Software and Data for Academic Research
Understand fundamental aspects of chemistry, mine the world’s experimentally determined molecular structures, or develop novel compounds and materials.
Cambridge Structural Database (CSD) data and software are used by leading academic institutions around the world to support impactful research across chemistry, biochemistry, materials science, agrochemical science, and beyond.
We offer heavy discounts to all academic users, and our FAIRE grants make access free in over 80 eligible countries.
Academic users can choose from our free CSD-Community licence, or paid CSD-Enterprise licence.
Search, sort, and prepare the world’s small molecule structural data, contributed from the literature and the community since 1965. Our powerful Python API lets you search and prepare the data ready for ML, AI, or whatever your work demands.
Perform protein-ligand docking, generate conformers, find scaffold hops, and assess pocket druggability. CSD data and software enables every stage of drug discovery with empirically driven insights.
Functional Materials Design
Explore the world’s known MOFs and organic small molecules, and use informatics technique to evaluate your own structure. Novel semiconductors, optical materials, MOFs, and applications of materials are developed using CSD data and software, with references across the literature.
Train Machine Learning Models
Train your model with verified, experimentally determined and expertly curated data. The CSD is CoreTrustSeal verified and every structure has been experimentally determined, so you can be assured of quality for training or testing.
Use advanced and customizable tools to find novel targets for existing compounds, or perform large-scale virtual screens of ligands against a protein target of interest. Advanced docking without tokens or limitations.
Examples of research performed with CSD data and software, from publications across the literature.
CSD in Action: Optimizing Metal-Organic Frameworks for the Recovery of Volatile Organic Compound Emissions
CSD in Action: Using Machine Learning to Predict the Crystalline Properties of Molecular Compounds without their Crystal Structures
CSD in Action: Training a Machine Learning Model to Predict MOF Pore Accessibility with 80% Certainty
University of Manchester
“With its software development and the Cambridge Structural Database, CCDC has stretched structural chemistry and biology to its limits.
The CSD with its innovative mining tools has become the most valuable information resource for crystallographers, crystal growers and crystal engineers, always sitting at the heart of what we do.”
Dr Aurora Cruz-Cabeza
“The ability of the database to do new and interesting types of queries has a lot of potential – there’s no limit to how many questions you could ask.”
Professor Jennifer Swift
Abilene Christian Unviersity
“Our subscription to the CSD has been extremely beneficial to the research efforts of several faculty members in the Department of Chemistry & Biochemistry, and we are hopeful that we can continue to use it for years to come. It helps us to decide which projects are worth pursuing and to compare and contrast our results with those of other research groups around the world.”
Professor Greg Powell