How can I predict binding affinity without a target protein structure?
Why traditional ligand-based QSAR methods have fallen short You might be sceptical about ligand-based QSAR approaches; many researchers are. We discussed why there has…
Ensemble-based conformational modelling for macrocycles
From X-ray refinement to lead optimisation Conventional ligand-fitting and refinement methods in X-ray electron density maps often yield models with…
Share your science, not your secrets: How StarDrop 8 Supports Collaboration with external partners
The collaboration challenge: Where generic tools fall short Several collaboration platforms have been designed to support molecule design and optimisation.…
Looking beyond statistics: How do I determine whether a QSAR model will add value to my project?
Good statistics don’t guarantee good applicability. Performance metrics will tell you how well a QSAR model predicts known data, but they don’t tell you whether it will add practical value…
Enhanced ADME predictions : New and improved models in StarDrop 8
All models are available in StarDrop’s ADME QSAR module: pKa– Most acidic pKa– Most basic pKa– All pKa valueslogP (Octanol/Water)logD7.4 (Octanol/buffer…
Counting what counts: Structural descriptors in StarDrop
In medicinal chemistry, it’s often the little things, like the subtle changes in a molecule’s structure, that make the difference.…
Real-time collaboration for molecule design: Why medicinal chemists need more than just shared documents
Imagine if everyone on your team could stay in sync with the latest compounds and data, working with the same…
xGen™: Fitting of complex ligand conformational ensembles to X-ray electron density maps
Conventional ligand fitting and refinement in X-ray electron density maps relies on single conformers and B-factors, that often yields ligands…
Pushing the limits of QSAR modelling
Probably the most common use of machine learning (ML) in drug discovery is QSAR modelling, where we predict the properties…
