In 2019 we started exploring how the CCDC’s experience in data management and standards could best serve the data needs of the Crystal Structure Prediction (CSP) community. Around 18 months on, we wanted to share the outputs so far, how you can get involved, and what you can expect to see from us in the future.
Here we highlight a paper using CSD-Discovery to identify drug models for the treatment of complications due to diabetes and to define molecular features that can guide future drug design. This is part of our series highlighting examples of the Cambridge Crystallographic Data Centre (CCDC) tools in action by scientists around the world.
The existence of various molecular arrangements that occur in the solid-state is called polymorphism. Identifying polymorphs is important for risk management purposes and exploring the polymorphic landscape to identify the most stable forms is an important step during early-stage drug development. As part of our Tools in Action blog series highlighting the use of CCDC tools by scientists around the world, we recently showed how a research team used the Cambridge Structural Database (CSD) and the Hydrogen Bond Propensity (HBP) tool to characterize two polymorphs of an anti-inflammatory drug and predict the existence of additional forms. Here we present more information about how the HBP tool works to see if you can use it to assess polymorphs.
Here we highlight a paper using the CSD Ligand Overlay tool in ligand-based drug design for the development of antibiotics and antifungals. This is part of our series highlighting examples of the Cambridge Crystallographic Data Centre (CCDC) tools in action by scientists around the world.