Equilibrium model selection: dTTP induced R1 dimerization

<p>Abstract</p> <p>Background</p> <p>Biochemical equilibria are usually modeled iteratively: given one or a few fitted models, if there is a lack of fit or over fitting, a new model with additional or fewer parameters is then fitted, and the process is repeated. The problem with this approach is that different analysts can propose and select different models and thus extract different binding parameter estimates from the same data. An alternative is to first generate a comprehensive standardized list of plausible models, and to then fit them exhaustively, or semi-exhaustively.</p> <p>Results</p> <p>A framework is presented in which equilibriums are modeled as pairs (<it>g</it>, <it>h</it>) where <it>g </it>= 0 maps total reactant concentrations (system inputs) into free reactant concentrations (system states) which <it>h </it>then maps into expected values of measurements (system outputs). By letting dissociation constants <it>K</it>_{<it>d </it>}be either freely estimated, infinity, zero, or equal to other <it>K</it>_<it>d</it>, and by letting undamaged protein fractions be either freely estimated or 1, many <it>g </it>models are formed. A standard space of <it>g </it>models for ligand-induced protein dimerization equilibria is given. Coupled to an <it>h </it>model, the resulting (<it>g</it>, <it>h</it>) were fitted to dTTP induced R1 dimerization data (R1 is the large subunit of ribonucleotide reductase). Models with the fewest parameters were fitted first. Thereafter, upon fitting a batch, the next batch of models (with one more parameter) was fitted only if the current batch yielded a model that was better (based on the Akaike Information Criterion) than the best model in the previous batch (with one less parameter). Within batches models were fitted in parallel. This semi-exhaustive approach yielded the same best models as an exhaustive model space fit, but in approximately one-fifth the time.</p> <p>Conclusion</p> <p>Comprehensive model space based biochemical equilibrium model selection methods are realizable. Their significance to systems biology as mappings of data into mathematical models warrants their development.</p

DNA building blocks: keeping control of manufacture

Ribonucleotide reductase (RNR) is the only source for de novo production of the four deoxyribonucleoside triphosphate (dNTP) building blocks needed for DNA synthesis and repair. It is crucial that these dNTP pools are carefully balanced, since mutation rates increase when dNTP levels are either unbalanced or elevated. RNR is the major player in this homeostasis, and with its four different substrates, four different allosteric effectors and two different effector binding sites, it has one of the most sophisticated allosteric regulations known today. In the past few years, the structures of RNRs from several bacteria, yeast and man have been determined in the presence of allosteric effectors and substrates, revealing new information about the mechanisms behind the allosteric regulation. A common theme for all studied RNRs is a flexible loop that mediates modulatory effects from the allosteric specificity site (s-site) to the catalytic site for discrimination between the four substrates. Much less is known about the allosteric activity site (a-site), which functions as an on-off switch for the enzyme's overall activity by binding ATP (activator) or dATP (inhibitor). The two nucleotides induce formation of different enzyme oligomers, and a recent structure of a dATP-inhibited α6β2 complex from yeast suggested how its subunits interacted non-productively. Interestingly, the oligomers formed and the details of their allosteric regulation differ between eukaryotes and Escherichia coli Nevertheless, these differences serve a common purpose in an essential enzyme whose allosteric regulation might date back to the era when the molecular mechanisms behind the central dogma evolved

HF-EPR, Raman, UV/VIS Light Spectroscopic, and DFT Studies of the Ribonucleotide Reductase R2 Tyrosyl Radical from Epstein-Barr Virus

Epstein-Barr virus (EBV) belongs to the gamma subfamily of herpes viruses, among the most common pathogenic viruses in humans worldwide. The viral ribonucleotide reductase small subunit (RNR R2) is involved in the biosynthesis of nucleotides, the DNA precursors necessary for viral replication, and is an important drug target for EBV. RNR R2 generates a stable tyrosyl radical required for enzymatic turnover. Here, the electronic and magnetic properties of the tyrosyl radical in EBV R2 have been determined by X-band and high-field/high-frequency electron paramagnetic resonance (EPR) spectroscopy recorded at cryogenic temperatures. The radical exhibits an unusually low g1-tensor component at 2.0080, indicative of a positive charge in the vicinity of the radical. Consistent with these EPR results a relatively high C-O stretching frequency associated with the phenoxyl radical (at 1508 cm−1) is observed with resonance Raman spectroscopy. In contrast to mouse R2, EBV R2 does not show a deuterium shift in the resonance Raman spectra. Thus, the presence of a water molecule as a hydrogen bond donor moiety could not be identified unequivocally. Theoretical simulations showed that a water molecule placed at a distance of 2.6 Å from the tyrosyl-oxygen does not result in a detectable deuterium shift in the calculated Raman spectra. UV/VIS light spectroscopic studies with metal chelators and tyrosyl radical scavengers are consistent with a more accessible dimetal binding/radical site and a lower affinity for Fe2+ in EBV R2 than in Escherichia coli R2. Comparison with previous studies of RNR R2s from mouse, bacteria, and herpes viruses, demonstrates that finely tuned electronic properties of the radical exist within the same RNR R2 Ia class

Neuroprotective effect of small heat shock protein, Hsp27, after acute and chronic alcohol administration

Alcohol induces degeneration of neurons and inhibits neurogenesis in the brain. Small heat shock proteins are able to protect neurons in cerebral ischemia and oxidative stress. In this study, we investigated the neuroprotective effect of small heat shock protein, Hsp27, after acute and chronic ethanol administrations using transgenic mice overexpressing the human Hsp27 protein. Transgenic mice and wild-type littermates were injected with 2 g/kg ethanol intraperitoneally, and then motor coordination and muscle strength were analyzed using different behavioral tests, such as footprint analysis, balance beam, and inverted screen tests. Ethanol-injected transgenic mice showed similar footprints to control saline-injected mice, did not fall of the beam, and were able to climb to the top of the inverted screen, while wild-type mice showed ataxia and incoordination after ethanol injection. The effect of Hsp27 on chronic ethanol consumption was also investigated. Drinking water of mice was replaced by a 20% ethanol solution for 5 weeks, and then brain sections were stained with Fluoro Jade C staining. We found significantly lesser amount of degenerating neurons in the brain of ethanol-drinking transgenic mice compared to wild-type mice. We conclude that Hsp27 can protect neurons against the acute and chronic toxic effects of ethanol