PLBD: protein–ligand binding database of thermodynamic and kinetic intrinsic parameters

We introduce a protein–ligand binding database (PLBD) that presents thermodynamic and kinetic data of reversible protein interactions with small molecule compounds. The manually curated binding data are linked to protein–ligand crystal structures, enabling structure–thermodynamics correlations to be determined. The database contains over 5500 binding datasets of 556 sulfonamide compound interactions with the 12 catalytically active human carbonic anhydrase isozymes defined by fluorescent thermal shift assay, isothermal titration calorimetry, inhibition of enzymatic activity and surface plasmon resonance. In the PLBD, the intrinsic thermodynamic parameters of interactions are provided, which account for the binding-linked protonation reactions. In addition to the protein–ligand binding affinities, the database provides calorimetrically measured binding enthalpies, providing additional mechanistic understanding. The PLBD can be applied to investigations of protein–ligand recognition and could be integrated into small molecule drug design

Rozmnażanie in vitro alternatywnych roślin ogrodniczych (Actinidia, Chaenomeles, Aronia)

Succesful propagation of selected clones and cultivars of Actinidia kolomicta (Maxim.) Maxim., A. arguta (Siebold et Zucc.) Planch, ex Miq., Chaenomeles japonica (Thunb.) Lindl, ex Spach and Aronia melanocarpa (Michx.) Elliott has been achieved by in vitro methods. It has been demonstrated that the intensity and pathway of microvegetative propagation depend on the properties of plant species, genotype and sex. Under in vitro conditions, actinidia multiplicated by forming shoots from apical meristems and auxiliary buds of shoots, dwarf Japanese quince and black chokeberry - by new adventitious shoots. For in vitro development, male plants of actinidia species demanded opposite ratios of auxins and cytokinins than the female plants. They worse adapted to in vitro conditions. Multiplication coefficient in the fourth week was as follows: Actinidia - 1.3-4.5; Chaenomeles – 1.9-4.1; Aronia - 14.3.Przy pomocy metod in vitro udało się rozmnożyć wybrane klony i odmiany Actinidia kolomicta (Maxim) Maxim, A. arguta (Siebold et Zucc.) Planch, ex Miq., Chaenomeles japonica (Thunb.) Lindl, ex Spach oraz Aronia melanocarpa (Michx.) Elliott. Wykazano, że intensywność i przebieg rozmnażania zależały od właściwości gatunku rośliny, genotypu i płci. W warunkach in vitro aktynidia rozmnażała się poprzez tworzenie pędów z merystemów wierzchołka i pomocniczych pęków na pędach, karłowata pigwa japońska i aronia - poprzez nowe pędy przybyszowe. W celu rozmnożenia w warunkach in vitro rośliny męskie wymagały odwrotnych proporcji auksyn i cytokinin niż rośliny żeńskie. Gorzej dostosowywały się do warunków in vitro. Współczynnik rozmnażania w czwartym tygodniu był następujący: Actinidia - 1.3-4.5; Chaenomeles - 1.9-4.1; Aronia - 14.3

AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance

The ever-growing availability of computing power and the sustained development of advanced computational methods have contributed much to recent scientific progress. These developments present new challenges driven by the sheer amount of calculations and data to manage. Next-generation exascale supercomputers will harden these challenges, such that automated and scalable solutions become crucial. In recent years, we have been developing AiiDA (http://www.aiida.net), a robust open-source high-throughput infrastructure addressing the challenges arising from the needs of automated workflow management and data provenance recording. Here, we introduce developments and capabilities required to reach sustained performance, with AiiDA supporting throughputs of tens of thousands processes/hour, while automatically preserving and storing the full data provenance in a relational database making it queryable and traversable, thus enabling high-performance data analytics. AiiDA's workflow language provides advanced automation, error handling features and a flexible plugin model to allow interfacing with any simulation software. The associated plugin registry enables seamless sharing of extensions, empowering a vibrant user community dedicated to making simulations more robust, user-friendly and reproducible