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…
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…
In medicinal chemistry, it’s often the little things, like the subtle changes in a molecule’s structure, that make the difference.…
Probably the most common use of machine learning (ML) in drug discovery is QSAR modelling, where we predict the properties…
Abstract We explore a “best-of-both” approach to modelling molecular properties by combining learned molecular descriptors from a graph neural network…
Why QSAR models matter in drug discovery Before we start troubleshooting, let’s remember why we build and run these models…
Introduction 3D molecular modelling plays a vital role in modern drug discovery, offering powerful applications to streamline research, reduce costs,…
Introduction In early-stage drug discovery, medicinal chemists rely on predictive models to help guide which compounds to synthesise or test…
Introduction After training a classification model, we would like to evaluate its performance by using the trained model on an…
What is Derek Nexus? Developed by Lhasa Limited, Derek Nexus is an expert-knowledge based system that draws on over 40…
How can I predict my compound’s absorption? The first of the ADMET properties relate to absorption. Understanding how a drug…
My hope is that these posts will be of interest to people who want to understand more of the nuts…
What are StarDrop and Semeta? Semeta is a tailored platform for DMPK scientists. It enables users to address key challenges…
Data curation for model building A model can only be as good as the data it has been trained on.…
What’s the purpose of a predictive model? What’s the value of predictive models for drug discovery? Most of the undergraduate…
We’re often asked, “What’s the difference between QSAR and imputation models?”, so I’m going to explain how the methods differ, their advantages and disadvantages, and when each approach is applicable.
During this example we will consider three compounds from a lead series which we would like to try to evolve into a candidate. The compound has a good profile of ADME properties but insufficient inhibition of the target, the Serotonin transporter. In this example we will use StarDrop’s Nova module to generate new ideas for compounds to improve the potency while maintaining the balance of other properties.
Accurate QSAR models lead to more efficient and cost-effective molecular discovery. Better predictions enable you to prioritise the optimal compounds…
