Predicting a small molecule-kinase interaction map: A machine learning approach

<p>Abstract</p> <p>Background</p> <p>We present a machine learning approach to the problem of protein ligand interaction prediction. We focus on a set of binding data obtained from 113 different protein kinases and 20 inhibitors. It was attained through ATP site-dependent binding competition assays and constitutes the first available dataset of this kind. We extract information about the investigated molecules from various data sources to obtain an informative set of features.</p> <p>Results</p> <p>A Support Vector Machine (SVM) as well as a decision tree algorithm (C5/See5) is used to learn models based on the available features which in turn can be used for the classification of new kinase-inhibitor pair test instances. We evaluate our approach using different feature sets and parameter settings for the employed classifiers. Moreover, the paper introduces a new way of evaluating predictions in such a setting, where different amounts of information about the binding partners can be assumed to be available for training. Results on an external test set are also provided.</p> <p>Conclusions</p> <p>In most of the cases, the presented approach clearly outperforms the baseline methods used for comparison. Experimental results indicate that the applied machine learning methods are able to detect a signal in the data and predict binding affinity to some extent. For SVMs, the binding prediction can be improved significantly by using features that describe the active site of a kinase. For C5, besides diversity in the feature set, alignment scores of conserved regions turned out to be very useful.</p

The Priority position paper: protecting Europe's food chain from prions

International audienceBovine spongiform encephalopathy (BSE) created a global European crisis in the 1980s and 90s, with very serious health and economic implications. Classical BSE now appears to be under control, to a great extent as a result of a global research effort that identified the sources of prions in meat and bone meal (MBM) and developed new animal-testing tools that guided policy. Priority ( www.prionpriority.eu ) was a European Union (EU) Framework Program 7 (FP7)-funded project through which 21 European research institutions and small and medium enterprises (SMEs) joined efforts between 2009 and 2014, to conduct coordinated basic and applied research on prions and prion diseases. At the end of the project, the Priority consortium drafted a position paper ( www.prionpriority.eu/Priority position paper) with its main conclusions. In the present opinion paper, we summarize these conclusions. With respect to the issue of re-introducing ruminant protein into the feed-chain, our opinion is that sustaining an absolute ban on feeding ruminant protein to ruminants is essential. In particular, the spread and impact of non-classical forms of scrapie and BSE in ruminants is not fully understood and the risks cannot be estimated. Atypical prion agents will probably continue to represent the dominant form of prion diseases in the near future in Europe. Atypical L-type BSE has clear zoonotic potential, as demonstrated in experimental models. Similarly, there are now data indicating that the atypical scrapie agent can cross various species barriers. More epidemiological data from large cohorts are necessary to reach any conclusion on the impact of its transmissibility on public health. Re-evaluations of safety precautions may become necessary depending on the outcome of these studies. Intensified searching for molecular determinants of the species barrier is recommended, since this barrier is key for important policy areas and risk assessment. Understanding the structural basis for strains and the basis for adaptation of a strain to a new host will require continued fundamental research, also needed to understand mechanisms of prion transmission, replication and how they cause nervous system dysfunction and death. Early detection of prion infection, ideally at a preclinical stage, also remains crucial for development of effective treatment strategies

Estimators of the asymptotic variance of stationary point processes - a comparison

summary:We investigate estimators of the asymptotic variance $\sigma^2$ of a $d$–dimensional stationary point process $\Psi$ which can be observed in convex and compact sampling window $W_n=n\, W$. Asymptotic variance of $\Psi$ is defined by the asymptotic relation ${Var}(\Psi(W_n)) \sim \sigma^2 |W_n|$ (as $n \to \infty$) and its existence is guaranteed whenever the corresponding reduced covariance measure $\gamma^{(2)}_{{\rm red}}(\cdot)$ has finite total variation. The three estimators discussed in the paper are the kernel estimator, the estimator based on the second order intesity of the point process and the subsampling estimator. We study the mean square consistency of the estimators. Since the expressions for the variance of the estimators are not available in closed form and depend on higher order moment measures of the point process, only the bias of the estimators can be compared theoretically. The second part of the paper is therefore devoted to a simulation study which compares the efficiency of the estimators by means of the mean squared error and for several clustered and repulsive point processes observed on middle-sized windows

The potential of PAI-1 expression in needle biopsies as a predictive marker for prostate cancer

The relative abundance of urokinase plasminogen activator (uPA) and plasminogen activator inhibitor type-1 (PAI-1) in transurethral resections of the prostate (TURP) has been shown to correlate with disease state. The objective of this study was to assay for uPA and PAI-1 in prostate needle biopsies, and to test their potential as predictive markers for prostate cancer (PCa). uPA and PAI-1 levels were determined for 111 patients (55 PCa; 56 benign prostatic hyperplasia (BPH)), using the FEMTELLE enzyme-linked immunosorbent (ELISA) assay. The PAI-1 concentrations for PCa and BPH patients differed significantly (p = 0.0403) and a level of ≥ 4.5 ng/mg protein in men 60 years and older appears to be predictive of PCa, with a sensitivity of 63%. uPA plays a minor role as a potential marker in biopsy tissue, a feature noted in our recent TURP tissue studies, and elsewhere. The potential utility of the uPA/PAI-1 ratio as a predictor of prostate disease, as previously suggested for TURP tissue, is not apparent in needle biopsy tissue. PAI-1 concentration in prostate biopsies could be a candidate marker for distinguishing between PCa and BPH in older patients

C-ITS Relevant Critical Vehicle-to-Vehicle Accident Scenarios for Accident Analysis

The relevance of scientific investigations, whether simulative or empirical, is strongly related to the environment used and the scenarios associated with it. Within the field of cooperative intelligent transport systems, use-cases are defined to describe the benefits of applications. This has already been conducted in the available safety-relevant Day 1 applications longitudinal and intersection collision risk warning through the respective technical specifications. However, the relevance of traffic scenarios is always a function of accident severity and frequency of a retrospective consideration of accident databases. In this study, vehicle-to-vehicle scenarios with high frequency and/or severe personal injuries are therefore determined with the help of the CISS database and linked to the use-cases of the safety-relevant Day 1 applications. The relevance of the scenarios thus results on the one hand from the classical parameters of retrospective accident analysis and on the other hand from the coverage by the named vehicle-to-x applications. As a result, accident scenarios with oncoming vehicles are the most relevant scenarios for investigations with cooperative intelligent transport systems. In addition, high coverage of the most critical scenarios within the use-cases of longitudinal and intersection collision risk warning is already apparent

Ultra-sensitive detection of prion protein fibrils by flow cytometry in blood from cattle affected with bovine spongiform encephalopathy

<p>Abstract</p> <p>Background</p> <p>The definite diagnosis of prion diseases such as Creutzfeldt-Jakob disease (CJD) in humans or bovine spongiform encephalopathy (BSE) in cattle currently relies on the <it>post mortem </it>detection of the pathological form of the prion protein (PrP^Sc) in brain tissue. Infectivity studies indicate that PrP^Scmay also be present in body fluids, even at presymptomatic stages of the disease, albeit at concentrations well below the detection limits of currently available analytical methods.</p> <p>Results</p> <p>We developed a highly sensitive method for detecting prion protein aggregates that takes advantage of kinetic differences between seeded and unseeded polymerization of prion protein monomers. Detection of the aggregates was carried out by flow cytometry. In the presence of prion seeds, the association of labelled recombinant PrP monomers in plasma and serum proceeds much more efficiently than in the absence of seeds. In a diagnostic model system, synthetic PrP aggregates were detected down to a concentration of approximately 10^-8nM [0.24 fg/ml]. A specific signal was detected in six out of six available serum samples from BSE-positive cattle.</p> <p>Conclusion</p> <p>We have developed a method based on seed-dependent PrP fibril formation that shows promising results in differentiating a small number of BSE-positive serum samples from healthy controls. This method may provide the basis for an <it>ante mortem </it>diagnostic test for prion diseases.</p