both at the bulk and surface regions is important. Impurities make recombination sites and they are the major reason for recombination. Phosphorus (P) gettering was introduced to reduce metal impurities in the bulk region of Si wafers and then to improve the efficiency of Si heterojunction solar cells fabricated on the wafers. Resistivity of wafers was measured by a four-point probe method. Fill factor of solar cells was measured by a solar simulator. Saturation current and ideality factor were calculated from a dark current density-voltage graph. External quantum efficiency was analyzed to assess the effect of P gettering on the performance of solar cells. Minority bulk lifetime measured by microwave photoconductance decay increases from 368.3 to 660.8 mu s. Open-circuit voltage and short-circuit current density increase from 577 to 598 mV and 27.8 to 29.8mA/cm(2), respectively. The efficiency of solar cells increases from 11.9 to 13.4%. P gettering will be feasible to improve the efficiency of Si heterojunction solar cells fabricated on P-doped Si wafers.open1

Involvement of mTOR signaling in sphingosylphosphorylcholine-induced hypopigmentation effects

<p>Abstract</p> <p>Background</p> <p>Sphingosylphosphorylcholine (SPC) acts as a potent lipid mediator and signaling molecule in various cell types. In the present study, we investigated the effects of SPC on melanogenesis and SPC-modulated signaling pathways related to melanin synthesis.</p> <p>Methods</p> <p>Melanin production was measured in Mel-Ab cells. A luciferase assay was used to detect transcriptional activity of the MITF promoter. Western blot analysis was performed to examine SPC-induced signaling pathways.</p> <p>Results</p> <p>SPC produced significant hypopigmentation effects in a dose-dependent manner. It was found that SPC induced not only activation of Akt but also stimulation of mTOR, a downstream mediator of the Akt signaling pathway. Moreover, SPC decreased the levels of LC3 II, which is known to be regulated by mTOR. Treatment with the mTOR inhibitor rapamycin eliminated decreases in melanin and LC3 II levels by SPC. Furthermore, we found that the Akt inhibitor LY294002 restored SPC-mediated downregulation of LC3 II and inhibited the activation of mTOR by SPC.</p> <p>Conclusions</p> <p>Our data suggest that the mTOR signaling pathway is involved in SPC-modulated melanin synthesis.</p

Concomitant renal insufficiency and diabetes mellitus as prognostic factors for acute myocardial infarction

<p>Abstract</p> <p>Background</p> <p>Diabetes mellitus and renal dysfunction are prognostic factors after acute myocardial infarction (AMI). However, few studies have assessed the effects of renal insufficiency in association with diabetes in the context of AMI. Here, we investigated the clinical outcomes according to the concomitance of renal dysfunction and diabetes mellitus in patients with AMI.</p> <p>Methods</p> <p>From November 2005 to August 2008, 9905 patients (63 ± 13 years; 70% men) with AMI were enrolled in a nationwide prospective Korea Acute Myocardial Infarction Registry (KAMIR) and were categorized into 4 groups: Group I (n = 5700) had neither diabetes nor renal insufficiency (glomerular filtration rate [GFR] ≥ 60 ml/min/1.73 m²), Group II (n = 1730) had diabetes but no renal insufficiency, Group III (n = 1431) had no diabetes but renal insufficiency, and Group IV (n = 1044) had both diabetes and renal insufficiency. The primary endpoints were major adverse cardiac events (MACE), including a composite of all cause-of-death, myocardial infarction, target lesion revascularization, and coronary artery bypass graft after 1-year clinical follow-up.</p> <p>Results</p> <p>Primary endpoints occurred in 1804 (18.2%) patients. There were significant differences in composite MACE among the 4 groups (Group I, 12.5%; Group II, 15.7%; Group III, 30.5%; Group IV, 36.5%; <it>p </it>< 0.001). In a Cox proportional hazards model, after adjusting for multiple covariates, the 1-year mortality increased stepwise from Group III to IV as compared with Group I (hazard ratio [HR], 1.96; 95% confidence interval [CI], 1.34-2.86; <it>p </it>= 0.001; and HR, 2.42; 95% CI, 1.62-3.62; <it>p </it>< 0.001, respectively). However, Kaplan-Meier analysis showed no significant difference in probability of death at 1 year between Group III and IV (p = 0.288).</p> <p>Conclusions</p> <p>Renal insufficiency, especially in association with diabetes, is associated with the occurrence of composite MACE and indicates poor prognosis in patients with AMI. Categorization of patients with diabetes and/or renal insufficiency provides valuable information for early-risk stratification of AMI patients.</p