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

A web-based group course intervention for 15-25-year-olds whose parents have substance use problems or mental illness: study protocol for a randomized controlled trial

Abstract Background Depending on the definitions used, between 5 and 20 % of all Swedish children grow up with at least one parent suffering from alcohol problems, while 6 % have at least one parent who has received inpatient psychiatric care, conditions that may affect the children negatively. Nine out of ten Swedish municipalities therefore provide support resources, but less than 2 % of these children are reached by such support. Delivering intervention programs via the Internet is a promising strategy. However, web-based programs targeting this at-risk group of children are scarce. We have previously developed a 1.5-h-long web-based self-help program, Alcohol & Coping, which appears to be effective with regards to adolescents’ own alcohol consumption. However, there is a need for a more intense program, and therefore we adapted Kopstoring, a comprehensive Dutch web-based psycho-educative prevention program, to fit the Swedish context. The purpose of the program, which in Swedish has been called Grubbel, is to strengthen protective factors, such as coping skills and psychological well-being, prevent the development of psychological disorders, and reduce alcohol consumption. Methods/design The aim of the current study is to evaluate the effectiveness of Grubbel, which targets 15–25-year-olds whose parents have substance use problems and/or mental illness. Specific research questions relate to the participants’ own coping strategies, mental health status and substance use. The study was initiated in the spring of 2016 and uses a two-armed RCT design. Participants will be recruited via social media and also through existing agencies that provide support to this target group. The assessment will consist of a baseline measurement (t0) and three follow-ups after six (t1), 12 (t2), and 24 months (t3). Measures include YSR, CES-DC, Ladder of Life, Brief COPE, AUDIT-C, and WHOQOL-BREF. Discussion Studies have revealed that the majority of children whose parents have substance use or mental health problems are not reached by the existing support. Thus, there is an urgent need to develop, implement, and evaluate novel intervention programs and disseminate successful programs to a broader audience. This study, investigating the effects of a web-based intervention, therefore makes an important contribution to this field of research. Trial registration ISRCTN10099247 . Retrospectively registered on August 31, 2016