45 research outputs found

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

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    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

    OPTIMADE, an API for exchanging materials data

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    : The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification

    OPTIMADE, an API for exchanging materials data.

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    The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification

    Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange

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    The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the upcoming v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development

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

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    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

    AceDRG: a stereochemical description generator for ligands

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    The program AceDRG is designed for the derivation of stereochemical information about small molecules. It uses local chemical and topological environment-based atom typing to derive and organize bond lengths and angles from a small-molecule database: the Crystallography Open Database (COD). Information about the hybridization states of atoms, whether they belong to small rings (up to seven-membered rings), ring aromaticity and nearest neighbour information is encoded in the atom types. All atoms from the COD have been classified according to the generated atom types. All bonds and angles have also been classified according to the atom types and, in a certain sense, bond types. Derived data are tabulated in a machine-readable form that is freely available from CCP4. AceDRG can also generate stereochemical information, provided that the basic bonding pattern of a ligand is known. The basic bonding pattern is perceived from one of the computational chemistry file formats, including SMILES, mmCIF, SDF MOL and SYBYL MOL2 files. Using the bonding chemistry, atom types, and bond and angle tables generated from the COD, AceDRG derives the ‘ideal’ bond lengths, angles, plane groups, aromatic rings and chirality information, and writes them to an mmCIF file that can be used by the refinement program REFMAC5 and the model-building program Coot. Other refinement and model-building programs such as PHENIX and BUSTER can also use these files. AceDRG also generates one or more coordinate sets corresponding to the most favourable conformation(s) of a given ligand. AceDRG employs RDKit for chemistry perception and for initial conformation generation, as well as for the interpretation of SMILES strings, SDF MOL and SYBYL MOL2 files

    Validation and extraction of molecular-geometry information from small-molecule databases

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    A freely available small-molecule structure database, the Crystallography Open Database (COD), is used for the extraction of molecular-geometry information on small-molecule compounds. The results are used for the generation of new ligand descriptions, which are subsequently used by macromolecular model-building and structure-refinement software. To increase the reliability of the derived data, and therefore the new ligand descriptions, the entries from this database were subjected to very strict validation. The selection criteria made sure that the crystal structures used to derive atom types, bond and angle classes are of sufficiently high quality. Any suspicious entries at a crystal or molecular level were removed from further consideration. The selection criteria included (i) the resolution of the data used for refinement (entries solved at 0.84 Å resolution or higher) and (ii) the structure-solution method (structures must be from a single-crystal experiment and all atoms of generated molecules must have full occupancies), as well as basic sanity checks such as (iii) consistency between the valences and the number of connections between atoms, (iv) acceptable bond-length deviations from the expected values and (v) detection of atomic collisions. The derived atom types and bond classes were then validated using high-order moment-based statistical techniques. The results of the statistical analyses were fed back to fine-tune the atom typing. The developed procedure was repeated four times, resulting in fine-grained atom typing, bond and angle classes. The procedure will be repeated in the future as and when new entries are deposited in the COD. The whole procedure can also be applied to any source of small-molecule structures, including the Cambridge Structural Database and the ZINC database

    A workflow for deriving chemical entities from crystallographic data and its application to the Crystallography Open Database

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    Abstract Knowledge about the 3-dimensional structure, orientation and interaction of chemical compounds is important in many areas of science and technology. X-ray crystallography is one of the experimental techniques capable of providing a large amount of structural information for a given compound, and it is widely used for characterisation of organic and metal-organic molecules. The method provides precise 3D coordinates of atoms inside crystals, however, it does not directly deliver information about certain chemical characteristics such as bond orders, delocalization, charges, lone electron pairs or lone electrons. These aspects of a molecular model have to be derived from crystallographic data using refined information about interatomic distances and atom types as well as employing general chemical knowledge. This publication describes a curated automatic pipeline for the derivation of chemical attributes of molecules from crystallographic models. The method is applied to build a catalogue of chemical entities in an open-access crystallographic database, the Crystallography Open Database (COD). The catalogue of such chemical entities is provided openly as a derived database. The content of this catalogue and the problems arising in the fully automated pipeline are discussed, along with the possibilities to introduce manual data curation into the process

    Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds

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    Two-dimensional (2D) materials have emerged as promising candidates for next-generation electronic and optoelectronic applications. Yet, only a few dozen 2D materials have been successfully synthesized or exfoliated. Here, we search for 2D materials that can be easily exfoliated from their parent compounds. Starting from 108,423 unique, experimentally known 3D compounds, we identify a subset of 5,619 compounds that appear layered according to robust geometric and bonding criteria. High-throughput calculations using van der Waals density functional theory, validated against experimental structural data and calculated random phase approximation binding energies, further allowed the identification of 1,825 compounds that are either easily or potentially exfoliable. In particular, the subset of 1,036 easily exfoliable cases provides novel structural prototypes and simple ternary compounds as well as a large portfolio of materials to search from for optimal properties. For a subset of 258 compounds, we explore vibrational, electronic, magnetic and topological properties, identifying 56 ferromagnetic and antiferromagnetic systems, including half-metals and half-semiconductors
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