The HP1 Homolog Rhino Anchors a Nuclear Complex that Suppresses piRNA Precursor Splicing

SummarypiRNAs guide an adaptive genome defense system that silences transposons during germline development. The Drosophila HP1 homolog Rhino is required for germline piRNA production. We show that Rhino binds specifically to the heterochromatic clusters that produce piRNA precursors, and that binding directly correlates with piRNA production. Rhino colocalizes to germline nuclear foci with Rai1/DXO-related protein Cuff and the DEAD box protein UAP56, which are also required for germline piRNA production. RNA sequencing indicates that most cluster transcripts are not spliced and that rhino, cuff, and uap56 mutations increase expression of spliced cluster transcripts over 100-fold. LacI::Rhino fusion protein binding suppresses splicing of a reporter transgene and is sufficient to trigger piRNA production from a trans combination of sense and antisense reporters. We therefore propose that Rhino anchors a nuclear complex that suppresses cluster transcript splicing and speculate that stalled splicing differentiates piRNA precursors from mRNAs

Reconciling disparate prevalence rates of PTSD in large samples of US male Vietnam veterans and their controls

BACKGROUND: Two large independent studies funded by the US government have assessed the impact of the Vietnam War on the prevalence of PTSD in US veterans. The National Vietnam Veterans Readjustment Study (NVVRS) estimated the current PTSD prevalence to be 15.2% while the Vietnam Experience Study (VES) estimated the prevalence to be 2.2%. We compared alternative criteria for estimating the prevalence of PTSD using the NVVRS and VES public use data sets collected more than 10 years after the United States withdrew troops from Vietnam. METHODS: We applied uniform diagnostic procedures to the male veterans from the NVVRS and VES to estimate PTSD prevalences based on varying criteria including one-month and lifetime prevalence estimates, combat and non-combat prevalence estimates, and prevalence estimates using both single and multiple indicator models. RESULTS: Using a narrow and specific set of criteria, we derived current prevalence estimates for combat-related PTSD of 2.5% and 2.9% for the VES and the NVVRS, respectively. Using a more broad and sensitive set of criteria, we derived current prevalence estimates for combat-related PTSD of 12.2% and 15.8% for the VES and NVVRS, respectively. CONCLUSION: When comparable methods were applied to available data we reconciled disparate results and estimated similar current prevalences for both narrow and broad definitions of combat-related diagnoses of PTSD

Characterization of the thermal and photoinduced reactions of photochromic spiropyrans in aqueous solution

Six water-soluble spiropyran derivatives have been characterized with respect to the thermal and photoinduced reactions over a broad pH-interval. A comprehensive kinetic model was formulated including the spiro- and the merocyanine isomers, the respective protonated forms, and the hydrolysis products. The experimental studies on the hydrolysis reaction mechanism were supplemented by calculations using quantum mechanical (QM) models employing density functional theory. The results show that (1) the substitution pattern dramatically influences the pKa-values of the protonated forms as well as the rates of the thermal isomerization reactions, (2) water is the nucleophile in the hydrolysis reaction around neutral pH, (3) the phenolate oxygen of the merocyanine form plays a key role in the hydrolysis reaction. Hence, the nonprotonated merocyanine isomer is susceptible to hydrolysis, whereas the corresponding protonated form is stable toward hydrolytic degradation

Scoring docking conformations using predicted protein interfaces

BACKGROUND: Since proteins function by interacting with other molecules, analysis of protein-protein interactions is essential for comprehending biological processes. Whereas understanding of atomic interactions within a complex is especially useful for drug design, limitations of experimental techniques have restricted their practical use. Despite progress in docking predictions, there is still room for improvement. In this study, we contribute to this topic by proposing T-PioDock, a framework for detection of a native-like docked complex 3D structure. T-PioDock supports the identification of near-native conformations from 3D models that docking software produced by scoring those models using binding interfaces predicted by the interface predictor, Template based Protein Interface Prediction (T-PIP). RESULTS: First, exhaustive evaluation of interface predictors demonstrates that T-PIP, whose predictions are customised to target complexity, is a state-of-the-art method. Second, comparative study between T-PioDock and other state-of-the-art scoring methods establishes T-PioDock as the best performing approach. Moreover, there is good correlation between T-PioDock performance and quality of docking models, which suggests that progress in docking will lead to even better results at recognising near-native conformations. CONCLUSION: Accurate identification of near-native conformations remains a challenging task. Although availability of 3D complexes will benefit from template-based methods such as T-PioDock, we have identified specific limitations which need to be addressed. First, docking software are still not able to produce native like models for every target. Second, current interface predictors do not explicitly consider pairwise residue interactions between proteins and their interacting partners which leaves ambiguity when assessing quality of complex conformations

Community-Wide Assessment of Protein-Interface Modeling Suggests Improvements to Design Methodology

The CAPRI and CASP prediction experiments have demonstrated the power of community wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting there may be important physical chemistry missing in the energy calculations. 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the non-polar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were on average structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a non-binder