A novel scoring profile for the design of antibacterials active against gram-negative bacteria
Introduction The increasing occurrence of multidrug-resistant bacteria is one of the major global threats to human health. Design of new…
Activity landscapes
This short video gives an introduction to the Activity Landscape analysis tool in StarDrop and how you can view and…
Clustering in Card View
This short video gives an introduction to the Clustering tool in StarDrop and how you can interact with the results…
Single-scaffold R-group analysis
In this quick example, we will look at a single-scaffold R-group analysis to identify any functionalities which are influencing potency. The data…
R-group decomposition
StarDrop’s R-group analysis makes it quick and easy to explore the variation of properties by the substituents within a chemical series. This…
R-group matched pairs
This short video illustrates how to perform Matched Molecular Pair Analysis (MMPA) within a chemical series using StarDrop’s R-group analysis tool. This…
Matched Series for SAR Analysis
Try Matched Series Analysis in this follow-along tutorial
Hit list triage
In this example, Card View is applied to analyse the results from a kinase project in which a large screening…
Information rich SAR plots
This short video illustrates how to create information rich SAR plots, including pie charts, histograms, scatter plots, radar plots, etc.…
Matched pairs neighbourhood analysis
This short video gives an introduction to the Matched Pairs Neighbourhood tool in StarDrop’s Card View. If you are interested…
Introduction to matched series analysis
This short movie gives an introduction to StarDrop’s Matched Series Analysis which is part of the Nova module which searches databases of…
Matched molecular pair analysis
This short video gives an introduction to the Matched Molecular Pair Analysis tool in StarDrop and how you can interact…
Activity neighbourhoods
This short video gives an introduction to the Activity Neighbourhood analysis tool in StarDrop’s Card View.
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…
Overcoming psychological barriers to good discovery decisions
Summary This article explores the psychological barriers and risks of cognitive biases to R&D decision-making. It contrasts current practice with…
Iterative refinement of a binding pocket model: active computational steering of lead optimisation
Computational approaches for binding affinity prediction are most frequently demonstrated through cross-validation within a series of molecules or through performance shown on a blinded test set. Here, we show how such a system performs in an iterative, temporal lead optimization exercise. A series of gyrase inhibitors with known synthetic order formed the set of molecules that could be selected for “synthesis.”
Preprint: considering the impact of ‘drug-like’ properties on the chance of success
Summary There are many different definitions of ‘drug-like’, with rules proposed based on property trends seen in successful drugs. In…