Inventing the dynamo machine: the evolution of the F-type and V-type ATPases

The rotary proton- and sodium-translocating ATPases are reversible molecular machines present in all cellular life forms that couple ion movement across membranes with ATP hydrolysis or synthesis. Sequence and structural comparisons of F- and V-type ATPases have revealed homology between their catalytic and membrane subunits, but not between the subunits of the central stalk that connects the catalytic and membrane components. Based on this pattern of homology, we propose that these ATPases originated from membrane protein translocases, which, themselves, evolved from RNA translocases. We suggest that in these ancestral translocases, the position of the central stalk was occupied by the translocated polymer.     

Semi-supervised protein classification using cluster kernels

MOTIVATION: Building an accurate protein classification system depends critically upon choosing a good representation of the input sequences of amino acids. Recent work using string kernels for protein data has achieved state-of-the-art classification performance. However, such representations are based only on labeled data--examples with known 3D structures, organized into structural classes--whereas in practice, unlabeled data are far more plentiful. RESULTS: In this work, we develop simple and scalable cluster kernel techniques for incorporating unlabeled data into the representation of protein sequences. We show that our methods greatly improve the classification performance of string kernels and outperform standard approaches for using unlabeled data, such as adding close homologs of the positive examples to the training data. We achieve equal or superior performance to previously presented cluster kernel methods and at the same time achieving far greater computational efficiency. AVAILABILITY: Source code is available at www.kyb.tuebingen.mpg.de/bs/people/weston/semiprot. The Spider matlab package is available at www.kyb.tuebingen.mpg.de/bs/people/spider. SUPPLEMENTARY INFORMATION: www.kyb.tuebingen.mpg.de/bs/people/weston/semiprot.     

A life-like virtual cell membrane using discrete automata

A framework is presented that captures the discrete and probabilistic nature of molecular transport and reaction kinetics found in a living cell as well as formally representing the spatial distribution of these phenomena. This particle or agent-based approach is computationally robust and complements established methods. Namely it provides a higher level of spatial resolution than formulations based on ordinary differential equations (ODE) while offering significant advantages in computational efficiency over molecular dynamics (MD). Using this framework, a model cell membrane has been constructed with discrete particle agents that respond to local component interactions that resemble flocking or herding behavioural cues in animals. Results from simulation experiments are presented where this model cell exhibits many of the characteristic behaviours associated with its biological counterpart such as lateral diffusion, response to osmotic pressure gradients, membrane growth and cell division. Lateral diffusion rates and estimates for the membrane modulus of elasticity derived from these simple experiments fall well within a biologically relevant range of values. More importantly, these estimates were obtained by applying a simple qualitative tuning of the model membrane. Membrane growth was simulated by injecting precursor molecules into the proto-cell at different rates and produced a variety of morphologies ranging from a single large cell to a cluster of cells. The computational scalability of this methodology has been tested and results from benchmarking experiments indicate that real-time simulation of a complete bacterial cell will be possible within 10 years.     

Role of protein phosphatase 2A in mGluR5-regulated MEK/ERK phosphorylation in neurons

The regulation of protein phosphorylation requires coordinated interaction between protein kinases and protein phosphatases (PPs). Recent evidence has shown that the Galphaq-protein-coupled metabotropic glutamate receptor (mGluR) 5 up-regulates phosphorylation of MAPK/ERK1/2. However, signaling mechanisms linking mGluR5 to ERK are poorly understood. In this study, roles of a major serine/threonine PP, PP2A, in this event were evaluated in cultured neurons. We found that the PP1/2A inhibitors okadaic acid and calyculin A mimicked the effect of the mGluR5 agonists (RS)-3,5-dihydroxyphenylglycine and (RS)-2-chloro-5-hydroxyphenylglycine in facilitating phosphorylation of ERK1/2 and its upstream kinase, MEK1/2, in a PP2A-dependent but not PP1-dependent manner. Co-administration of either inhibitor with an mGluR5 agonist produced additive phosphorylation of ERK1/2. Enzymatic assays showed a basal level of phosphatase activity of PP2A under normal conditions, and activation of mGluR5 selectively inhibited PP2A, but not PP1, activity. In addition, a physical association of the cytoplasmic C terminus of mGluR5 with PP2A was observed, and ligand activation of mGluR5 reduced mGluR5-PP2A binding. Additional mechanistic studies revealed that mGluR5 activation increased tyrosine (Tyr307) phosphorylation of PP2A, which was dependent on activation of a p60c-Src family tyrosine kinase, but not the epidermal growth factor receptor tyrosine kinase and resulted in dissociation of PP2A from mGluR5 and reduced PP2A activity. Together, we have identified a novel, mGluR5-triggered signaling mechanism involving use- and Src-dependent inactivation of PP2A, which contributes to mGluR5 activation of MEK1/2 and ERK1/2.     

Immunogenetic factors in beryllium sensitization and chronic beryllium disease

Exposure to beryllium in the workplace can cause beryllium sensitization and chronic beryllium disease. Sensitization to beryllium can be detected in the laboratory using the beryllium lymphocyte proliferation test. It was shown that anti-HLA antibodies could block the beryllium-specific response in the beryllium lymphocyte proliferation test, thereby implicating HLA genes in chronic beryllium disease. A supratypic genetic marker, HLA-DPB1*E69, was found to be strongly associated with immunologic sensitization to beryllium and chronic beryllium disease in beryllium workers. However, there are 40 HLA-DPB1 gene variants that have E69 but that also have other DNA sequence variations. The purpose of the study was to evaluate the evidence for potential differential susceptibility that may be associated with the physical characteristics of HLA protein molecules for which different HLA-DPB1*E69 variants code; that is, do some HLA-DPB1*E69 variants convey higher risk of beryllium sensitization and chronic beryllium disease than others. To do this, two approaches were pursued: first, detailed analysis of the findings from the published literature was performed, and second, computational chemistry was used to seek clues concerning the physical properties of the HLA protein molecules for which these alleles code. Among the 40 HLA-DPB1 gene variants that code for E69, molecular epidemiological studies have suggested a risk hierarchy, where some variants appear to convey low to moderate risk of chronic beryllium disease (e.g., HLA-DPB1*0201, approximately 3-fold increased risk), some convey an intermediate risk (e.g., HLA-DPB1*1901, approximately 5-fold) and others convey high risk (e.g., HLA-DPB1*1701, >10-fold). Molecular modeling has been used to further investigate a potential mechanistic basis for these observations. We found a strong correlation between the hierarchical order of risk of chronic beryllium disease associated with specific alleles and the predicted surface electrostatic potential and charge of the corresponding isotypes. Therefore, when alleles were grouped by the relative negative charge on the molecules for which they code, the data suggest that those alleles associated with the most negatively charged proteins carry the greatest risk of beryllium sensitization and disease.     

Global analysis of fluorescence fluctuation data

Over the last decade the number of applications of fluorescence correlation spectroscopy (FCS) has grown rapidly. Here we describe the development and application of a software package, FCS Data Processor, to analyse the acquired correlation curves. The algorithms combine strong analytical power with flexibility in use. It is possible to generate initial guesses, link and constrain fit parameters to improve the accuracy and speed of analysis. A global analysis approach, which is most effective in analysing autocorrelation curves determined from fluorescence fluctuations of complex biophysical systems, can also be implemented. The software contains a library of frequently used models that can be easily extended to include user-defined models. The use of the software is illustrated by analysis of different experimental fluorescence fluctuation data sets obtained with Rhodamine Green in aqueous solution and enhanced green fluorescent protein in vitro and in vivo.An erratum to this article can be found at Victor V. Skakun, Mark A. Hink and Anatoli V. Digris contributed equally to this work.     

Synthesis and evaluation of urea-based indazoles as melanin-concentrating hormone receptor 1 antagonists for the treatment of obesity

A series of urea-based N-1-(2-aminoethyl)-indazoles was synthesized and evaluated for melanin-concentrating hormone receptor 1 (MCHr1) antagonism in both binding and functional assays. Several compounds that acted as MCHr1 antagonists were identified, and optimization afforded a compound with excellent binding affinity, good functional potency, and oral efficacy in a chronic model for weight loss in diet-induced obese mice.