Blog CSD-Core

On 14 October, we hosted Dr Peyman Z. Moghadam from The University of Sheffield at our MOFs networking event. He presented his talk, High-throughput Computational Screening for MOF Materials Discovery. He spoke on how the analysis of MOFs data can support and guide the development of novel MOFs to suit specific applications like energy storage, catalysis, and CO2 sequestering. Here, you'll find materials from the event, including a recording of his presentation.

The FAIR Data Principles stand for findability, accessibility, interoperability, and reusability of data for both humans and machines. Here we highlight a few ways CCDC supports the FAIR Data Principles.

Here we highlight a paper by researchers at the University of Liverpool and Università di Siena who used the Cambridge Structural Database (CSD) to identify a set of promising compounds for use in semiconductors and a new tool for discovering materials with electronic properties. This is part of our series highlighting examples of​​ the Cambridge Crystallographic Data Centre (CCDC) tools in action by scientists around the world.

We are pleased to announce the September 2021 data update of the Cambridge Structural Database (CSD) is now available!  This data update brings you 16,688 new organic and metal-organic experimentally determined structures (17,283 new entries) and increases the total size of the CSD to over 1,129,000 structures (1,152,000 entries).

I’m a Research and Applications Scientist on the Discovery Science team at CCDC. In this short blog and accompanying video, I walk through how to make the most of your CSD-Enterprise licence using the tools in CSD-Discovery. The video highlights the available software in the Discovery suite and how it might fit into a drug development workflow. I also present real-world examples of a variety of research applications, including identifying dynamic disorder in semiconductors, advancing COVID-19 research and understanding ALR2 inhibitors for the treatment of diabetes complications.

Molecules that have different molecular packing arrangements despite identical chemical composition are said to be polymorphic. The variety of possible forms, each an allomorph (or polymorph), presents opportunities and challenges in various fields – including the drug industry and agriculture and forestry. In this blog, we talk to United States Department of Agriculture (USDA) Research Scientist Emeritus¹ and the Editor-in-Chief of Cellulose, Dr Alfred D. French about his work with cellulose, which has multiple polymorphs (allomorphs).

Here we highlight a paper by John W. Liebeschuetz from Astex Pharmaceuticals that used Mogul to analyze the geometry of drug-like ligand models for high-resolution crystallographic protein-ligand complexes. This is part of our series highlighting examples of​​ the Cambridge Crystallographic Data Centre (CCDC) tools in action by scientists around the world.

The CCDC offers a selection of products and services free of charge for the benefit of the scientific community, which includes a free version of Mercury. While the free version supports several functionalities, many popular features are only available with a licence. Here we explain the differences between the free and paid licence versions of Mercury.

I’m a Research and Applications Scientist on the Materials Science team at CCDC, and I recently taught a session at the Rigaku School for Practical Crystallography, which ran from June 7–18, 2021. The school focused on practical applications of software, techniques and technologies for crystallography. This blog contains links to my recorded modules as well as a self-assessment quiz you can use to check what you’ve learned.

Here we highlight a paper by scientists at the Lawrence Livermore National Laboratory using the Cambridge Structural Database (CSD) to train models to predict the densities of molecules from chemical structure alone. This is part of our series highlighting examples of​​ the Cambridge Crystallographic Data Centre (CCDC) tools in action by scientists around the world.