Domain-based small molecule binding site annotation

BACKGROUND: Accurate small molecule binding site information for a protein can facilitate studies in drug docking, drug discovery and function prediction, but small molecule binding site protein sequence annotation is sparse. The Small Molecule Interaction Database (SMID), a database of protein domain-small molecule interactions, was created using structural data from the Protein Data Bank (PDB). More importantly it provides a means to predict small molecule binding sites on proteins with a known or unknown structure and unlike prior approaches, removes large numbers of false positive hits arising from transitive alignment errors, non-biologically significant small molecules and crystallographic conditions that overpredict ion binding sites. DESCRIPTION: Using a set of co-crystallized protein-small molecule structures as a starting point, SMID interactions were generated by identifying protein domains that bind to small molecules, using NCBI's Reverse Position Specific BLAST (RPS-BLAST) algorithm. SMID records are available for viewing at . The SMID-BLAST tool provides accurate transitive annotation of small-molecule binding sites for proteins not found in the PDB. Given a protein sequence, SMID-BLAST identifies domains using RPS-BLAST and then lists potential small molecule ligands based on SMID records, as well as their aligned binding sites. A heuristic ligand score is calculated based on E-value, ligand residue identity and domain entropy to assign a level of confidence to hits found. SMID-BLAST predictions were validated against a set of 793 experimental small molecule interactions from the PDB, of which 472 (60%) of predicted interactions identically matched the experimental small molecule and of these, 344 had greater than 80% of the binding site residues correctly identified. Further, we estimate that 45% of predictions which were not observed in the PDB validation set may be true positives. CONCLUSION: By focusing on protein domain-small molecule interactions, SMID is able to cluster similar interactions and detect subtle binding patterns that would not otherwise be obvious. Using SMID-BLAST, small molecule targets can be predicted for any protein sequence, with the only limitation being that the small molecule must exist in the PDB. Validation results and specific examples within illustrate that SMID-BLAST has a high degree of accuracy in terms of predicting both the small molecule ligand and binding site residue positions for a query protein

Comparison of I-131 Radioimmunotherapy Tumor Dosimetry: Unit Density Sphere Model Versus Patient-Specific Monte Carlo Calculations

High computational requirements restrict the use of Monte Carlo algorithms for dose estimation in a clinical setting, despite the fact that they are considered more accurate than traditional methods. The goal of this study was to compare mean tumor absorbed dose estimates using the unit density sphere model incorporated in OLINDA with previously reported dose estimates from Monte Carlo simulations using the dose planning method (DPMMC) particle transport algorithm. The dataset (57 tumors, 19 lymphoma patients who underwent SPECT/CT imaging during I-131 radioimmunotherapy) included tumors of varying size, shape, and contrast. OLINDA calculations were first carried out using the baseline tumor volume and residence time from SPECT/CT imaging during 6 days post-tracer and 8 days post-therapy. Next, the OLINDA calculation was split over multiple time periods and summed to get the total dose, which accounted for the changes in tumor size. Results from the second calculation were compared with results determined by coupling SPECT/CT images with DPM Monte Carlo algorithms. Results from the OLINDA calculation accounting for changes in tumor size were almost always higher (median 22%, range -1%-68%) than the results from OLINDA using the baseline tumor volume because of tumor shrinkage. There was good agreement (median -5%, range -13%-2%) between the OLINDA results and the self-dose component from Monte Carlo calculations, indicating that tumor shape effects are a minor source of error when using the sphere model. However, because the sphere model ignores cross-irradiation, the OLINDA calculation significantly underestimated (median 14%, range 2%-31%) the total tumor absorbed dose compared with Monte Carlo. These results show that when the quantity of interest is the mean tumor absorbed dose, the unit density sphere model is a practical alternative to Monte Carlo for some applications. For applications requiring higher accuracy, computer-intensive Monte Carlo calculation is needed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90433/1/cbr-2E2011-2E0965.pd

Hotline sessions presented at the American College of Cardiology Congress 2009

The article summarizes the results of clinical trials in the field of cardiovascular medicine, which were presented during the Hotline Sessions at the annual meeting of the American College of Cardiology in Orlando, USA, from 28th March to 31st March 2009. The data were presented by leading experts in the field with relevant positions within the trials. Unpublished reports should be considered as preliminary data as the analysis may change in the final publications. The summaries presented in the manuscript were generated from the oral presentations and provide the readers with the comprehensive information on the results of the latest clinical trials in cardiovascular medicine

Current concepts in periodontal bioengineering

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73112/1/j.1601-6343.2005.00352.x.pd

Pressure RElieving Support SUrfaces: a Randomised Evaluation 2 (PRESSURE 2): study protocol for a randomised controlled trial

Background Pressure ulcers represent a major burden to patients, carers and the healthcare system, affecting approximately 1 in 17 hospital and 1 in 20 community patients. They impact greatly on an individual’s functional status and health-related quality of life. The mainstay of pressure ulcer prevention practice is the provision of pressure redistribution support surfaces and patient repositioning. The aim of the PRESSURE 2 study is to compare the two main mattress types utilised within the NHS: high-specification foam and alternating pressure mattresses, in the prevention of pressure ulcers. Methods/Design PRESSURE 2 is a multicentre, open-label, randomised, double triangular, group sequential, parallel group trial. A maximum of 2954 ‘high-risk’ patients with evidence of acute illness will be randomised on a 1:1 basis to receive either a high-specification foam mattress or alternating-pressure mattress in conjunction with an electric profiling bed frame. The primary objective of the trial is to compare mattresses in terms of the time to developing a new Category 2 or above pressure ulcer by 30 days post end of treatment phase. Secondary endpoints include time to developing new Category 1 and 3 or above pressure ulcers, time to healing of pre-existing Category 2 pressure ulcers, health-related quality of life, cost-effectiveness, incidence of mattress change and safety. Validation objectives are to determine the responsiveness of the Pressure Ulcer Quality of Life-Prevention instrument and the feasibility of having a blinded endpoint assessment using photography. The trial will have a maximum of three planned analyses with unequally spaced reviews at event-driven coherent cut-points. The futility boundaries are constructed as non-binding to allow a decision for stopping early to be overruled by the Data Monitoring and Ethics Committee. Discussion The double triangular, group sequential design of the PRESSURE 2 trial will provide an efficient design through the possibility of early stopping for demonstrating either superiority, inferiority of mattresses or futility of the trial. The trial optimises the potential for producing robust clinical evidence on the effectiveness of two commonly used mattresses in clinical practice earlier than in a conventional design

Egg Production in a Coastal Seabird, the Glaucous-Winged Gull (Larus glaucescens), Declines during the Last Century

Seabirds integrate information about oceanic ecosystems across time and space, and are considered sensitive indicators of marine conditions. To assess whether hypothesized long-term foodweb changes such as forage fish declines may be reflected in a consumer's life history traits over time, I used meta-regression to evaluate multi-decadal changes in aspects of egg production in the glaucous-winged gull (Larus glaucescens), a common coastal bird. Study data were derived from literature searches of published papers and unpublished historical accounts, museum egg collections, and modern field studies, with inclusion criteria based on data quality and geographic area of the original study. Combined historical and modern data showed that gull egg size declined at an average of 0.04 cc y−1 from 1902 (108 y), equivalent to a decline of 5% of mean egg volume, while clutch size decreased over 48 y from a mean of 2.82 eggs per clutch in 1962 to 2.25 in 2009. There was a negative relationship between lay date and mean clutch size in a given year, with smaller clutches occurring in years where egg laying commenced later. Lay date itself advanced over time, with commencement of laying presently (2008–2010) 7 d later than in previous studies (1959–1986). This study demonstrates that glaucous-winged gull investment in egg production has declined significantly over the past ∼50–100 y, with such changes potentially contributing to recent population declines. Though gulls are generalist feeders that should readily be able to buffer themselves against food web changes, they are likely nutritionally constrained during the early breeding period, when egg production requirements are ideally met by consumption of high-quality prey such as forage fish. This study's results suggest a possible decline in the availability of such prey, and the incremental long-term impoverishment of a coastal marine ecosystem bordering one of North America's rapidly growing urban areas

Predicting the seasonal evolution of southern African summer precipitation in the DePreSys3 prediction system

We assess the ability of the DePreSys3 prediction system to predict austral summer precipitation (DJF) over southern Africa, defined as the African continent south of 15°S. DePresys3 is a high resolution prediction system (at a horizontal resolution of ~ 60 km in the atmosphere in mid-latitudes and of the quarter degree in the Ocean) and spans the long period 1959–2016. We find skill in predicting interannual precipitation variability, relative to a long-term trend; the anomaly correlation skill score over southern Africa is greater than 0.45 for the first summer (i.e. lead month 2–4), and 0.37 over Mozambique, Zimbabwe and Zambia for the second summer (i.e. lead month 14–16). The skill is related to the successful prediction of the El-Nino Southern Oscillation (ENSO), and the successful simulation of ENSO teleconnections to southern Africa. However, overall skill is sensitive to the inclusion of strong La-Nina events and also appears to change with forecast epoch. For example, the skill in predicting precipitation over Mozambique is significantly larger for the first summer in the 1990–2016 period, compared to the 1959–1985 period. The difference in skill in predicting interannual precipitation variability over southern Africa in different epochs is consistent with a change in the strength of the observed teleconnections of ENSO. After 1990, and consistent with the increased skill, the observed impact of ENSO appears to strengthen over west Mozambique, in association with changes in ENSO related atmospheric convergence anomalies. However, these apparent changes in teleconnections are not captured by the ensemble-mean predictions using DePreSys3. The changes in the ENSO teleconnection are consistent with a warming over the Indian Ocean and modulation of ENSO properties between the different epochs, but may also be associated with unpredictable atmospheric variability