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Containers are gaining popularity in life science research as they provide a solution for encompassing dependencies of provisioned tools, simplify software installations for end users and offer a form of isolation between processes. Scientific workflows are ideal for chaining containers into data analysis pipelines to aid in creating reproducible analyses. In this manuscript we review a number of approaches to using containers as implemented in the workflow tools Nextflow, Galaxy, Pachyderm, Argo, Kubeflow, Luigi and SciPipe, when deployed in cloud environments. A particular focus is placed on the workflow tool’s interaction with the Kubernetes container orchestration framework.

Silver-based products have been marketed as an alternative to antibiotics, and their consumption has increased. Bacteria may, however, develop resistance to silver.To study the presence of genes encoding silver resistance (silE, silP, silS) over time in three clinically important Enterobacteriaceae genera.Using polymerase chain reaction (PCR), 752 bloodstream isolates from the years 1990-2010 were investigated. Age, gender, and ward of patients were registered, and the susceptibility to antibiotics and silver nitrate was tested. Clonality and single nucleotide polymorphism were assessed with repetitive element sequence-based PCR, multi-locus sequence typing, and whole-genome sequencing.Genes encoding silver resistance were detected most frequently in Enterobacter spp. (48%), followed by Klebsiella spp. (41%) and Escherichia coli 4%. Phenotypical resistance to silver nitrate was found in Enterobacter (13%) and Klebsiella (3%) isolates. The lowest carriage rate of sil genes was observed in blood isolates from the neonatology ward (24%), and the highest in blood isolates from the oncology/haematology wards (66%). Presence of sil genes was observed in international high-risk clones. Sequences of the sil and pco clusters indicated that a single mutational event in the silS gene could have caused the phenotypic resistance.Despite a restricted consumption of silver-based products in Swedish health care, silver resistance genes are widely represented in clinical isolates of Enterobacter and Klebsiella species. To avoid further selection and spread of silver-resistant bacteria with a high potential for healthcare-associated infections, the use of silver-based products needs to be controlled and the silver resistance monitored.

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.

Containers are gaining popularity in life science research as they encompass all dependencies of provisioned tools and simplifies software installations for end users, as well as offering a form of isolation between processes. Scientific workflows are ideal to chain containers into data analysis pipelines to sustain reproducible science. In this manuscript we review the different approaches to use containers inside the workflow tools Nextflow, Galaxy, Pachyderm, Luigi, and SciPipe when deployed in cloud environments. A particular focus is placed on the workflow tool’s interaction with the Kubernetes container orchestration framework.

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 (p40%. 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 (p40%. 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.

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.

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.

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. Electronic supplementary material The online version of this article (doi:10.1186/s13321-016-0151-5) contains supplementary material, which is available to authorized users.

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.

Virtual screening has the potential to accelerate and reduce costs of probe development and drug discovery. To develop and benchmark virtual screening methods, validation data sets are commonly used. Over the years, such data sets have been constructed to overcome the problems of analogue bias and artificial enrichment. With the rapid growth of public domain databases containing high-throughput screening data, such as the PubChem BioAssay database, there is an increased possibility to use such data for validation. In this study, we identify PubChem data sets suitable for validation of both structure- and ligand-based virtual screening methods. To achieve this, high-throughput screening data for which a crystal structure of the bioassay target was available in the PDB were identified. Thereafter, the data sets were inspected to identify structures and data suitable for use in validation studies. In this work, we present seven data sets (MMP13, DUSP3, PTPN22, EPHX2, CTDSP1, MAPK10, and CDK5) compiled using this method. In the seven data sets, the number of active compounds varies between 19 and 369 and the number of inactive compounds between 59 405 and 337 634. This gives a higher ratio of the number of inactive to active compounds than what is found in most benchmark data sets. We have also evaluated the screening performance using docking and 3D shape similarity with default settings. To characterize the data sets, we used physicochemical similarity and 2D fingerprint searches. We envision that these data sets can be a useful complement to current data sets used for method evaluation.

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.

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.

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.

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.

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.

15-Lipoxygenase-1 catalyzes the introduction of molecular oxygen into polyunsaturated fatty acids to form a lipid hydroper- oxide. 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 phos- phine 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 Zvalue 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. (Journal of Biomolecular Screening 2010:671-679)

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.

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.

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.

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.