Why don’t my QSAR models work?
Why QSAR models matter in drug discovery Before we start troubleshooting, let’s remember why we build and run these models…
How can categorical models provide value in supporting compound prioritisation?
Introduction In early-stage drug discovery, medicinal chemists rely on predictive models to help guide which compounds to synthesise or test…
Which ADMET properties are important for me to predict?
How can I predict my compound’s absorption? The first of the ADMET properties relate to absorption. Understanding how a drug…
Machine Learning 101: How to train your first QSAR model
My hope is that these posts will be of interest to people who want to understand more of the nuts…
How do I know if Optibrium’s predictive models work?
Data curation for model building A model can only be as good as the data it has been trained on.…
How can I make the most of my predictive models for drug discovery?
What’s the purpose of a predictive model? What’s the value of predictive models for drug discovery? Most of the undergraduate…
What’s the difference between QSAR and imputation predictive models – which method should I use and when?
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.
How much does drug discovery software cost?
How number of users affect drug discovery software costs The number of people who need access to the platform is…
How to build a better QSAR model
To guide drug design, it’s important to understand the likely ADME and physicochemical properties of your compounds at an early…
pKa prediction using quantum mechanics and machine learning
The dissociation of a proton from a heteroatom has a significant influence on the charge distribution and interactions of a…
Number of carbons
These two models calculates the number of sp3 carbons and the total number of carbons compound. These are available to…
Hit list triage
In this example, Card View is applied to analyse the results from a kinase project in which a large screening…
Compound prioritisation and selection
In this demo we’re going to take a look at how StarDrop can guide the prioritisation and selections of compounds using a combination of in vitro and in silico data.
Number of aromatic rings
Improve compound characterisation with StarDrop’s Number of Aromatic Rings tool. Download now for precise ring counting and structural analysis
ADMET property prediction: The state of the art and current challenges
Summary This article discusses Quantitative Structure – Activity relationships (QSAR) methods to predict absorption, distribution, metabolism, excretion and toxicity (ADMET)…
Automatic QSAR modeling of ADME properties: blood-brain barrier penetration and aqueous solubility
Summary In this study, our researchers combined an automatic model generation process for building QSAR models with the Gaussian Processes…
Gaussian processes for classification: QSAR modeling of ADMET and target activity
Summary In this study, the researchers look to solve classification quantitative structure−activity relationship (QSAR) modelling problems using Gaussian processes. They…