Blog Data mining

The U.S. National Committee for Crystallography (USNC/Cr) of the National Academies of Sciences, Engineering, and Medicine is providing an online workshop series for students and researchers on the use, development, and maintenance of crystallographic and structural databases. CCDC is excited to present a two-day session at the event about the Cambridge Structural Database! To celebrate, we’re hosting a live AMA (ask me anything) via Twitter with the CCDC session host, Dr Jeff Lengyel, and departmental crystallographer at the University of Notre Dame, Dr Allen Oliver.

Cyclo-P_n ligands are carbon-free analogues to aromatic organic ligands. They have lone electron pairs, which are reactive towards Lewis acidic transition metals to give various coordination. According to a recent review article co-authored by researchers at the University of Regensburg, these are a few reasons cyclo-P_n ligand complexes are so important to the field of organometallic chemistry. In this Q&A blog, we talk to two of the co-authors on that paper, Dr Peresypkina and Dr Virovets, about the team’s work, trends they found, and potential applications for the compounds.

Formally published in Nature Scientific Data in 2016, the FAIR Data Principles provide a framework for scientific data management and stewardship. “FAIR” is an acronym for the Findability, Accessibility, Interoperability, and Reusability of data—for both humans and machines. In this Q&A-style blog, Carmen Nitsche (CCDC US general manager who is also active in several InChI and IUPAC data standards initiatives) answers common questions about how the FAIR Data Principles can help solve real-world challenges.

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.

How many groups took part in the first challenge of the 7th CSP Blind Test? What kind of experimental work goes on behind the scenes? Read on for answers, and an interesting Q&A with a team from Catalent. Catalent is a development and manufacturing partner that has provided the high-quality experimental data for this test of crystal structure prediction (CSP) methods.

This year the CCDC and the Protein Data Bank (PDB) are hosting a day-long symposium at the American Chemical Society’s (ACS) Fall 2021 meeting. The conference theme is “the resiliency of chemistry,” and our symposium focuses on understanding enzyme function in 3D.

At our upcoming virtual Discovery Science meeting, we’ll hear from speakers on the theme: High-performance data meets high-performance computing. We’re increasingly seeing from the literature and our user community that combining quality data with computing power is changing drug discovery approaches. Here I want to share some examples of this theme.

CCDC was honored to sponsor and present at the first joint virtual meeting of the Southern California and Boston Area Groups for Informatics and Modeling (SAGIM and BAGIM) last Thursday, April 15th. Over 150 participants attended to discuss the value of information extracted from structural databases and the important metrics for database curation.