Portuguese and Brazilian stock market integration : a non-linear and detrended approach

Besides the historical heritage that Portugal and Brazil share, the last two decades have also shown an increase in some economic indicators, such as the percentage of imports/exports and foreign direct investment. In order to take advantage of all the benefits, the countries should increase economic integration, stock market integration being one of the possibilities. In this context, this paper analyses stock market integration between these two countries, using non-linear methodologies: detrended fluctuation analysis, detrended cross-correlation analysis and detrended moving-average cross-correlation analysis. Using the main stock indexes, and splitting the sample in six different periods, the main conclusion is that integration between these two countries increased over time. However, since 2013, the integration pattern has decreased, with the economic crisis both countries suffered being the main factor.info:eu-repo/semantics/publishedVersio

Complementarity Between a Docking and a High-Throughput Screen in Discovering New Cruzain Inhibitors†

Virtual and high-throughput screens (HTS) should have complementary strengths and weaknesses, but studies that prospectively and comprehensively compare them are rare. We undertook a parallel docking and HTS screen of 197861 compounds against cruzain, a thiol protease target for Chagas disease, looking for reversible, competitive inhibitors. On workup, 99 % of the hits were eliminated as false positives, yielding 146 well-behaved, competitive ligands. These fell into five chemotypes: two were prioritized by scoring among the top 0.1 % of the docking-ranked library, two were prioritized by behavior in the HTS and by clustering, and one chemotype was prioritized by both approaches. Determination of an inhibitor/cruzain crystal structure and comparison of the high-scoring docking hits to experiment illuminated the origins of docking false-negatives and false-positives. Prioritizing molecules that are both predicted by docking and are HTS-active yields well-behaved molecules, relatively unobscured by the false-positives to which both techniques are individually prone

A statistical framework to evaluate virtual screening

<p>Abstract</p> <p>Background</p> <p>Receiver operating characteristic (ROC) curve is widely used to evaluate virtual screening (VS) studies. However, the method fails to address the "early recognition" problem specific to VS. Although many other metrics, such as RIE, BEDROC, and pROC that emphasize "early recognition" have been proposed, there are no rigorous statistical guidelines for determining the thresholds and performing significance tests. Also no comparisons have been made between these metrics under a statistical framework to better understand their performances.</p> <p>Results</p> <p>We have proposed a statistical framework to evaluate VS studies by which the threshold to determine whether a ranking method is better than random ranking can be derived by bootstrap simulations and 2 ranking methods can be compared by permutation test. We found that different metrics emphasize "early recognition" differently. BEDROC and RIE are 2 statistically equivalent metrics. Our newly proposed metric SLR is superior to pROC. Through extensive simulations, we observed a "seesaw effect" – overemphasizing early recognition reduces the statistical power of a metric to detect true early recognitions.</p> <p>Conclusion</p> <p>The statistical framework developed and tested by us is applicable to any other metric as well, even if their exact distribution is unknown. Under this framework, a threshold can be easily selected according to a pre-specified type I error rate and statistical comparisons between 2 ranking methods becomes possible. The theoretical null distribution of SLR metric is available so that the threshold of SLR can be exactly determined without resorting to bootstrap simulations, which makes it easy to use in practical virtual screening studies.</p

Automated Docking Screens: A Feasibility Study

Molecular docking is themost practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCKBlaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCKBlaster recapitulates the crystal ligand pose within 2 A ̊ rmsd 50-60 % of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5 % of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5 % of 100 property-matched decoys while also posing within 2 A ̊ rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available a

WISDOM-II: Screening against multiple targets implicated in malaria using computational grid infrastructures

<p>Abstract</p> <p>Background</p> <p>Despite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the <it>Plasmodium </it>parasite, some are promising targets to carry out rational drug discovery.</p> <p>Motivation</p> <p>Recent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR), and on a new promising one, glutathione-S-transferase.</p> <p>Methods</p> <p>In silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate <it>in silico </it>docking and in information technology to design and operate large scale grid infrastructures.</p> <p>Results</p> <p>On the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, <it>In vitro </it>results are underway for all the targets against which screening is performed.</p> <p>Conclusion</p> <p>The current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software on computational grids in finding hits against three different targets (PfGST, PfDHFR, PvDHFR (wild type and mutant forms) implicated in malaria. Grid-enabled virtual screening approach is proposed to produce focus compound libraries for other biological targets relevant to fight the infectious diseases of the developing world.</p

Diagnosing mucopolysaccharidosis IVA

Mucopolysaccharidosis IVA (MPS IVA; Morquio A syndrome) is an autosomal recessive lysosomal storage disorder resulting from a deficiency of N-acetylgalactosamine-6-sulfate sulfatase (GALNS) activity. Diagnosis can be challenging and requires agreement of clinical, radiographic, and laboratory findings. A group of biochemical genetics laboratory directors and clinicians involved in the diagnosis of MPS IVA, convened by BioMarin Pharmaceutical Inc., met to develop recommendations for diagnosis. The following conclusions were reached. Due to the wide variation and subtleties of radiographic findings, imaging of multiple body regions is recommended. Urinary glycosaminoglycan analysis is particularly problematic for MPS IVA and it is strongly recommended to proceed to enzyme activity testing even if urine appears normal when there is clinical suspicion of MPS IVA. Enzyme activity testing of GALNS is essential in diagnosing MPS IVA. Additional analyses to confirm sample integrity and rule out MPS IVB, multiple sulfatase deficiency, and mucolipidoses types II/III are critical as part of enzyme activity testing. Leukocytes or cultured dermal fibroblasts are strongly recommended for enzyme activity testing to confirm screening results. Molecular testing may also be used to confirm the diagnosis in many patients. However, two known or probable causative mutations may not be identified in all cases of MPS IVA. A diagnostic testing algorithm is presented which attempts to streamline this complex testing process

Determination of sin2 θeff w using jet charge measurements in hadronic Z decays

The electroweak mixing angle is determined with high precision from measurements of the mean difference between forward and backward hemisphere charges in hadronic decays of the Z. A data sample of 2.5 million hadronic Z decays recorded over the period 1990 to 1994 in the ALEPH detector at LEP is used. The mean charge separation between event hemispheres containing the original quark and antiquark is measured for bb̄ and cc̄ events in subsamples selected by their long lifetimes or using fast D*'s. The corresponding average charge separation for light quarks is measured in an inclusive sample from the anticorrelation between charges of opposite hemispheres and agrees with predictions of hadronisation models with a precision of 2%. It is shown that differences between light quark charge separations and the measured average can be determined using hadronisation models, with systematic uncertainties constrained by measurements of inclusive production of kaons, protons and A's. The separations are used to measure the electroweak mixing angle precisely as sin2 θeff w = 0.2322 ± 0.0008(exp. stat.) ±0.0007(exp. syst.) ± 0.0008(sep.). The first two errors are due to purely experimental sources whereas the third stems from uncertainties in the quark charge separations