Migrating to Long-Read Sequencing for Clinical Routine BCR-ABL1 TKI Resistance Mutation Screening

Objective

The aim of this project was to implement long-read sequencing for BCR-ABL1 TKI resistance mutation screening in a clinical setting for patients undergoing treatment for chronic myeloid leukemia.

Materials and Methods

Processes were established for registering and transferring samples from the clinic to an academic sequencing facility for long-read sequencing. An automated analysis pipeline for detecting mutations was established, and an information system was implemented comprising features for data management, analysis and visualization. Clinical validation was performed by identifying BCR-ABL1 TKI resistance mutations by Sanger and long-read sequencing in parallel. The developed software is available as open source via GitHub at https://github.com/pharmbio/clamp.

Results

The information system enabled traceable transfer of samples from the clinic to the sequencing facility, robust and automated analysis of the long-read sequence data, and communication of results from sequence analysis in a reporting format that could be easily interpreted and acted upon by clinical experts. In a validation study, all 17 resistance mutations found by Sanger sequencing were also detected by long-read sequencing. An additional 16 mutations were found only by long-read sequencing, all of them with frequencies below the limit of detection for Sanger sequencing. The clonal distributions of co-existing mutations were automatically resolved through the long-read data analysis. After the implementation and validation, the clinical laboratory switched their routine protocol from using Sanger to long-read sequencing for this application.

Conclusions

Long-read sequencing delivers results with higher sensitivity compared to Sanger sequencing and enables earlier detection of emerging TKI resistance mutations. The developed processes, analysis workflow, and software components lower barriers for adoption and could be extended to other applications.

Predicting protein network topology clusters from chemical structure using deep learning

Comparing chemical structures to infer protein targets and functions is a common approach, but basing comparisons on chemical similarity alone can be misleading. Here we present a methodology for predicting target protein clusters using deep neural networks. The model is trained on clusters of compounds based on similarities calculated from combined compound-protein and protein-protein interaction data using a network topology approach. We compare several deep learning architectures including both convolutional and recurrent neural networks. The best performing method, the recurrent neural network architecture MolPMoFiT, achieved an F1 score approaching 0.9 on a held-out test set of 8907 compounds. In addition, in-depth analysis on a set of eleven well-studied chemical compounds with known functions showed that predictions were justifiable for all but one of the chemicals. Four of the compounds, similar in their molecular structure but with dissimilarities in their function, revealed advantages of our method compared to using chemical similarity.

Predicting target profiles with confidence as a service using docking scores

Background

Identifying and assessing ligand-target binding is a core component in early drug discovery as one or more unwanted interactions may be associated with safety issues.

Contributions

We present an open-source, extendable web service for predicting target profiles with confidence using machine learning for a panel of 7 targets, where models are trained on molecular docking scores from a large virtual library. The method uses conformal prediction to produce valid measures of prediction efficiency for a particular confidence level. The service also offers the possibility to dock chemical structures to the panel of targets with QuickVina on individual compound basis.

Results

The docking procedure and resulting models were validated by docking well-known inhibitors for each of the 7 targets using QuickVina. The model predictions showed comparable performance to molecular docking scores against an external validation set. The implementation as publicly available microservices on Kubernetes ensures resilience, scalability, and extensibility.

Rapid Increase in Carriage Rates of Enterobacteriaceae Producing Extended-Spectrum β-Lactamases in Healthy Preschool Children, Sweden

By collecting and analyzing diapers, we identified a >6-fold increase in carriage of extended-spectrum β-lactamase (ESBL)–producing Enterobacteriaceae for healthy preschool children in Sweden (p<0.0001). For 6 of the 50 participating preschools, the carriage rate was >40%. We analyzed samples from 334 children and found 56 containing >1 ESBL producer. The prevalence in the study population increased from 2.6% in 2010 to 16.8% in 2016 (p<0.0001), and for 6 of the 50 participating preschools, the carriage rate was >40%. Furthermore, 58% of the ESBL producers were multidrug resistant, and transmission of ESBL-producing and non–ESBL-producing strains was observed at several of the preschools. Toddlers appear to be major carriers of ESBL producers in Sweden.

Tracking the NGS revolution: managing life science research on shared high-performance computing clusters

Background

Next-generation sequencing (NGS) has transformed the life sciences, and many research groups are newly dependent upon computer clusters to store and analyze large datasets. This creates challenges for e-infrastructures accustomed to hosting computationally mature research in other sciences. Using data gathered from our own clusters at UPPMAX computing center at Uppsala University, Sweden, where core hour usage of ∼800 NGS and ∼200 non-NGS projects is now similar, we compare and contrast the growth, administrative burden, and cluster usage of NGS projects with projects from other sciences.

Results

The number of NGS projects has grown rapidly since 2010, with growth driven by entry of new research groups. Storage used by NGS projects has grown more rapidly since 2013 and is now limited by disk capacity. NGS users submit nearly twice as many support tickets per user, and 11 more tools are installed each month for NGS projects than for non-NGS projects. We developed usage and efficiency metrics and show that computing jobs for NGS projects use more RAM than non-NGS projects, are more variable in core usage, and rarely span multiple nodes. NGS jobs use booked resources less efficiently for a variety of reasons. Active monitoring can improve this somewhat.

Conclusions

Hosting NGS projects imposes a large administrative burden at UPPMAX due to large numbers of inexperienced users and diverse and rapidly evolving research areas. We provide a set of recommendations for e-infrastructures that host NGS research projects. We provide anonymized versions of our storage, job, and efficiency databases.

A confidence predictor for logD using conformal regression and a support-vector machine

Lipophilicity is a major determinant of ADMET properties and overall suitability of drug candidates. We have developed large-scale models to predict water–octanol distribution coefficient (logD) for chemical compounds, aiding drug discovery projects. Using ACD/logD data for 1.6 million compounds from the ChEMBL database, models are created and evaluated by a support-vector machine with a linear kernel using conformal prediction methodology, outputting prediction intervals at a specified confidence level. The resulting model shows a predictive ability of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {Q}^{2}=0.973$$\end{document}Q2=0.973 and with the best performing nonconformity measure having median prediction interval of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pm ~0.39$$\end{document}±0.39 log units at 80% confidence and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pm ~0.60$$\end{document}±0.60 log units at 90% confidence. The model is available as an online service via an OpenAPI interface, a web page with a molecular editor, and we also publish predictive values at 90% confidence level for 91 M PubChem structures in RDF format for download and as an URI resolver service.

Efficient iterative virtual screening with Apache Spark and conformal prediction

Background

Docking and scoring large libraries of ligands against target proteins forms the basis of structure-based virtual screening. The problem is trivially parallelizable, and calculations are generally carried out on computer clusters or on large workstations in a brute force manner, by docking and scoring all available ligands.

Contribution

In this study we propose a strategy that is based on iteratively docking a set of ligands to form a training set, training a ligand-based model on this set, and predicting the remainder of the ligands to exclude those predicted as ‘low-scoring’ ligands. Then, another set of ligands are docked, the model is retrained and the process is repeated until a certain model efficiency level is reached. Thereafter, the remaining ligands are docked or excluded based on this model. We use SVM and conformal prediction to deliver valid prediction intervals for ranking the predicted ligands, and Apache Spark to parallelize both the docking and the modeling.

Results

We show on 4 different targets that conformal prediction based virtual screening (CPVS) is able to reduce the number of docked molecules by 62.61% while retaining an accuracy for the top 30 hits of 94% on average and a speedup of 3.7. The implementation is available as open source via GitHub (https://github.com/laeeq80/spark-cpvs) and can be run on high-performance computers as well as on cloud resources.

Large-scale virtual screening on public cloud resources with Apache Spark

Background

Structure-based virtual screening is an in-silico method to screen a target receptor against a virtual molecular library. Applying docking-based screening to large molecular libraries can be computationally expensive, however it constitutes a trivially parallelizable task. Most of the available parallel implementations are based on message passing interface, relying on low failure rate hardware and fast network connection. Google’s MapReduce revolutionized large-scale analysis, enabling the processing of massive datasets on commodity hardware and cloud resources, providing transparent scalability and fault tolerance at the software level. Open source implementations of MapReduce include Apache Hadoop and the more recent Apache Spark.

Results

We developed a method to run existing docking-based screening software on distributed cloud resources, utilizing the MapReduce approach. We benchmarked our method, which is implemented in Apache Spark, docking a publicly available target receptor against \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim $$\end{document}∼2.2 M compounds. The performance experiments show a good parallel efficiency (87%) when running in a public cloud environment.

Conclusion

Our method enables parallel Structure-based virtual screening on public cloud resources or commodity computer clusters. The degree of scalability that we achieve allows for trying out our method on relatively small libraries first and then to scale to larger libraries. Our implementation is named Spark-VS and it is freely available as open source from GitHub (https://github.com/mcapuccini/spark-vs).Graphical abstract

Docking of Macrocycles: Comparing Rigid and Flexible Docking in Glide

In recent years, there has been an increased interest in using macrocyclic compounds for drug discovery and development. For docking of these commonly large and flexible compounds to be addressed, a screening and a validation set were assembled from the PDB consisting of 16 and 31 macrocycle-containing protein complexes, respectively. The macrocycles were docked in Glide by rigid docking of pregenerated conformational ensembles produced by the macrocycle conformational sampling method (MCS) in Schrödinger Release 2015-3 or by direct Glide flexible docking after performing ring-templating. The two protocols were compared to rigid docking of pregenerated conformational ensembles produced by an exhaustive Monte Carlo multiple minimum (MCMM) conformational search and a shorter MCMM conformational search (MCMM-short). The docking accuracy was evaluated and expressed as the RMSD between the heavy atoms of the ligand as found in the X-ray structure after refinement and the poses obtained by the docking protocols. The median RMSD values for top-scored poses of the screening set were 0.83, 0.80, 0.88, and 0.58 Å for MCMM, MCMM-short, MCS, and Glide flexible docking, respectively. There was no statistically significant difference in the performance between rigid docking of pregenerated conformations produced by the MCS and direct docking using Glide flexible docking. However, the flexible docking protocol was 2-times faster in docking the screening set compared to that of the MCS protocol. In a final study, the new Prime-MCS method was evaluated in Schrödinger Release 2016-3. This method is faster compared that of to MCS; however, the conformations generated were found to be suboptimal for rigid docking. Therefore, on the basis of timing, accuracy, and ease of set up, standard Glide flexible docking with prior ring-templating is recommended over current gold standard protocols using rigid docking of pregenerated conformational ensembles.

Large-scale ligand-based predictive modelling using support vector machines

The increasing size of datasets in drug discovery makes it challenging to build robust and accurate predictive models within a reasonable amount of time. In order to investigate the effect of dataset sizes on predictive performance and modelling time, ligand-based regression models were trained on open datasets of varying sizes of up to 1.2 million chemical structures. For modelling, two implementations of support vector machines (SVM) were used. Chemical structures were described by the signatures molecular descriptor. Results showed that for the larger datasets, the LIBLINEAR SVM implementation performed on par with the well-established libsvm with a radial basis function kernel, but with dramatically less time for model building even on modest computer resources. Using a non-linear kernel proved to be infeasible for large data sizes, even with substantial computational resources on a computer cluster. To deploy the resulting models, we extended the Bioclipse decision support framework to support models from LIBLINEAR and made our models of logD and solubility available from within Bioclipse.

N-Substituted pyrazole-3-carboxamides as inhibitors of human 15-lipoxygenase

High-throughput screening was used to find selective inhibitors of human 15-lipoxygenase-1 (15-LOX-1). One hit, a 1-benzoyl substituted pyrazole-3-carboxanilide (1a), was used as a starting point in a program to develop potent and selective 15-LOX-1 inhibitors.

3-Substituted pyrazoles and 4-substituted triazoles as inhibitors of human 15-lipoxygenase-1

Investigation of 1N-substituted pyrazole-3-carboxanilides as 15-lipoxygenase-1 (15-LOX-1) inhibitors demonstrated that the 1N-substituent was not essential for activity or selectivity. Additional halogen substituents on the pyrazole ring, however, increased activity. Further development led to triazole-4-carboxanilides and 2-(3-pyrazolyl) benzoxazoles, which are potent and selective 15-LOX-1 inhibitors.

Automated QuantMap for rapid quantitative molecular network topology analysis

Summary: The previously disclosed QuantMap method for grouping chemicals by biological activity used online services for much of the data gathering and some of the numerical analysis. The present work attempts to streamline this process by using local copies of the databases and in-house analysis. Using computational methods similar or identical to those used in the previous work, a qualitatively equivalent result was found in just a few seconds on the same dataset (collection of 18 drugs). We use the user-friendly Galaxy framework to enable users to analyze their own datasets. Hopefully, this will make the QuantMap method more practical and accessible and help achieve its goals to provide substantial assistance to drug repositioning, pharmacology evaluation and toxicology risk assessment.

Availability:http://galaxy.predpharmtox.org

Contact:mats.gustafsson@medsci.uu.se or ola.spjuth@farmbio.uu.se

Supplementary information:Supplementary data are available at Bioinformatics online.

Development of a fluorescent intensity assay amenable for high-throughput screening for determining 15-lipoxygenase activity

15-Lipoxygenase-1 catalyzes the introduction of molecular oxygen into polyunsaturated fatty acids to form a lipid hydroperoxide. The authors have developed an assay for the detection of lipid hydroperoxides formed by human 15-lipoxygenase (15-LO) in enzyme or cellular assays using either a 96-well or a 384-well format. The assays described take advantage of the ability of lipid hydroperoxides to oxidize nonfluorescent diphenyl-1-pyrenylphosphine (DPPP) to a fluorescent phosphine oxide. Oxidation of DPPP yields a fluorescent compound, which is not sensitive to temperature and is stable for more than 2 h. The assay is sensitive toward inhibition and robust with a Z' value of 0.79 and 0.4 in a 96- and 384-well format, respectively, and thus amenable for high-throughput screening. The utility of DPPP as a marker for 15-lipoxygenase activity was demonstrated with both enzyme- and cell-based assays for the identification of hits and to determine potency by IC(50) determinations.

Improved CoMFA Modeling by Optimization of Settings

The possibility of improving the predictive ability of comparative molecular field analysis (CoMFA) by settings optimization has been evaluated to show that CoMFA predictive ability can be improved. Ten different CoMFA settings are evaluated, producing a total of 6120 models. This method has been applied to nine different data sets, including the widely used benchmark steroid data set, as well as eight other data sets proposed as QSAR benchmarking data sets by Sutherland et al. (J. Med. Chem. 2004, 47, 5541-5554). All data sets have been studied using training and test sets to allow for both internal (q(2)) and external (r(2)(pred)) predictive ability assessment. CoMFA settings optimization was successful in developing models with improved q(2) and r(2)(pred) as compared to default CoMFA modeling. Optimized CoMFA is compared with comparative molecular similarity indices analysis (CoMSIA) and holographic quantitative structure-activity relationship (HQSAR) models and found to consistently produce models with improved or equivalent q(2) and r(2)(pred). The ability of settings optimization to improve model predictive ability has been validated using both internal and external predictions, and the risk of chance correlation has been evaluated using response variable randomization tests.

Cyclic sulfamide HIV-1 protease inhibitors, with sidechains spanning from P2/P2' to P1/P1'

Previous studies of HIV protease inhibitors have shown that it is possible to elongate the P1/P1' sidechains to reach the S3/S3' binding sites. By analogy, we expected that it would be possible to design inhibitors reaching between the S1/S1' and S2/S2' binding sites. Molecular modeling suggested that this could be achieved with appropriate ortho-substitution of the P2/P2' benzyl groups in our cyclic sulfamide inhibitors. Four different spacer groups were investigated. The compounds were smoothly prepared from tartaric acid in five steps and exhibit low to moderate activity, the most potent inhibitor possessing a Ki value of 0.53 microM.

High-speed optimization of inhibitors of the malarial proteases plasmepsin I and II

Four focused libraries targeted for inhibition of the malarial proteases plasmepsin I and II were designed, synthesized, purified, and screened. Selected carboxylic acids and organometallic reactants with diverse physical properties were attached to the hydroxylethylamine scaffold in the P3 and P1' positions to furnish inhibitors with highly improved activity. The concept of controlled and sequential microwave heating was employed for rapid library generation. This combinatorial optimization protocol afforded plasmepsin inhibitors not only with K(i) values in the low nanomolar range, but also with high selectivity versus the human protease cathepsin D. With this class of inhibitory agents, modifications of the P1' substituents resulted in the largest impact on the plasmepsin/cathepsin D selectivity.

Optimization of P1-P3 groups in symmetric and asymmetric HIV-1 protease inhibitors

HIV-1 protease is an important target for treatment of AIDS, and efficient drugs have been developed. However, the resistance and negative side effects of the current drugs has necessitated the development of new compounds with different binding patterns. In this study, nine C-terminally duplicated HIV-1 protease inhibitors were cocrystallised with the enzyme, the crystal structures analysed at 1.8-2.3 A resolution, and the inhibitory activity of the compounds characterized in order to evaluate the effects of the individual modifications. These compounds comprise two central hydroxy groups that mimic the geminal hydroxy groups of a cleavage-reaction intermediate. One of the hydroxy groups is located between the delta-oxygen atoms of the two catalytic aspartic acid residues, and the other in the gauche position relative to the first. The asymmetric binding of the two central inhibitory hydroxyls induced a small deviation from exact C2 symmetry in the whole enzyme-inhibitor complex. The study shows that the protease molecule could accommodate its structure to different sizes of the P2/P2' groups. The structural alterations were, however, relatively conservative and limited. The binding capacity of the S3/S3' sites was exploited by elongation of the compounds with groups in the P3/P3' positions or by extension of the P1/P1' groups. Furthermore, water molecules were shown to be important binding links between the protease and the inhibitors. This study produced a number of inhibitors with Ki values in the 100 picomolar range.

Relationships between structure and interaction kinetics for HIV-1 protease inhibitors

The interaction between HIV-1 protease and 58 structurally diverse transition-state analogue inhibitors has been analyzed by a surface plasmon resonance based biosensor. Association and dissociation rate constants and affinities were determined and displayed as k(on)-k(off)-K(D) maps. It was shown that different classes of inhibitors fall into distinct clusters in these maps. Significant changes in association and dissociation rates were found as a result of modifying the P1/P1' or P2/P2' side chains of a linear lead compound. Similarly, cyclic urea and cyclic sulfamide inhibitors displayed different kinetic features and the affinities of both classes of cyclic compounds were limited by fast dissociation rates. These results confirm that association and dissociation rates are important features of drug-target interactions and indicate that optimization of inhibitor efficacy may be guided by aiming for high association and low dissociation rates rather than high affinity alone. The present approach thus provides a new tool for structure-interaction kinetic analysis and drug discovery.

Lung function of school children with low levels of alpha1-antitrypsin and tobacco smoke exposure

Exposure to environmental tobacco smoke (ETS) and other air pollutants has been associated with small decrements in lung function. The susceptibility to pollution exposure may, however, vary substantially between individuals. Children with an impaired protease-antiprotease balance may be particularly vulnerable. Therefore this study aimed to investigate the effects of ETS exposure on children with reduced levels of alpha1-antitrypsin (alpha1-AT). Random samples of school children (aged 9-11 yrs) (n=3,526) were studied according to the International Study of Asthma and Allergies in Childhood (ISAAC) phase II protocol, including parental questionnaires, pulmonary function and allergy testing. Blood samples were obtained to measure plasma levels of alpha1-AT and to genotype for pleomorphic protein inhibitor (Pi)Z and PiS alleles. Children with low levels of alpha1-AT (< or = 116 mg x dL(-1)) showed significant, albeit small decrements in baseline lung function. When exposed to ETS, pronounced decrements of pulmonary function, particularly in measures of mid- to end-expiratory flow rates, were seen in these children as compared to exposed children with normal levels of alpha1-AT. The mean levels of % predicted+/-SE in both groups were: maximum expiratory flow at 50% of vital capacity 79.4+/-7.2 versus 99.0+/-1.5, maximum expiratory flow at 25% of vital capacity 67.4+/-10.0 versus 100.3+/-2.1, maximal midexpiratory flow 73.7+/-8.6 versus 99.9+/-1.7. These findings suggest that school children with low levels of alpha1-antitrypsin are at risk of developing pronounced decrements in pulmonary function, particularly if they are exposed to environmental tobacco smoke. Parents of children with heterozygous alpha1-antitrypsin deficiency resulting in significantly reduced blood concentrations should be advised to prevent their children from being exposed to environmental tobacco smoke and dissuade them from taking up smoking.

Synthesis and comparative molecular field analysis (CoMFA) of symmetric and nonsymmetric cyclic sulfamide HIV-1 protease inhibitors

We have previously reported on the unexpected flipped conformation in the cyclic sulfamide class of inhibitors. An attempt to induce a symmetric binding conformation by introducing P2/P2' substituents foreseen to bind preferentially in the S2/S2' subsite was unsuccessful. On the basis of the flipped conformation we anticipated that nonsymmetric sulfamide inhibitors, with P2/P2' side chains modified individually for the S1' and S2 subsites, should be more potent than the corresponding symmetric analogues. To test this hypothesis, a set of 18 cyclic sulfamide inhibitors (11 nonsymmetric and 7 symmetric) with different P2/P2' substituents was prepared and evaluated in an enzyme assay. To rationalize the structure-activity relationship (SAR) and enable the alignment of the nonsymmetric inhibitors, i.e., which of the P2/P2' substituents of the nonsymmetric inhibitors interact with which subsite, a CoMFA study was performed. The CoMFA model, constructed from the 18 inhibitors in this study along with seven inhibitors from previous work by our group, has successfully been used to rationalize the SAR of the cyclic sulfamide inhibitors. Furthermore, from the information presented herein, the SAR of the cyclic sulfamide class of inhibitors seems to differ from the SAR of the related cyclic urea inhibitors reported by DuPont and DuPont-Merck.

Characterization of a set of HIV-1 protease inhibitors using binding kinetics data from a biosensor-based screen

The interaction between 290 structurally diverse human immunodeficiency virus type 1 (HIV-1) protease inhibitors and the immobilized enzyme was analyzed with an optical biosensor. Although only a single concentration of inhibitor was used, information about the kinetics of the interaction could be obtained by extracting binding signals at discrete time points. The statistical correlation between the biosensor binding data, inhibition of enzyme activity (K(i)), and viral replication (EC(50)) revealed that the association and dissociation rates for the interaction could be resolved and that they were characteristic for the compounds. The most potent inhibitors, with respect to K(i) and EC(50) values, including the clinically used drugs, all exhibited fast association and slow dissociation rates. Selective or partially selective binders for HIV-1 protease could be distinguished from compounds that showed a general protein-binding tendency by using three reference target proteins. This biosensor-based direct binding assay revealed a capacity to efficiently provide high-resolution information on the interaction kinetics and specificity of the interaction of a set of compounds with several targets simultaneously.

Inhibitors of the C(2)-symmetric HIV-1 protease: nonsymmetric binding of a symmetric cyclic sulfamide with ketoxime groups in the P2/P2' side chains

Symmetric cyclic sulfamides, substituted in the P2/P2' position with functional groups foreseen to bind preferentially to the S2/S2' subsites of HIV-1 protease, have been prepared. Despite efforts to promote a symmetric binding, the sulfamides seemed prone to bind nonsymmetrically, as deduced from X-ray crystal structure analysis of one of the most potent inhibitors, possessing ketoxime groups in the P2/P2' side chains. Ab initio calculations suggested that the nonsymmetric conformation of the cyclic sulfamide scaffold had lower energy than the corresponding symmetric, cyclic urea-like conformation.

Lower prevalence of asthma and atopy in Turkish children living in Germany

Ethnic origin has been reported to affect the prevalence of atopic diseases in several studies in different parts of the world. However, little is known about the prevalence of asthma and atopy in immigrants living in Europe. The objective of this study was to evaluate the prevalence of asthma and atopy in Turkish children living in Germany and to investigate the role of ethnic origin on the development of asthma and atopy in this population. In a cross-sectional survey the prevalence of physician-diagnosed asthma, atopy, skin-prick tests and bronchial hyperresponsiveness (BHR) to cold dry air challenge was assessed in 7,445 school children aged 9-11 yrs, living in Munich, south Germany. Questionnaires were distributed to the parents for self-completion and children underwent skin prick tests and cold air hyperventilation challenge. The Turkish children showed a significantly lower prevalence of asthma (5.3 versus 9.4%, p<0.05) than their German peers. Furthermore, atopy, as assessed by skin prick tests (24.7 versus 36.7%, p<0.001) and BHR (3.9 versus 7.7%, p<0.001), was less common in Turkish children. In multivariate regression models controlling for potential explanatory factors, Turkish origin still showed a significantly lower risk of developing asthma, atopic sensitization and BHR. The prevalence of childhood asthma was therefore shown to be lower in Turkish children living in Germany than in Turkey. These findings suggest that the lower prevalence of asthma and allergy in Turkish children living in Germany might be attributable to a selection bias affecting the parents of these children, as healthy individuals may have decided to come to Germany for work.

Unexpected binding mode of a cyclic sulfamide HIV-1 protease inhibitor

Two cyclic, C2-symmetric HIV-1 protease inhibitors, one sulfamide and one urea derivative, both comprising phenyl ether groups in the P1/P1' positions, were cocrystallized with HIV-1 protease, and the crystal structures were determined to 2.0 A resolution. The structure of the urea 2 showed a conformation similar to that reported for the related urea 3 by Lam et al., while the sulfamide 1 adopted an unanticipated conformation in which the P1' and P2' side chains were transposed.

Isoprene and Rubber. Part 28. The Fractionation and Cracking of Hydrorubber

The Fractionation of Hydrorubber According to the investigations of Geiger, treatment of rubber with hydrogen in the presence of nickel at 270° brings about a reduction with simultaneous cracking of the macromolecules of the rubber. The hemi-colloidal hydrorubber thus formed ought not to consist of uniform long molecules, but of a mixture of homologous polymers; because in other similar cases mixtures of homologous polymers were obtained when macromolecular substances are decomposed, e. g., in the acetolytic decomposition of polyoxymethylenes and of cellulose. According to the views of Pummerer, on the other hand, if rubber consists of relatively small molecules, there would be no decomposition by cracking during its reduction, but only a saturation of individual primary valence chains with breaking up of the micellar structure, with formation of a hydrorubber whose molecules are uniformly long. Pummerer and Koch believed that they had obtained such a substance. To prove whether hydrorubber consists of a mixture of homologous polymers, it was split up into five fractions by fractional precipitation with alcohol from its ethereal solution, and the viscosities of the individual fractions were determined in 0.5 molar carbon tetrachloride solution (Table I).

Isoprene and Rubber. Part 26. Hemicolloidal Hydrorubbers

The reduction of rubber without solvent takes place only at 270°, according to experiments by Fritschi. Below this temperature rubber is reduced only with difficulty and incompletely. In the dissolved eondition, on the contrary, Pummerer and Burkard showed that rubber can be reduced at ordinary temperature. In an earlier communication it was accordingly assumed that on heating a cleavage of secondary colloid particles into primary ones (into macromolecules) takes place, and that heating, therefore, has about the same effect as strong dilution. A distinction was made between primary and secondary particles, and it was assumed that the strong diminution in viscosity which is observed in dilute rubber solutions depends upon a cleavage of the secondary colloid particles, just as do the decreases in viscosity which rubber undergoes upon heating, and which have been generally described as depolymerization. These earlier ideas of ours are, however, incorrect. An extensive cracking of the rubber molecules takes place upon heating, and this was more carefully investigated by Geiger and later by Bondy. In this way reduction is facilitated. With strong dilution, on the other hand, the rubber solution passes from the gel state to the sol state, the rubber passes into normal solution, and therefore reduction can take place more easily in a dilute solution than in a concentrated one. With reduction by heat, therefore, a derivative of unchanged rubber cannot be expected; instead the hydrorubbers obtained, for example, those first prepared by Fritschi, are not reduction products of rubber itself, but are hemicolloidal decomposition products of the latter. Only by careful reduction in cold solution can one succeed in obtaining a hydrorubber in which the rubber molecules remain unchanged.