ArticleJournal of cheminformatics2023
A workflow for deriving chemical entities from crystallographic data and its application to the Crystallography Open Database.
Article in Journal of cheminformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
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- Application of Magnetic Nanoparticles for Reactive Dye Removal from Aqueous Solutions: Practical and Theoretical Approaches.Nanomaterials (Basel, Switzerland) · 2026Article
- Determination of bonding radii from small-molecule crystal structures.Journal of cheminformatics · 2026Article
- Mean weighted residuals reveal systematic overestimation of Bragg intensities in single-crystal diffraction.Journal of applied crystallography · 2026Article
- Potential Application of Epoxy Powder Coating Waste in Concrete: Strength Properties and Durability of Concrete.Materials (Basel, Switzerland) · 2026Article
- Monitoring Interfacial Dynamics of a Zinc-Ion Battery Cathode Using In Situ Grazing Incidence X-Ray Absorption Spectroscopy: A Case Study of Manganese Dioxide.Small methods · 2026Article
- Silver nanoparticles as antimicrobials: A comparative analysis of green and traditional chemistry synthesis methods.PloS one · 2026Article
- Application of Chemometric Methods in X-Ray Diffraction Data on Arabica Coffee Management Soils in Brazil.Analytical science advances · 2025Article
- Antibacterial and antibiofilm activity of nanoparticles inRSC advances · 2025Article
- An NMR Database for Organic and Organometallic Compounds.Molecules (Basel, Switzerland) · 2025Article
- Rare-Earth Molecular Cluster Aggregates with Sandglass-like Core Topology as Surrogates for Minor Actinides in Immobilization within Alkaline-Earth Manganites.Inorganic chemistry · 2025Article
- Data-Driven Site Occupancy Statistics in Cubic Prussian Blue.ACS physical chemistry Au · 2025Article
- One step laser-induced synthesis of a bimetallic iron-cobalt sulfide for efficient solar light driven, Fenton-like and electrochemical catalysis.RSC advances · 2025Article
- A new benchmark for machine learning applied to powder X-ray diffraction.Scientific data · 2025Article
- Machine Learning in Computational Design and Optimization of Disordered Nanoporous Materials.Materials (Basel, Switzerland) · 2025Review
- Predictive crystallography at scale: mapping, validating, and learning from 1000 crystal energy landscapes.Faraday discussions · 2025Article
- Data Generation for Machine Learning Interatomic Potentials and Beyond.Chemical reviews · 2024Review
- Solidified Salt Melts of the NaCl-KCl-CeFMaterials (Basel, Switzerland) · 2024Article
- Silicate coprecipitation reduces green rust crystal size and limits dissolution-precipitation during air oxidation.Geochemical transactions · 2024Article
- Heterocycles as supramolecular handles for crystal engineering: a case study with 7-(diethylamino)coumarin derivatives.RSC advances · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
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.
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