A new computational approach to analyze human protein complexes and predict novel protein interactions

We propose a new approach to identify interacting proteins based on gene expression data. By using hypergeometric distribution and extensive Monte-Carlo simulations, we demonstrate that looking at synchronous expression peaks in a single time interval is a high sensitivity approach to detect co-regulation among interacting proteins. Combining gene expression and Gene Ontology similarity analyses enabled the extraction of novel interactions from microarray datasets. Applying this approach to p21-activated kinase 1, we validated α-tubulin and early endosome antigen 1 as its novel interactors.     

A universal thermodynamic approach to analyze biomolecular binding experiments

Binding processes of any kind can be characterized as an association of a given ligand with some binding factor. This includes macromolecules as well as supramolecular aggregates such as micelles or membranes. The underlying molecular binding mechanism may be more or less complicated due to various intermediate steps (involving for instance conformational changes, aggregation, cooperativity, etc.). A sensible discussion of possible binding models naturally calls for a model-independent access to basic thermodynamic properties. The present contribution will demonstrate how this can quite generally be accomplished by a pertinent processing of properly selected experimental data. The method requires a series of titration measurements comprising the use of variable amounts of both the ligand and the binding factor. It leads to a linear mass conservation plot (i.e. amount of the ligand vs. a matching amount of the binding factor) whose slope and ordinate intercept are equal to the binding ratio (i.e. bound ligand per binding factor) and the free ligand concentration, respectively. This establishes the specific binding isotherm. The approach also reveals latent structurally determined features of the applied physical measuring signal. A number of examples including specific binding, unspecific adsorption and insertion in two-dimensional molecular films will illustrate the methodology.     

A molecular chromatographic approach to analyze the cell diffusion of arginase inhibitors

Our group demonstrated that arginase inhibition reduces endothelial dysfunction in spontaneously hypertensive rats [C. Demougeot, A. Prigent-Tessier, C. Marie, A. Berthelot, J. Hypertens. 23 (2005) 971; C. Demougeot, A. Prigent-Tessier, T. Bagnost, C. Andre, Y. Guillaume, M. Bouhaddi, C. Marie, A. Berthelot, Life Sci. 80 (2007) 1128] which opens perspectives in the development of drugs against hypertension. In previous papers [T. Bagnost, Y.C. Guillaume, M. Thomassin, J.F. Robert, A. Berthelot, A. Xicluna, C. Andre, J. Chromatogr. B: Analyt. Technol. Biomed. Life Sci. 856 (2007) 113; T. Bagnost, Y.C. Guillaume, M. Thomassin, A. Berthelot, C. Demougeot, C. Andre, J. Chromatogr. B: Analyt. Technol. Biomed. Life Sci. 873 (2008) 37], we developed a biochromatographic column for studying the binding of an arginase inhibitor with this enzyme and the effect of magnesium on this binding. In this paper, the interaction of arginase inhibitors with an immobilized artificial membrane (IAM) has been studied using a biochromatographic approach. This IAM provided a biophysical model system to study the inhibitor passive transport across cells. It was demonstrated that more the inhibitor cross the cell membrane by passive diffusion more it is potent. As well, an analysis of the thermodynamics of the interaction of the arginase inhibitors with the IAM showed that van der Waals, hydrogen and ionic bonds were the main forces between the arginase inhibitors and the polar head groups of the IAM surface.     

A computational approach to analyze the mechanism of action of the kinase inhibitor bafetinib

Prediction of drug action in human cells is a major challenge in biomedical research. Additionally, there is strong interest in finding new applications for approved drugs and identifying potential side effects. We present a computational strategy to predict mechanisms, risks and potential new domains of drug treatment on the basis of target profiles acquired through chemical proteomics. Functional protein-protein interaction networks that share one biological function are constructed and their crosstalk with the drug is scored regarding function disruption. We apply this procedure to the target profile of the second-generation BCR-ABL inhibitor bafetinib which is in development for the treatment of imatinib-resistant chronic myeloid leukemia. Beside the well known effect on apoptosis, we propose potential treatment of lung cancer and IGF1R expressing blast crisis.     

A frequentist approach to dynamic borrowing

There has been growing interest in leveraging external control data to augment a randomized control group data in clinical trials and enable more informative decision making. In recent years, the quality and availability of real-world data have improved steadily as external controls. However, information borrowing by directly pooling such external controls with randomized controls may lead to biased estimates of the treatment effect. Dynamic borrowing methods under the Bayesian framework have been proposed to better control the false positive error. However, the numerical computation and, especially, parameter tuning, of those Bayesian dynamic borrowing methods remain a challenge in practice. In this paper, we present a frequentist interpretation of a Bayesian commensurate prior borrowing approach and describe intrinsic challenges associated with this method from the perspective of optimization. Motivated by this observation, we propose a new dynamic borrowing approach using adaptive lasso. The treatment effect estimate derived from this method follows a known asymptotic distribution, which can be used to construct confidence intervals and conduct hypothesis tests. The finite sample performance of the method is evaluated through extensive Monte Carlo simulations under different settings. We observed highly competitive performance of adaptive lasso compared to Bayesian approaches. Methods for selecting tuning parameters are also thoroughly discussed based on results from numerical studies and an illustration example.     

A quantitative approach to analyze binding diffusion kinetics by confocal FRAP

Most of the important types of interactions that occur in cells can be characterized as binding-diffusion type processes, and can be quantified by kinetic rate constants such as diffusion coefficients (D) and binding rate constants (k_on and k_off). Confocal FRAP is a potentially important tool for the quantitative analysis of intracellular binding-diffusion kinetics, but how to dependably extract accurate kinetic constants from such analyses is still an open question. To this end, in this study, we developed what we believe is a new analytical model for confocal FRAP-based measurements of intracellular binding-diffusion processes, based on a closed-form equation of the FRAP formula for a spot photobleach geometry. This approach incorporates a binding diffusion model that allows for diffusion of both the unbound and bound species, and also compensates for binding diffusion that occurs during photobleaching, a critical consideration in confocal FRAP analysis. In addition, to address the problem of parametric multiplicity, we propose a scheme to reduce the number of fitting parameters in the effective diffusion subregime when D's for the bound and unbound species are known. We validate this method by measuring kinetic rate constants for the CAAX-mediated binding of Ras to membranes of the endoplasmic reticulum, obtaining binding constants of k_on ∼ 255/s and k_off ∼ 31/s.     

A proteomic approach to analyze salt-responsive proteins in rice leaf sheath

To examine the response of rice to salt stress, changes in protein expression were analyzed using a proteomic approach. To investigate dose- and time-dependent responses, rice seedlings were exposed to 50, 100 and 150 mM NaCl for 6 to 48 h. Proteins were extracted from leaf sheath and separated by two-dimensional polyacrylamide gel electrophoresis. Eight proteins showed 1- to 3-fold up-regulation in leaf sheath, in response to 50 mM NaCl for 24 h. Among these, three proteins were unidentified (LSY081, LSY262 and LSY363) while five proteins were identified as fructose bisphosphate aldolases, photosystem II (PSII) oxygen evolving complex protein, oxygen evolving enhancer protein 2 (OEE2) and superoxide dismutase (SOD). The maximum expression levels of seven proteins were at 24 h. Their expression declined after 48 h of 50 mM NaCl treatment. In contrast, SOD maintained its elevated expression throughout these conditions. The increased expression of proteins seen in the 50 mM NaCl treatment group was less pronounced in the groups receiving 100 or 150 mM NaCl for 24 h. The expression of SOD was a common response to cold, drought, salt and abscisic acid (ABA) stresses while the expression of LSY081, LSY363 and OEE2 was enhanced by salt and ABA stresses. LSY262 was expressed in leaf sheath and root, while fructose bisphosphate aldolases, PSII oxygen evolving complex protein and OEE2 were expressed in leaf sheath and leaf blade. LSY363 was expressed in leaf sheath but was below the level of detection in leaf blade and root. These results indicate that specific proteins expressed in specific regions of rice show a coordinated response to salt stress.     

A dynamic approach to tolerate soft errors

Dynamic implementation for software-based soft error tolerance method which can protect more types of codes can cover more soft errors. This paper explores soft error tolerance with dynamic software-based method. We propose a new dynamic software-based approach to tolerate soft errors. In our approach, the objective which is protected is dynamic program. For those protected dynamic binary codes, we make sure right control flow and right data flow to significant extent in our approach. Our approach copies every data and operates every operation twice to ensure those data stored into memory are right. Additionally, we ensure every branch instruction can jump to the right address by checking condition and destination address. Our approach is implemented by the technique dynamic binary instrumentation. Specifically, our tool is implemented on the basis of valgrind framework which is a heavyweight dynamic binary instrumentation tool. Our experimental results demonstrate that our approach can get higher reliability of dynamic software than those approaches which is implemented with static program protection method. However, our approach is only suitable for the system which has a strict requirement of reliability because our approach also sacrifices more performance of software than those static program protection methods.     

A new approach to experimental investigation of dynamic self-organization in reaction centers of purple bacteria

The results of a study of molecular self-organization processes in the reaction centers (RC) ofRb. Sphaeroides purple bacteria by the method of pulsed optical excitation is presented. The existence of a bistability domain for the parameters of RC recovery kinetics is shown. A good agreement between the theory and experimental results is obtained.     

A new approach to microhomogenization

A versatile microhomogenizer is described which is capable of handling sample volumes ranging from 1 μl to several millititers. The sample and homogenization buffer are sealed within a segment of flexible plastic tubing. The sample is disrupted by rubbing or rolling a metal rod back and forth over the length of tubing. Centrifugation of the homogenate is performed in the same sealed tubing segment. This method can be used to homogenize single cells.     

A proteomic approach to analyze nitrogen- and cytokinin-responsive proteins in rice roots

Nitrogen plays a central role in rice growth and development because it modulates a wide variety of processes, including cytokinin (CK) metabolism. CK-mediated signaling is also related to nitrogen metabolism. The functional relation between nitrogen and CK are extremely complex and unclear. In this study, a comparative proteomic analysis was carried out to analyze proteins regulated by nitrogen and CK in rice roots. Proteins extracted from rice roots are separated by two-dimensional polyacrylamide gel electrophoresis. Thirty-two protein spots that expressed similarly by nitrogen and CK treatments are selected for identification by mass spectrometry. Of these spots, 28 are successfully identified. These proteins were categorized into classes related to energy, metabolism, disease/defense, protein degradation, signal transduction, transposons, and unclear classification. Energy gives the largest functional category, suggesting that the glycolysis (two enzymes detected) and tricarboxylic acid cycle (six enzymes detected) are accurately regulated by nitrogen and CK, thus promoting the synthesis of amino acid. The identification of novel proteins provides new insights into the coordination of nitrogen and CK in rice. The possible role of these proteins is discussed.     

A new approach to the Namib Region

For a new approach to the phytogeography of the Namib region three sets of data are analyzed, (a) distribution data of ca. 1700 taxa, (b) habitat informations of a large number of taxa, collected in course of an extensive phytosociological survey, (c) distribution data of characteristic life form spectra and plant formations.In this paper, as a first step of a comprehensive phytochorological analysis, phytochoria and their limits are proposed as derived from frequently observed areas of distribution, while a numerical analysis of the complete flora of these phytochoria is in preparation.