Blog pharmaceutical

Here we highlight a recent paper by researchers at UBE Industries and Santen Pharmaceutical Co in which ConQuest helped identify a scaffold with a promising EP2-selective receptor agonist that may lower intraocular pressure (IOP). A prodrug of it was selected as a clinical candidate for the treatment of glaucoma.

This is part of our series highlighting examples of​​ the Cambridge Crystallographic Data Centre (CCDC) tools in action by scientists around the world.

I’m a Research and Applications Scientist on the Materials 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-Materials. In the first half of the video, I focus on the Cambridge Structural Database (CSD), highlighting its integrations with other databases and how to best use it for geometric analysis. In the second half of the video, I discuss applications of the CSD-Materials software, demonstrating how the different tools within the suite can help with pharmaceutical risk analysis.

We recently hosted our 2021 Discovery Science Conference: High-performance data meets high-performance computing. Over the course of the two-day event, leading researchers discussed how drug discovery continues to evolve – with data-driven approaches answering more questions than ever about novel and improved active pharmaceutical ingredients (APIs). Here are some of our key takeaways.

Here we highlight a recent paper in which CSD-CrossMiner was used to find potential target protein(s) for newly synthesized spirobarbituric scaffolds. Such compounds have promising biomedical applications as anticonvulsants, anti-AIDS agents and anti-inflammatory remedies.

This is part of our series highlighting examples of​​ the Cambridge Crystallographic Data Centre (CCDC) tools in action by scientists around the world.

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.

How do you design a drug if you don't know the target protein structure? Ligand-based drug design is an approach used in the absence of 3D structures of drug targets. This enables early-stage discovery and lead optimisation even when the protein structure is unknown. One option involves pharmacophore modelling, and it can be used in lieu of a protein-structure-based pathway.

Generating new ideas or looking at protein-ligand interactions in a novel way is key to innovative drug discovery and design. Pharmacophore models are an excellent way to do this.

On 16^th June news outlets around the world reported the fantastic results seen in trials using dexamethasone in critically ill COVID-19 patients. This quick briefing explores the chemistry and history of this compound, and what could be coming next.