Real value prediction of protein solvent accessibility using enhanced PSSM features

<p>Abstract</p> <p>Background</p> <p>Prediction of protein solvent accessibility, also called accessible surface area (ASA) prediction, is an important step for tertiary structure prediction directly from one-dimensional sequences. Traditionally, predicting solvent accessibility is regarded as either a two- (exposed or buried) or three-state (exposed, intermediate or buried) classification problem. However, the states of solvent accessibility are not well-defined in real protein structures. Thus, a number of methods have been developed to directly predict the real value ASA based on evolutionary information such as position specific scoring matrix (PSSM).</p> <p>Results</p> <p>This study enhances the PSSM-based features for real value ASA prediction by considering the physicochemical properties and solvent propensities of amino acid types. We propose a systematic method for identifying residue groups with respect to protein solvent accessibility. The amino acid columns in the PSSM profile that belong to a certain residue group are merged to generate novel features. Finally, support vector regression (SVR) is adopted to construct a real value ASA predictor. Experimental results demonstrate that the features produced by the proposed selection process are informative for ASA prediction.</p> <p>Conclusion</p> <p>Experimental results based on a widely used benchmark reveal that the proposed method performs best among several of existing packages for performing ASA prediction. Furthermore, the feature selection mechanism incorporated in this study can be applied to other regression problems using the PSSM. The program and data are available from the authors upon request.</p

Predicting the protein-protein interactions using primary structures with predicted protein surface

<p>Abstract</p> <p>Background</p> <p>Many biological functions involve various protein-protein interactions (PPIs). Elucidating such interactions is crucial for understanding general principles of cellular systems. Previous studies have shown the potential of predicting PPIs based on only sequence information. Compared to approaches that require other auxiliary information, these sequence-based approaches can be applied to a broader range of applications.</p> <p>Results</p> <p>This study presents a novel sequence-based method based on the assumption that protein-protein interactions are more related to amino acids at the surface than those at the core. The present method considers surface information and maintains the advantage of relying on only sequence data by including an accessible surface area (ASA) predictor recently proposed by the authors. This study also reports the experiments conducted to evaluate a) the performance of PPI prediction achieved by including the predicted surface and b) the quality of the predicted surface in comparison with the surface obtained from structures. The experimental results show that surface information helps to predict interacting protein pairs. Furthermore, the prediction performance achieved by using the surface estimated with the ASA predictor is close to that using the surface obtained from protein structures.</p> <p>Conclusion</p> <p>This work presents a sequence-based method that takes into account surface information for predicting PPIs. The proposed procedure of surface identification improves the prediction performance with an <it>F-measure </it>of 5.1%. The extracted surfaces are also valuable in other biomedical applications that require similar information.</p

Search for a Very Light CP-Odd Higgs Boson in Top Quark Decays from p(p)over-bar Collisions at root s=1.96 TeV

We present the results of a search for a very light CP-odd Higgs boson a(1)(0) originating from top quark decays t -> H(+/-)b -> W-+/-(*) a(1)(0)b, and subsequently decaying into tau(+)tau(-). Using a data sample corresponding to an integrated luminosity of 2.7 fb(-1) collected by the CDF II detector in p (p) over bar collisions at 1.96 TeV, we perform a search for events containing a lepton, three or more jets, and an additional isolated track with transverse momentum in the range 3 to 20 GeV/c. Observed events are consistent with background sources, and 95% C.L. limits are set on the branching ratio of t -> H(+/-)b for various masses of H-+/- and a(1)(0)

Docosahexaenoic Acid Alleviates Trimethylamine-N-oxide-mediated Impairment of Neovascularization in Human Endothelial Progenitor Cells

BackgroundHuman endothelial progenitor cells (hEPCs), originating from hemangioblasts in bone marrow (BM), migrate into the blood circulation, differentiate into endothelial cells, and could act as an alternative tool for tissue regeneration. In addition, trimethylamine-N-oxide (TMAO), one of the gut microbiota metabolites, has been identified as an atherosclerosis risk factor. However, the deleterious effects of TMAO on the neovascularization of hEPCs have not been studied yet.ResultsOur results demonstrated that TMAO dose-dependently impaired human stem cell factor (SCF)-mediated neovascularization in hEPCs. The action of TMAO was through the inactivation of Akt/endothelial nitric oxide synthase (eNOS), MAPK/ERK signaling pathways, and an upregulation of microRNA (miR)-221. Docosahexaenoic acid (DHA) could effectively inhibit the cellular miR-221 level and induce the phosphorylation level of Akt/eNOS, MAPK/ERK signaling molecules, and neovascularization in hEPCs. DHA enhanced cellular amounts of reduced form glutathione (GSH) through an increased expression of the gamma-glutamylcysteine synthetase (γ-GCS) protein.ConclusionsTMAO could significantly inhibit SCF-mediated neovascularization, in part in association with an upregulation of miR-221 level, inactivation of Akt/eNOS and MAPK/ERK cascades, suppression of γ-GCS protein, and decreased levels of GSH and GSH/GSSG ratio. Furthermore, the DHA could alleviate the detrimental effects of TMAO and induce neovasculogenesis through suppression of miR-221 level, activation of Akt/eNOS and MAPK/ERK signaling cascades, increased expression of γ-GCS protein, and increment of cellular GSH level and GSH/GSSG ratio in hEPCs

Docosahexaenoic Acid Alleviates Trimethylamine-<i>N</i>-oxide-mediated Impairment of Neovascularization in Human Endothelial Progenitor Cells

Background: Human endothelial progenitor cells (hEPCs), originating from hemangioblasts in bone marrow (BM), migrate into the blood circulation, differentiate into endothelial cells, and could act as an alternative tool for tissue regeneration. In addition, trimethylamine-N-oxide (TMAO), one of the gut microbiota metabolites, has been identified as an atherosclerosis risk factor. However, the deleterious effects of TMAO on the neovascularization of hEPCs have not been studied yet. Results: Our results demonstrated that TMAO dose-dependently impaired human stem cell factor (SCF)-mediated neovascularization in hEPCs. The action of TMAO was through the inactivation of Akt/endothelial nitric oxide synthase (eNOS), MAPK/ERK signaling pathways, and an upregulation of microRNA (miR)-221. Docosahexaenoic acid (DHA) could effectively inhibit the cellular miR-221 level and induce the phosphorylation level of Akt/eNOS, MAPK/ERK signaling molecules, and neovascularization in hEPCs. DHA enhanced cellular amounts of reduced form glutathione (GSH) through an increased expression of the gamma-glutamylcysteine synthetase (γ-GCS) protein. Conclusions: TMAO could significantly inhibit SCF-mediated neovascularization, in part in association with an upregulation of miR-221 level, inactivation of Akt/eNOS and MAPK/ERK cascades, suppression of γ-GCS protein, and decreased levels of GSH and GSH/GSSG ratio. Furthermore, the DHA could alleviate the detrimental effects of TMAO and induce neovasculogenesis through suppression of miR-221 level, activation of Akt/eNOS and MAPK/ERK signaling cascades, increased expression of γ-GCS protein, and increment of cellular GSH level and GSH/GSSG ratio in hEPCs