Identification of chemical compounds with specific biological activities is an important step in both chemical biology and drug discovery. When the structure of the intended target is available, one approach is to use molecular docking programs to assess the chemical complementarity of small molecules with the target; such calculations provide a qualitative measure of affinity that can be used in virtual screening (VS) to rank order a list of compounds according to their potential to be active. rDock is a molecular docking program developed at Vernalis for high-throughput VS (HTVS) applications. Evolved from RiboDock, the program can be used against proteins and nucleic acids, is designed to be computationally very efficient and allows the user to incorporate additional constraints and information as a bias to guide docking. This article provides an overview of the program structure and features and compares rDock to two reference programs, AutoDock Vina (open source) and Schrödinger's Glide (commercial). In terms of computational speed for VS, rDock is faster than Vina and comparable to Glide. For binding mode prediction, rDock and Vina are superior to Glide. The VS performance of rDock is significantly better than Vina, but inferior to Glide for most systems unless pharmacophore constraints are used; in that case rDock and Glide are of equal performance. The program is released under the Lesser General Public License and is freely available for download, together with the manuals, example files and the complete test sets, at http://rdock.sourceforge.net/
Summary Cylindrospermopsis raciborskii occupies a rapidly expanding geographical area. Its invasive success challenges eutrophication control in many lakes. To understand better the load‐dependent behaviour of this nitrogen fixing cyanobacterium under in situ conditions, we studied P‐dependent growth of a C. raciborskii strain under continuous and pulsed P supply. The Droop model reasonably described P‐dependent growth in the continuously supplied chemostats. Large P pulses, however, caused a delay in growth and cells subject to P pulses grew slower than their counterparts with the same P quota supplied continuously. The kinetics of P uptake indicated that C. raciborskii is opportunistic with respect to P. Its high excess P storage capacity after a saturating P pulse (Qex=95 µg P [mg C]‐1) and P‐specific uptake capacity (Umax = Vmax/QP=150–1200) are indicative of storage adaptation. At the same time, the affinity of the P uptake system (Umax/K = 800–4000) is also high. Rate of leakage exceeded that of the steady state net P uptake by one to two orders of magnitude. Growth affinity of C. raciborskii (µmax/Kµ≈ 20) was relatively low, presumably due to the substantial leakage. The dynamics of the particular water body determine which trait contributes most to competitive success of C. raciborskii. In deep lakes with vertical nutrient gradients, the cyanobacterium may rely primarily on its high P storage capacity, which is coupled to a lack of short‐term feedback inhibition and efficient buoyancy regulation. In lakes without such gradients, high P uptake affinity may be vitally important.
Whole-genome sequencing (WGS) is a fundamental technology for research to advance precision medicine, but the limited availability of portable and user-friendly workflows for WGS analyses poses a major challenge for many research groups and hampers scientific progress. Here we present Sarek, an open-source workflow to detect germline variants and somatic mutations based on sequencing data from WGS, whole-exome sequencing (WES), or gene panels. Sarek features (i) easy installation, (ii) robust portability across different computer environments, (iii) comprehensive documentation, (iv) transparent and easy-to-read code, and (v) extensive quality metrics reporting. Sarek is implemented in the Nextflow workflow language and supports both Docker and Singularity containers as well as Conda environments, making it ideal for easy deployment on any POSIX-compatible computers and cloud compute environments. Sarek follows the GATK best-practice recommendations for read alignment and pre-processing, and includes a wide range of software for the identification and annotation of germline and somatic single-nucleotide variants, insertion and deletion variants, structural variants, tumour sample purity, and variations in ploidy and copy number. Sarek offers easy, efficient, and reproducible WGS analyses, and can readily be used both as a production workflow at sequencing facilities and as a powerful stand-alone tool for individual research groups. The Sarek source code, documentation and installation instructions are freely available at https://github.com/nf-core/sarek and at https://nf-co.re/sarek/.
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